{"meta":{"query_hash":"25201e07f843","filters":{"topic":"Decision-Making and Behavioral Economics"},"cohort_total":1177,"direct_labels_cover":1,"predictions_cover":1177,"exported":1177,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/25201e07f843","api":"https://metacan.xera.ac/api/v1/cohort?topic=Decision-Making+and+Behavioral+Economics"},"results":[{"id":"W1035079886","doi":"10.1016/j.jom.2015.07.003","title":"How analytic reasoning style and global thinking relate to understanding stocks and flows","year":2015,"lang":"en","type":"article","venue":"Journal of Operations Management","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":40,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"National Science Foundation","keywords":"Stock (firearms); Stock management; Computer science; Cognition; Operations research; Psychology; Mathematics","score_opus":0.1809101295181473,"score_gpt":0.39032180044424364,"score_spread":0.20941167092609633,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1035079886","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.81867236,0.00017904642,0.17141095,0.0061408533,0.000401368,0.00014688115,0.0000032480825,0.00000792483,0.003037391],"genre_scores_gemma":[0.9512628,0.000026680842,0.047672875,0.00018424747,0.000054101394,0.0000012166568,2.9094997e-7,0.000005241828,0.0007925916],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9983916,0.0000710434,0.0005030401,0.00022217778,0.00067426305,0.00013786239],"domain_scores_gemma":[0.9990952,0.00008795507,0.00018719988,0.00021579827,0.00018004634,0.00023378244],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.003052631,0.000101684906,0.00023554312,0.00033546265,0.00026493924,0.0022425626,0.0002797618,0.000034244706,0.000011618764],"category_scores_gemma":[0.000526643,0.00007464756,0.00004922046,0.00040537876,0.000027503345,0.00082093745,0.00024595327,0.00010803847,0.000009740258],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028753793,0.00025709585,0.026615936,0.00001431495,0.00037601305,0.00060992927,0.00841476,0.26104164,0.000039559625,0.14038737,0.037375983,0.5245799],"study_design_scores_gemma":[0.0047126636,0.0016579094,0.017421419,0.00070900493,0.000636675,0.0009367077,0.1357421,0.20316721,0.0000090169015,0.5834585,0.050530717,0.00101812],"about_ca_topic_score_codex":0.000009693402,"about_ca_topic_score_gemma":0.00010857441,"teacher_disagreement_score":0.5235617,"about_ca_system_score_codex":0.0003119482,"about_ca_system_score_gemma":0.000040943454,"threshold_uncertainty_score":0.9987932},"labels":[],"label_agreement":null},{"id":"W132620350","doi":"10.1016/s0065-2407(08)00006-2","title":"The Development of Rational Thought: A Taxonomy of Heuristics and Biases","year":2008,"lang":"en","type":"article","venue":"Advances in child development and behavior","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":134,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University; University of Toronto","funders":"","keywords":"Psychology; Heuristics; Cognitive psychology; Cognition; Action (physics); Social psychology; Distraction; Computer science","score_opus":0.14724489174087024,"score_gpt":0.3751750156841011,"score_spread":0.22793012394323087,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W132620350","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99674827,0.0017958268,0.0004535006,0.000036979916,0.00020388656,0.0002231807,0.000008309121,0.0000063321645,0.0005237005],"genre_scores_gemma":[0.9460815,0.0005213522,0.053155888,0.000013868736,0.00001630197,0.000058085086,0.0000048291663,0.000006271723,0.00014186952],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9977638,0.00003917946,0.0011818864,0.00032662795,0.00051557424,0.00017292693],"domain_scores_gemma":[0.99816763,0.0010182183,0.0003940322,0.00020879747,0.00015071206,0.000060629154],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009455818,0.00015027233,0.0003137599,0.00018946317,0.00039225,0.00004201961,0.0003109086,0.000051750376,0.000019391779],"category_scores_gemma":[0.00044164888,0.00009691839,0.000033039407,0.00027952594,0.00034934416,0.00029641972,0.00018216517,0.00009910845,0.000004542099],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029609415,0.00013972171,0.23912978,0.0000041722856,0.0000032521573,0.0000064381184,0.0008693932,0.000012684978,0.000019163148,0.00020543559,0.000037146037,0.7595432],"study_design_scores_gemma":[0.00079298153,0.00006535279,0.82336026,0.00016712406,0.000017479922,0.00008230507,0.0013622341,0.000036815203,0.007414223,0.0017641035,0.16458982,0.00034732217],"about_ca_topic_score_codex":0.000001796387,"about_ca_topic_score_gemma":0.0001715991,"teacher_disagreement_score":0.75919586,"about_ca_system_score_codex":0.00002592964,"about_ca_system_score_gemma":0.00020267292,"threshold_uncertainty_score":0.3952217},"labels":[],"label_agreement":null},{"id":"W1482089401","doi":"10.1007/s00199-022-01453-1","title":"Uncertainty and compound lotteries: calibration","year":2022,"lang":"en","type":"article","venue":"Economic Theory","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Ambiguity; Ranking (information retrieval); Sophistication; Probabilistic logic; Preference; Decision maker; Calibration; Expected utility hypothesis; Mathematical economics; Econometrics; Public finance; Computer science; Economics; Artificial intelligence; Microeconomics; Mathematics; Statistics; Management science","score_opus":0.07113588485411494,"score_gpt":0.34808626362587763,"score_spread":0.2769503787717627,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1482089401","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99289125,0.000075308715,0.0005624895,0.00052534364,0.0010776309,0.00009462684,0.00010718096,0.00003651425,0.0046296325],"genre_scores_gemma":[0.9974202,0.0000043533564,0.00012257589,0.0006575543,0.000080488135,0.000016664306,0.000009603355,0.00001173684,0.001676831],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99847275,0.00029987094,0.000486498,0.00043585754,0.00015037468,0.000154663],"domain_scores_gemma":[0.99799675,0.0012600218,0.00020930223,0.0004448164,0.000014011107,0.00007510287],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0032640835,0.00010621202,0.00022535976,0.00015312806,0.00042291463,0.00031923846,0.00047918022,0.00002946657,0.006757435],"category_scores_gemma":[0.00014698059,0.00009569109,0.00006824416,0.00007035018,0.0001382242,0.0003119477,0.0004066827,0.00012869533,0.00030277477],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004298813,0.00008992344,0.0058691977,0.0000018913344,0.000026646898,0.000023805289,0.0026706972,0.033850886,0.00020953933,0.16220117,0.03528253,0.75934386],"study_design_scores_gemma":[0.00028262695,0.00007621052,0.00074914534,0.0000013581982,0.0000060087177,0.000048321115,0.0034091242,0.008883264,0.000023815675,0.7963079,0.19004145,0.00017077722],"about_ca_topic_score_codex":0.000037065594,"about_ca_topic_score_gemma":0.00003222717,"teacher_disagreement_score":0.75917304,"about_ca_system_score_codex":0.00016283318,"about_ca_system_score_gemma":0.00008220615,"threshold_uncertainty_score":0.9941505},"labels":[],"label_agreement":null},{"id":"W1486144121","doi":"10.2139/ssrn.1481443","title":"How Time Preferences Differ: Evidence from 45 Countries","year":2010,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":48,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of Windsor","keywords":"Hofstede's cultural dimensions theory; Individualism; Time preference; Hyperbolic discounting; Discounting; Economics; Inflation (cosmology); Scale (ratio); Uncertainty avoidance; Survey data collection; Econometrics; Microeconomics; Social psychology; Psychology; Geography; Mathematics; Statistics; Collectivism","score_opus":0.05915660571519382,"score_gpt":0.3414524829229207,"score_spread":0.28229587720772686,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1486144121","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9910148,0.0012686992,0.0020458153,0.0039647715,0.0012794426,0.000089560715,0.000022582208,0.000043056272,0.00027130003],"genre_scores_gemma":[0.9923421,0.0012142005,0.00041254616,0.00010278486,0.00063456415,0.0000035684689,0.0000021630904,0.000018770928,0.0052693007],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99560845,0.00017916583,0.0006577245,0.0005738704,0.0013000568,0.0016807457],"domain_scores_gemma":[0.99610156,0.0020075727,0.0005685048,0.0007100935,0.00040193708,0.00021033712],"candidate_categories":["scholarly_communication","research_integrity","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.006019711,0.00025289593,0.00044205476,0.00024178384,0.00045244623,0.002405426,0.002070547,0.00019936833,0.001090774],"category_scores_gemma":[0.0032991886,0.00016749912,0.00022609589,0.00028892982,0.0002037427,0.0014630401,0.00016662007,0.0026735545,0.0015394425],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013440194,0.000075165146,0.030621998,5.9536234e-7,0.000056721485,0.000011558743,0.00031811759,0.000008796083,0.006525665,0.0040882505,0.003136229,0.9550225],"study_design_scores_gemma":[0.0002585181,0.00023265964,0.005080706,0.00003394959,0.000035065073,0.00018276395,0.00076578924,0.00025465092,0.0005192741,0.97301596,0.01934773,0.00027292868],"about_ca_topic_score_codex":0.00008821682,"about_ca_topic_score_gemma":0.0024662327,"teacher_disagreement_score":0.96892774,"about_ca_system_score_codex":0.00025363127,"about_ca_system_score_gemma":0.0018694414,"threshold_uncertainty_score":0.9998224},"labels":[],"label_agreement":null},{"id":"W1488103917","doi":"10.1023/a:1011132102314","title":"Ranked-Weighted Utilities and Qualitative Convolution","year":2001,"lang":"en","type":"article","venue":"Journal of Risk and Uncertainty","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Economics","score_opus":0.10997674900266957,"score_gpt":0.4204663498269124,"score_spread":0.3104896008242428,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1488103917","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9952695,0.0015052801,0.001999767,0.00036153785,0.0003499893,0.000041298925,0.000022997223,0.0000057044867,0.0004439275],"genre_scores_gemma":[0.9971195,0.0016243252,0.0008756726,0.00006430666,0.00010179586,4.2278066e-7,5.62521e-7,0.000004300903,0.00020911974],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9980659,0.00035909525,0.0007846686,0.00018530844,0.0004587878,0.0001462459],"domain_scores_gemma":[0.99590933,0.0026162658,0.00069016515,0.00014674262,0.0004886781,0.00014883425],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0043303403,0.000110698646,0.00037684952,0.00025047956,0.00018877785,0.00020699682,0.00018283406,0.00007274873,0.00012786506],"category_scores_gemma":[0.0018011829,0.00006860326,0.000104673774,0.00020349034,0.00023023813,0.0004004335,0.000047676716,0.00021613111,0.0000115346165],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00064650754,0.000064059685,0.02966338,0.0000017259642,0.00003153202,0.000033742715,0.013506872,0.000100352634,0.00003255211,0.001186904,0.002992084,0.95174026],"study_design_scores_gemma":[0.00202938,0.00051394565,0.046752073,0.00006792225,0.00008890435,0.00044164216,0.065210484,0.004452981,0.000024762416,0.80781937,0.07235161,0.00024692016],"about_ca_topic_score_codex":0.00013940463,"about_ca_topic_score_gemma":0.00008306941,"teacher_disagreement_score":0.9514934,"about_ca_system_score_codex":0.000036819478,"about_ca_system_score_gemma":0.000057221754,"threshold_uncertainty_score":0.27975598},"labels":[],"label_agreement":null},{"id":"W1491755126","doi":"10.1023/a:1011149422763","title":"Lottery Decisions and Probability Weighting Function","year":2001,"lang":"en","type":"article","venue":"Journal of Risk and Uncertainty","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal; Université de Montréal; Université du Québec à Montréal","funders":"","keywords":"Lottery; Argument (complex analysis); Mathematical economics; Function (biology); Weighting; Preference; Economics; Econometrics; Computer science; Microeconomics","score_opus":0.08839251925516983,"score_gpt":0.3476835833279564,"score_spread":0.25929106407278657,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1491755126","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9914906,0.00050583,0.00669592,0.00038234662,0.00056103565,0.00005526489,0.000007083172,0.0000075031994,0.00029443568],"genre_scores_gemma":[0.9966395,0.0008315846,0.002160573,0.00009947257,0.00019362556,5.503579e-7,3.1066787e-7,0.0000056807758,0.00006872614],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99787474,0.00017893975,0.00096082635,0.0002741374,0.0005399639,0.00017140094],"domain_scores_gemma":[0.9955172,0.0028199262,0.00076069694,0.00025559004,0.00044063822,0.00020596132],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004726859,0.0001239352,0.00036356124,0.000262039,0.00028275125,0.00032957373,0.00023276662,0.00008580308,0.00011530239],"category_scores_gemma":[0.0048850947,0.000075045835,0.00013350094,0.00029056365,0.000118684715,0.0004716857,0.000098832505,0.00030064103,0.0000149648595],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021647091,0.00004690023,0.15303893,4.674691e-7,0.000006741807,0.000015328857,0.00017158948,0.0004238634,0.00003134847,0.00009507593,0.00092837657,0.8450249],"study_design_scores_gemma":[0.000858822,0.00038404725,0.26294786,0.000066418404,0.00007765616,0.0005325566,0.0011367032,0.0024411208,0.000009013614,0.66709024,0.06427966,0.00017587586],"about_ca_topic_score_codex":0.000041346113,"about_ca_topic_score_gemma":0.00009427116,"teacher_disagreement_score":0.84484905,"about_ca_system_score_codex":0.000042405143,"about_ca_system_score_gemma":0.000060642193,"threshold_uncertainty_score":0.5848267},"labels":[],"label_agreement":null},{"id":"W1505479660","doi":"10.48550/arxiv.1302.3603","title":"A Measure of Decision Flexibility","year":2013,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Flexibility (engineering); Measure (data warehouse); Decision maker; Variety (cybernetics); Perspective (graphical); Computer science; Value (mathematics); Decision model; Economics; Artificial intelligence; Management science; Machine learning; Data mining","score_opus":0.3615174583195565,"score_gpt":0.30306867819917177,"score_spread":0.058448780120384736,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1505479660","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96278554,0.00005244815,0.03088695,0.00003903609,0.0012440431,0.0003791883,0.000093181225,0.000073802796,0.004445792],"genre_scores_gemma":[0.9972855,0.000042819687,0.0012976975,0.00003734849,0.000060265604,8.6360853e-7,0.0000073327838,0.000023500574,0.0012447044],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99581337,0.00031513808,0.0010642711,0.0018919316,0.0005564529,0.00035886304],"domain_scores_gemma":[0.99238515,0.0016901848,0.001110822,0.0032653671,0.0012627518,0.00028570375],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002993252,0.00040578115,0.0009812929,0.00067701505,0.00013955496,0.00024236646,0.0031300397,0.00064485,0.0014918528],"category_scores_gemma":[0.0023670837,0.00035817188,0.000739211,0.00092643226,0.00033539836,0.00041731444,0.0024782761,0.0006968745,0.0014726017],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00070499006,0.00087420456,0.057725407,0.00004761405,0.00013430764,0.00028052917,0.0004495621,0.29396364,0.00017545032,0.014182694,0.01164242,0.61981916],"study_design_scores_gemma":[0.0004951086,0.000079658625,0.00988639,0.00016985771,0.00009208366,0.0000049640726,0.00030495983,0.05127057,0.00012961414,0.9352386,0.0018450203,0.0004831499],"about_ca_topic_score_codex":0.000405968,"about_ca_topic_score_gemma":0.00012759036,"teacher_disagreement_score":0.9210559,"about_ca_system_score_codex":0.00024584073,"about_ca_system_score_gemma":0.00035151944,"threshold_uncertainty_score":0.99988705},"labels":[],"label_agreement":null},{"id":"W1505811175","doi":"","title":"Friedman, Harsanyi, Rawls, Boulding - or Somebody Else?","year":2003,"lang":"en","type":"preprint","venue":"Econstor (Econstor)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"European Commission","keywords":"Economics; Quarter (Canadian coin); Inequality; Veil of ignorance; Distributive justice; Ignorance; Distributive property; Social welfare function; Inequity aversion; Welfare; Microeconomics; Social psychology; Welfare economics; Economic Justice; Psychology; Mathematics; Political science; Law","score_opus":0.12777025388606833,"score_gpt":0.38208623443595663,"score_spread":0.2543159805498883,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1505811175","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92839134,0.0015467468,0.00084892864,0.00059935957,0.023561591,0.0010518881,0.0006811498,0.00040974084,0.042909276],"genre_scores_gemma":[0.9562452,0.0003479981,0.008639913,0.0017426811,0.0015160053,0.0002184214,0.00009479414,0.00028290335,0.030912112],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9872562,0.000763969,0.004336453,0.004023449,0.001966302,0.0016535897],"domain_scores_gemma":[0.9869064,0.0035270145,0.0029475957,0.0048284675,0.0007493327,0.0010412043],"candidate_categories":["metaepi_narrow","scholarly_communication","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"category_scores_codex":[0.007004476,0.0015913441,0.003015871,0.0019722867,0.00097557,0.002919878,0.0047735665,0.0018705344,0.025139987],"category_scores_gemma":[0.0057424353,0.0013454822,0.001566065,0.0008665695,0.0010893286,0.001069149,0.002518822,0.0027522447,0.011405694],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034010448,0.0008272333,0.40985972,0.000081847335,0.00039034904,0.0007452287,0.0010252374,0.00086248195,0.0003063698,0.0020636176,0.43037912,0.1531187],"study_design_scores_gemma":[0.0030342855,0.00039277354,0.023713375,0.0009619632,0.0005031496,0.00093603344,0.0018578357,0.0011422661,0.0011361327,0.16521439,0.79560596,0.0055018337],"about_ca_topic_score_codex":0.00012666169,"about_ca_topic_score_gemma":0.00036686828,"teacher_disagreement_score":0.38614634,"about_ca_system_score_codex":0.0012256023,"about_ca_system_score_gemma":0.0030257392,"threshold_uncertainty_score":0.99968344},"labels":[],"label_agreement":null},{"id":"W1507604397","doi":"10.1002/9780470752937.ch19","title":"Framing, Loss Aversion, and Mental Accounting","year":2004,"lang":"en","type":"other","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":107,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Framing (construction); Framing effect; Mental accounting; Loss aversion; Psychology; Social psychology; Political science; Economics; Engineering; Microeconomics; Persuasion","score_opus":0.052492178356885834,"score_gpt":0.36587273031831746,"score_spread":0.3133805519614316,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1507604397","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.052445494,0.00051554677,0.00057039206,0.00024711038,0.0019638909,0.00022690734,0.000066529254,0.00018909841,0.94377506],"genre_scores_gemma":[0.04513148,0.00013870285,0.0030033707,0.00040512296,0.00029625787,0.0000026048447,0.000011041708,0.00020155536,0.95080984],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.997864,0.000024819346,0.00045964413,0.00070963346,0.0007080409,0.00023386924],"domain_scores_gemma":[0.9987327,0.00018908843,0.0003708305,0.0005475989,0.000048512116,0.00011130178],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00073525583,0.00024760995,0.00040602012,0.0004946804,0.00011595779,0.0005471293,0.0006298317,0.00033099632,0.019673955],"category_scores_gemma":[0.00025671916,0.00017699924,0.000109784036,0.00020358874,0.00014003082,0.0001528182,0.00036714663,0.00018359562,0.0036737963],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000033781632,0.000025838863,0.004175751,0.000002909389,0.000007655805,0.000018599072,0.00006726505,0.000001388536,0.0000036484355,0.00018786882,0.77036494,0.22514078],"study_design_scores_gemma":[0.00025000153,0.000019219106,0.00028670445,0.000088215485,0.000009410043,0.000023685314,0.0003017933,0.000031837604,0.000009142217,0.0113732945,0.98734635,0.00026032334],"about_ca_topic_score_codex":0.0003303857,"about_ca_topic_score_gemma":0.00037203115,"teacher_disagreement_score":0.22488046,"about_ca_system_score_codex":0.000062393956,"about_ca_system_score_gemma":0.00007621983,"threshold_uncertainty_score":0.99710196},"labels":[],"label_agreement":null},{"id":"W1509147818","doi":"10.1080/03155986.2002.11732659","title":"Une Introduction à La Modélisation Des Préférences<sup>1</sup>","year":2002,"lang":"fr","type":"article","venue":"INFOR Information Systems and Operational Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Syntax; Preference; Point (geometry); Mod; Computer science; Linguistics; Mathematics; Philosophy; Artificial intelligence; Statistics","score_opus":0.22007452792755702,"score_gpt":0.4202759952893328,"score_spread":0.20020146736177577,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1509147818","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8584901,0.0054615163,0.014371287,0.022219436,0.0034134705,0.0022193268,0.00048221686,0.00011253655,0.09323009],"genre_scores_gemma":[0.97188956,0.001140339,0.0009734255,0.00016165542,0.0012432131,0.00013501133,0.00012625114,0.000014970358,0.024315603],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.993792,0.0006535706,0.0018823862,0.00041131178,0.002677188,0.0005835234],"domain_scores_gemma":[0.99393123,0.0016941612,0.00032200216,0.0004926173,0.0032343431,0.000325625],"candidate_categories":["sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.010317851,0.00026677232,0.0003775596,0.0011235808,0.0014949914,0.00632572,0.00051685935,0.00039968893,0.0015979073],"category_scores_gemma":[0.003756561,0.00022819999,0.0000987753,0.0017171743,0.00093329215,0.011628623,0.00021429645,0.0006259633,0.005176098],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000043690205,0.00007397163,0.0005903082,0.00008096106,0.000019887662,0.0000027234191,0.0095023075,0.12393636,0.000006887482,0.0692987,0.08544659,0.7109976],"study_design_scores_gemma":[0.00036175913,0.00013438631,0.00047338346,0.00010298349,0.0000058644814,0.00012712172,0.0058905943,0.45527953,0.00000827531,0.005035707,0.5324092,0.00017120548],"about_ca_topic_score_codex":0.0016757422,"about_ca_topic_score_gemma":0.00004875738,"teacher_disagreement_score":0.7108264,"about_ca_system_score_codex":0.00035454295,"about_ca_system_score_gemma":0.00031157242,"threshold_uncertainty_score":0.9998049},"labels":[],"label_agreement":null},{"id":"W1509923280","doi":"10.1111/risa.12353","title":"The Aggregation of Expert Judgment: Do Good Things Come to Those Who Weight?","year":2015,"lang":"en","type":"letter","venue":"Risk Analysis","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":40,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Cooke Aquaculture (Canada)","funders":"","keywords":"ROWE; Domain (mathematical analysis); Public domain; Psychology; Computer science; Management science; Data science; Engineering; Economics; Management; Mathematics; Philosophy","score_opus":0.08304401179302272,"score_gpt":0.3778362966466915,"score_spread":0.29479228485366876,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1509923280","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3085911,0.009842,0.013549855,0.64661855,0.004779506,0.0014853182,0.0013558436,0.00022212462,0.013555722],"genre_scores_gemma":[0.3004124,0.011960006,0.01362021,0.5578528,0.010286711,0.00035537852,0.0008121451,0.0004624894,0.10423785],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9933248,0.00062914076,0.0017528598,0.0010499144,0.002810379,0.00043287143],"domain_scores_gemma":[0.99138784,0.0028451916,0.0019638534,0.0026281285,0.0010003321,0.0001746582],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0062063583,0.00040743136,0.0013763477,0.0014949146,0.0004140734,0.0010806839,0.002694354,0.0005631021,0.00040330287],"category_scores_gemma":[0.0021556115,0.0002353394,0.0012113721,0.0032058284,0.00015294254,0.00036489792,0.00044076092,0.00088785926,0.00090530526],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016862521,0.000021611302,0.0021333464,9.608282e-7,0.00033830418,0.000012566212,0.0008603745,0.00032484348,0.0000015084722,0.000024266727,0.7066241,0.28964126],"study_design_scores_gemma":[0.00013734896,0.000056052224,0.00029322904,0.00005467559,0.0011165777,0.000001415554,0.00032130064,0.0016137961,0.000033224853,0.01804609,0.97799736,0.00032889913],"about_ca_topic_score_codex":0.00081573846,"about_ca_topic_score_gemma":0.00019720482,"teacher_disagreement_score":0.28931236,"about_ca_system_score_codex":0.00020807922,"about_ca_system_score_gemma":0.0001258891,"threshold_uncertainty_score":0.9999563},"labels":[],"label_agreement":null},{"id":"W1511911043","doi":"10.15353/rea.v4i1.1538","title":"Stochastic Dominance and Comparative Risk Aversion","year":2012,"lang":"en","type":"article","venue":"Review of Economic Analysis","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Stochastic dominance; Dominance (genetics); Econometrics; Economics; Risk aversion (psychology); Mathematics; Biology; Mathematical economics; Expected utility hypothesis","score_opus":0.17154483041347143,"score_gpt":0.43692257316964045,"score_spread":0.265377742756169,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1511911043","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94952846,0.04411305,0.00427052,0.00009048154,0.00016754911,0.00014438275,0.00006337787,0.0000064201035,0.0016157678],"genre_scores_gemma":[0.9854837,0.013366892,0.00085449906,0.00008373038,0.000040158695,0.00000438707,0.0000048217075,0.0000034362852,0.00015836804],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9981255,0.00017472664,0.001005687,0.00034286032,0.00017361323,0.00017763175],"domain_scores_gemma":[0.9970477,0.0010835493,0.0010728483,0.00058020354,0.00008142455,0.00013425961],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0034270552,0.00013817553,0.0011377346,0.00031977074,0.00008438628,0.00004000104,0.0003472785,0.000041859574,0.0012381751],"category_scores_gemma":[0.00046966225,0.00010183248,0.00043597212,0.00046985858,0.000108065375,0.00037405913,0.00012445648,0.000080162696,0.0007950799],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000052574163,0.00018604317,0.15022124,0.0001602226,0.00093216926,8.206244e-7,0.00069035933,0.0063583353,0.000010714975,0.0027632997,0.010033593,0.82859063],"study_design_scores_gemma":[0.0032089048,0.0005617514,0.40280962,0.0059590912,0.033263933,0.0000637097,0.004598951,0.20827079,0.00028234356,0.04743163,0.28977537,0.0037738928],"about_ca_topic_score_codex":0.00005854025,"about_ca_topic_score_gemma":0.000029632207,"teacher_disagreement_score":0.82481676,"about_ca_system_score_codex":0.00006572673,"about_ca_system_score_gemma":0.000027050646,"threshold_uncertainty_score":0.9999829},"labels":[],"label_agreement":null},{"id":"W1514149724","doi":"10.2139/ssrn.2468465","title":"Loss Aversion in the Laboratory","year":2014,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Wilfrid Laurier University","funders":"Social Sciences and Humanities Research Council of Canada; Rheinische Friedrich-Wilhelms-Universität Bonn","keywords":"Loss aversion; Risk aversion (psychology); Preference; Compensation (psychology); Economics; Task (project management); Experimental economics; Taste aversion; Psychology; Actuarial science; Microeconomics; Social psychology; Expected utility hypothesis; Financial economics","score_opus":0.03458233949557936,"score_gpt":0.341083179402152,"score_spread":0.3065008399065726,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1514149724","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.992705,0.00023086541,0.0028354859,0.0019847674,0.00040295263,0.000049269416,0.0000013808507,0.000008875297,0.0017813968],"genre_scores_gemma":[0.9986633,0.00021050827,0.00005328206,0.00052942237,0.0002129861,0.0000011977504,3.8277418e-7,0.000007993517,0.0003208992],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99689716,0.0004656974,0.00049963506,0.0002475281,0.00075746793,0.0011325377],"domain_scores_gemma":[0.99835676,0.00078320404,0.00023591066,0.00042816435,0.00013883079,0.000057154884],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02013353,0.00010910975,0.00018521961,0.00024398309,0.00023634241,0.00032462183,0.0012907035,0.00007422462,0.00009408394],"category_scores_gemma":[0.001174418,0.000061671635,0.00011036221,0.00055567943,0.00006181075,0.00032331573,0.000058838483,0.0014124857,0.000685024],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004868642,0.00009353412,0.015905647,3.1930014e-7,0.000006750291,0.000012782277,0.00041836067,0.00019658176,0.00007471117,0.044264104,0.0026100888,0.9363684],"study_design_scores_gemma":[0.00037533807,0.00016738649,0.002766736,0.0000072458065,0.0000057286907,0.00019175393,0.0028636772,0.00029249082,0.000015510372,0.9265727,0.06663722,0.00010423343],"about_ca_topic_score_codex":0.000018095778,"about_ca_topic_score_gemma":0.00058423454,"teacher_disagreement_score":0.9362642,"about_ca_system_score_codex":0.00034711338,"about_ca_system_score_gemma":0.00072723033,"threshold_uncertainty_score":0.8804826},"labels":[],"label_agreement":null},{"id":"W1514261845","doi":"10.2139/ssrn.1584185","title":"Loss Aversion and Intertemporal Choice: A Laboratory Investigation","year":2010,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University; University of Calgary","funders":"Rheinische Friedrich-Wilhelms-Universität Bonn","keywords":"Economics; Loss aversion; Intertemporal choice; Windfall gain; Context (archaeology); Behavioral economics; Microeconomics; Econometrics; Macroeconomics","score_opus":0.033644501839931173,"score_gpt":0.33996892568587556,"score_spread":0.3063244238459444,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1514261845","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99677837,0.00017487525,0.0005554331,0.0012836452,0.00092571316,0.000057572848,0.000004054868,0.000022150647,0.00019817511],"genre_scores_gemma":[0.99862003,0.00012986205,0.00025084044,0.00020211884,0.00028789963,0.0000012192504,0.0000013861396,0.000013043693,0.0004936119],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9976141,0.0001138718,0.0005230937,0.0003360457,0.00052795344,0.0008849529],"domain_scores_gemma":[0.99854344,0.00032606104,0.00035236398,0.00030716043,0.00027478772,0.00019620698],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0060504708,0.00014166752,0.00020872458,0.00029534366,0.0002987121,0.00045803882,0.00053677714,0.00013587959,0.00012172674],"category_scores_gemma":[0.0012918491,0.000105922925,0.000081020764,0.00033867417,0.00016703366,0.0007494447,0.000105171865,0.0020137355,0.0001940546],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000065794426,0.000059826634,0.19280589,0.0000012939249,0.000025316565,0.000013811512,0.00040997192,0.00000809983,0.008001669,0.01301059,0.0022521163,0.78334564],"study_design_scores_gemma":[0.00060484285,0.00021499892,0.00971703,0.000013555734,0.000016020062,0.00043764108,0.0011541917,0.00036263684,0.00032217588,0.9661979,0.020751722,0.00020729787],"about_ca_topic_score_codex":0.00004000548,"about_ca_topic_score_gemma":0.0014762293,"teacher_disagreement_score":0.9531873,"about_ca_system_score_codex":0.00019515316,"about_ca_system_score_gemma":0.0012535815,"threshold_uncertainty_score":0.8748791},"labels":[],"label_agreement":null},{"id":"W1515016839","doi":"10.1037/per0000099","title":"Choice impulsivity: Definitions, measurement issues, and clinical implications.","year":2015,"lang":"en","type":"article","venue":"Personality Disorders Theory Research and Treatment","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Centre for Addiction and Mental Health","funders":"National Center for Advancing Translational Sciences; Pfizer; National Institute of Mental Health; National Cancer Institute; National Institute on Alcohol Abuse and Alcoholism; AstraZeneca; National Institute on Drug Abuse; National Center for Responsible Gaming; State of Connecticut Department of Mental Health and Addiction Services; National Institutes of Health; H. Lundbeck A/S; Rush University","keywords":"Impulsivity; Psychology; Task (project management); Construct (python library); Clinical psychology; Delay discounting; Human studies; Medicine; Computer science","score_opus":0.7271465109527111,"score_gpt":0.5608638769486375,"score_spread":0.16628263400407362,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1515016839","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97894573,0.003989665,0.00016968143,0.012642944,0.00009676235,0.00045268907,0.000097410964,0.00003293552,0.0035721785],"genre_scores_gemma":[0.9967309,0.00212353,0.00036391563,0.00010197288,0.000082500155,0.000083677274,0.000013055448,0.00001257945,0.00048781573],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99555147,0.0013938834,0.00056806125,0.00081607135,0.0012539054,0.00041661048],"domain_scores_gemma":[0.99446356,0.003435733,0.00010784211,0.0006732743,0.00070945383,0.00061015034],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.016320085,0.00018684204,0.00037075742,0.00021735305,0.0005377906,0.0004973365,0.0003169627,0.0000997632,0.00009709751],"category_scores_gemma":[0.0053445934,0.00012971248,0.00011893026,0.00035620108,0.0008400871,0.00023747704,0.00022486088,0.0002115945,0.0001970563],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016666512,0.0009255232,0.22594903,0.0000016585628,0.00005147299,0.0000022747986,0.00039933846,5.430984e-7,0.0000024900048,0.01752591,0.0024122675,0.7525628],"study_design_scores_gemma":[0.0011152441,0.0008595333,0.13520771,0.000009316644,0.000025286075,0.000008030316,0.0018677278,0.000040592084,0.0000030812814,0.80989426,0.050834693,0.00013453313],"about_ca_topic_score_codex":0.0012317026,"about_ca_topic_score_gemma":0.0029030147,"teacher_disagreement_score":0.79236835,"about_ca_system_score_codex":0.00024929954,"about_ca_system_score_gemma":0.00027841024,"threshold_uncertainty_score":0.6398364},"labels":[],"label_agreement":null},{"id":"W1517449658","doi":"10.2139/ssrn.977508","title":"Gender, Affect and Intertemporal Consistency: An Experimental Approach","year":2007,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":26,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Affect (linguistics); Consistency (knowledge bases); Mood; Patience; Intertemporal choice; Psychology; Hyperbolic discounting; Discounting; Time preference; Delay discounting; Temporal discounting; Social psychology; Economics; Econometrics; Developmental psychology; Impulsivity; Mathematics; Microeconomics","score_opus":0.12037323552242123,"score_gpt":0.40336481414484554,"score_spread":0.2829915786224243,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1517449658","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9769843,0.0019435034,0.016105022,0.000051165123,0.00042256937,0.00010054616,0.0000017680921,0.000028551442,0.0043625813],"genre_scores_gemma":[0.998194,0.00008781486,0.0010718566,0.000108815984,0.00019919167,0.0000015545395,0.0000019543431,0.000020083333,0.0003147421],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99637735,0.00016943995,0.0007240241,0.00049775885,0.00066147844,0.0015699484],"domain_scores_gemma":[0.99868435,0.00025931987,0.00030563166,0.0003717142,0.00011024524,0.00026873325],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012672049,0.00020468973,0.0003313515,0.0003433094,0.00035673814,0.00047682744,0.0006398274,0.00011745212,0.00006877163],"category_scores_gemma":[0.00021938547,0.00015033015,0.00015552444,0.00023688223,0.00016044312,0.0006334266,0.00011573116,0.0010994693,0.000044024117],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002942797,0.0005084856,0.019791316,0.0000011588794,0.00005411407,0.000038933507,0.0014032488,0.000013701266,0.0019449753,0.033301916,0.00037007005,0.9422778],"study_design_scores_gemma":[0.0015992557,0.001614573,0.004843158,0.000011369112,0.000036375903,0.0063850675,0.053998116,0.0008147919,0.0009290362,0.9271282,0.0020783679,0.00056169805],"about_ca_topic_score_codex":0.000027210393,"about_ca_topic_score_gemma":0.0001939352,"teacher_disagreement_score":0.9417161,"about_ca_system_score_codex":0.00047334933,"about_ca_system_score_gemma":0.00074961194,"threshold_uncertainty_score":0.6130285},"labels":[],"label_agreement":null},{"id":"W1517480665","doi":"10.2139/ssrn.612503","title":"Diminishing Impatience and Non-Expected Utility: A Unified Framework","year":2004,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Economics; Econometrics; Computer science","score_opus":0.0528057114462755,"score_gpt":0.3590281226503948,"score_spread":0.3062224112041193,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1517480665","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9447527,0.00046467825,0.05283418,0.0009020143,0.00043146397,0.000092354276,0.0000028398113,0.000030016094,0.00048975827],"genre_scores_gemma":[0.9971029,0.00041148692,0.0020377962,0.00016776442,0.00014596489,0.0000023117263,6.1326784e-7,0.00001659406,0.000114524664],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99613947,0.000090711444,0.0007805939,0.0005175334,0.00079576304,0.00167595],"domain_scores_gemma":[0.9980634,0.0005886658,0.00041393907,0.00048789737,0.00022401378,0.00022211506],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0049570813,0.00020638725,0.0003682897,0.00028806072,0.00051186426,0.0008042382,0.0009115604,0.00016437002,0.00007291654],"category_scores_gemma":[0.0022766038,0.00015519862,0.00014458793,0.00064526795,0.0001442884,0.00070588064,0.00016668865,0.002053404,0.0001035009],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000116834155,0.00013560177,0.01306547,9.0004426e-7,0.00003058491,0.00002571778,0.0016563663,0.00018009578,0.00013717517,0.023586813,0.00005821601,0.9610062],"study_design_scores_gemma":[0.00049431174,0.00035147072,0.006215537,0.000039979393,0.000015946134,0.00040530993,0.005207832,0.00018339639,0.000053200747,0.9863993,0.00043806183,0.00019566577],"about_ca_topic_score_codex":0.000084592866,"about_ca_topic_score_gemma":0.00041296493,"teacher_disagreement_score":0.9628125,"about_ca_system_score_codex":0.0005146072,"about_ca_system_score_gemma":0.0018106473,"threshold_uncertainty_score":0.8921133},"labels":[],"label_agreement":null},{"id":"W1526201865","doi":"10.1007/s11166-017-9264-0","title":"Learning-by-doing in an ambiguous environment","year":2017,"lang":"en","type":"article","venue":"Journal of Risk and Uncertainty","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":21,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Center for Interuniversity Research and Analysis on Organizations","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Ambiguity; Ambiguity aversion; Expected utility hypothesis; Session (web analytics); Measure (data warehouse); Economics; Microeconomics; Psychology; Actuarial science; Social psychology; Computer science; Mathematical economics","score_opus":0.05447298923000997,"score_gpt":0.36696709040145403,"score_spread":0.31249410117144405,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1526201865","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99856526,0.00023549795,0.0005091819,0.00017415517,0.0002590998,0.000028445453,0.0000060711573,0.0000025018394,0.0002198135],"genre_scores_gemma":[0.99841875,0.00069374597,0.00063543936,0.000026915975,0.0000832398,3.4789014e-7,3.4895888e-7,0.0000060491257,0.00013518726],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.998316,0.00016428529,0.00066732336,0.00021668973,0.0004726512,0.00016304174],"domain_scores_gemma":[0.9979427,0.00025960247,0.0011922886,0.00036989732,0.00007500661,0.00016049453],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036021098,0.00010208721,0.00032808012,0.00016135233,0.00038274185,0.0006493182,0.00063382083,0.0000692341,0.000101299156],"category_scores_gemma":[0.0013471472,0.00006863637,0.00009276199,0.000036526577,0.000118512566,0.0005832857,0.000112465255,0.0004019983,0.000024083904],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000067933775,0.000056114313,0.1335334,2.6307396e-7,0.0000023559646,0.00003243983,0.00045835806,0.0056044115,0.00009180916,0.0000046707873,0.0002489535,0.8598993],"study_design_scores_gemma":[0.002721157,0.0015528175,0.77109253,0.000096774755,0.000053802203,0.00016021263,0.005723015,0.010641678,0.00012445654,0.059065677,0.14831299,0.0004548983],"about_ca_topic_score_codex":0.00034605464,"about_ca_topic_score_gemma":0.00013972631,"teacher_disagreement_score":0.8594444,"about_ca_system_score_codex":0.000056816283,"about_ca_system_score_gemma":0.000033541313,"threshold_uncertainty_score":0.6261391},"labels":[],"label_agreement":null},{"id":"W1526936651","doi":"10.3386/w21400","title":"Do Risk Preferences Change? Evidence from Panel Data before and after the Great East Japan Earthquake","year":2015,"lang":"en","type":"preprint","venue":"National Bureau of Economic Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":63,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Panel data; Geography; Economics; Econometrics","score_opus":0.827360945244902,"score_gpt":0.5793973896884685,"score_spread":0.24796355555643346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1526936651","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9877982,0.0020457876,0.0000072021726,0.0022201566,0.00072121393,0.00072685507,0.0039147283,0.000013879062,0.0025519906],"genre_scores_gemma":[0.9969,0.0007260522,0.0004611699,0.000034852157,0.00094258494,0.00015795985,0.00027776483,0.00002434423,0.00047523744],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.992845,0.0009577376,0.0012824333,0.0018909712,0.002595226,0.00042862853],"domain_scores_gemma":[0.9873669,0.0069952523,0.0008000307,0.0028202229,0.0017581889,0.000259402],"candidate_categories":["metaresearch","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.023059815,0.00032754274,0.00070278,0.0007120295,0.00026784945,0.001490803,0.005465186,0.0004440669,0.0011961919],"category_scores_gemma":[0.009519409,0.00021328598,0.00014669647,0.00024629536,0.0009144172,0.001038417,0.007240953,0.0013429052,0.0007741983],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004311432,0.00006843578,0.23533475,0.000014618556,0.000103548075,0.000004274808,0.0022845047,0.0004157135,0.000002269922,0.0008899991,0.014379545,0.7460712],"study_design_scores_gemma":[0.00019016888,0.00008585394,0.1575778,0.00023749706,0.000027070124,0.000005437993,0.00065648445,0.0067324652,0.0000022892896,0.83220446,0.0020822703,0.00019819576],"about_ca_topic_score_codex":0.006136814,"about_ca_topic_score_gemma":0.011958131,"teacher_disagreement_score":0.83131444,"about_ca_system_score_codex":0.00024579884,"about_ca_system_score_gemma":0.001230562,"threshold_uncertainty_score":0.9999157},"labels":[],"label_agreement":null},{"id":"W1527239430","doi":"10.2139/ssrn.2363870","title":"Uncertainty, Ambiguity and Risk Taking: An Experimental Investigation of Consumer Behavior and Demand for Insurance","year":2013,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal; Université de Sherbrooke","funders":"","keywords":"Ambiguity; Actuarial science; Consumer behaviour; Consumer demand; Business; Risk analysis (engineering); Economics; Microeconomics; Marketing; Computer science","score_opus":0.0696357363310113,"score_gpt":0.36868115798492423,"score_spread":0.2990454216539129,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1527239430","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99707985,0.0015831171,0.0008115363,0.00005839195,0.00013646272,0.00028715518,0.000018602383,0.000008792621,0.000016087795],"genre_scores_gemma":[0.9985572,0.0006620752,0.000625669,0.000028272514,0.000046661673,0.000024443494,0.0000019062765,0.000011981104,0.0000417602],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9979225,0.00015424535,0.0006123199,0.00033362416,0.00032875,0.0006485715],"domain_scores_gemma":[0.99809635,0.00033384416,0.0009273414,0.00021515558,0.00026741237,0.00015987438],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033798495,0.00014260315,0.00028648408,0.00015752425,0.0002958805,0.0002968818,0.00027856042,0.00008748096,0.000036873786],"category_scores_gemma":[0.0005854843,0.00010861252,0.00006781942,0.00012142633,0.00025410074,0.0006929948,0.00006006527,0.00043800968,0.00000581777],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000054622054,0.000065072476,0.5229068,0.000001227547,0.000016879423,4.3833472e-7,0.00039043342,0.000027429098,0.004441952,0.0010680408,0.000060087783,0.47096705],"study_design_scores_gemma":[0.0014338784,0.00096718373,0.34648597,0.000019574352,0.00005716613,0.00024124302,0.0040365253,0.0010592164,0.0021820883,0.6431256,0.00014357863,0.00024800573],"about_ca_topic_score_codex":0.00037541546,"about_ca_topic_score_gemma":0.00054512674,"teacher_disagreement_score":0.64205754,"about_ca_system_score_codex":0.00013391898,"about_ca_system_score_gemma":0.0003433865,"threshold_uncertainty_score":0.442909},"labels":[],"label_agreement":null},{"id":"W1527443085","doi":"10.1016/b978-0-08-097086-8.43033-3","title":"Decision and Choice: Random Utility Models of Choice and Response Time","year":2015,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Accumulator (cryptography); Representation (politics); Multiplicative function; Discrete choice; Context (archaeology); Mathematics; Expected utility hypothesis; Independence (probability theory); Econometrics; Computer science; Statistics; Algorithm","score_opus":0.12917386761093932,"score_gpt":0.3718050079174472,"score_spread":0.24263114030650787,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1527443085","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21437287,0.003774084,0.00011223811,0.0000740099,0.00052032986,0.00078194955,0.0002830176,0.000051204854,0.7800303],"genre_scores_gemma":[0.063535176,0.000114286275,0.0015066075,0.0000971385,0.00014470871,0.000011297644,0.0000071087775,0.000082347426,0.93450135],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9948302,0.00025419926,0.0017958045,0.0012924774,0.0015032424,0.00032410197],"domain_scores_gemma":[0.9878176,0.008423101,0.0009836478,0.0015976103,0.00074538746,0.00043263877],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.008839236,0.000567813,0.0016476879,0.0006047778,0.00017893585,0.00030701206,0.00086587155,0.00064327434,0.00044641],"category_scores_gemma":[0.003631485,0.00043369326,0.00030037647,0.000051916402,0.00061168574,0.00029263613,0.00079047674,0.00049625564,0.0002394501],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011181846,0.000014383409,0.0000522982,0.0000068488125,0.000022023794,0.000009149678,0.00017929776,0.000008372927,0.000027687944,0.00012548424,0.0012730181,0.99716324],"study_design_scores_gemma":[0.0015089603,0.00013518993,0.0002428617,0.00026076013,0.00009069512,0.000026495953,0.000013924842,0.0013871384,0.000006139929,0.3667022,0.62925375,0.00037188013],"about_ca_topic_score_codex":0.000004194905,"about_ca_topic_score_gemma":0.000044919598,"teacher_disagreement_score":0.99679136,"about_ca_system_score_codex":0.0000837037,"about_ca_system_score_gemma":0.00031611358,"threshold_uncertainty_score":0.9998115},"labels":[],"label_agreement":null},{"id":"W1534693585","doi":"10.1108/00251740710762026","title":"The positive side of negative framing","year":2007,"lang":"en","type":"article","venue":"Management Decision","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Overconfidence effect; Framing (construction); Framing effect; Originality; Decision quality; Psychology; Social psychology; Computer science; Knowledge management","score_opus":0.05900356430257299,"score_gpt":0.3929994382646191,"score_spread":0.3339958739620461,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1534693585","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8307933,0.00009218409,0.10589405,0.00021370346,0.0009285667,0.00030491393,0.000007097008,0.000025285228,0.06174089],"genre_scores_gemma":[0.9864535,0.000044140605,0.011508328,0.00016372798,0.000048821712,0.000003641178,0.0000010767989,0.000013316583,0.001763462],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99630487,0.000087605775,0.0011944928,0.0005178297,0.0015409956,0.00035419094],"domain_scores_gemma":[0.9888377,0.009312942,0.00042511415,0.0010002574,0.0003273081,0.00009663555],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0081784725,0.00016861776,0.0002847581,0.00042112387,0.00042210863,0.00034371385,0.0013095535,0.000072883464,0.000092992275],"category_scores_gemma":[0.0020386798,0.00009975491,0.00019697548,0.00092442543,0.00017162392,0.00027272452,0.0006298996,0.00014457369,0.0005163254],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000185882,0.00004614905,0.0018702924,6.6852095e-7,0.000015637663,0.00003641112,0.00018269647,0.00013722207,0.000041506955,0.004131488,0.0030605271,0.99029154],"study_design_scores_gemma":[0.00070137315,0.00016281895,0.17816299,0.00010242541,0.000037633,0.0000063883517,0.0056109424,0.00069000374,0.0022958883,0.75466824,0.057297975,0.00026333434],"about_ca_topic_score_codex":0.000020049465,"about_ca_topic_score_gemma":0.0000946484,"teacher_disagreement_score":0.9900282,"about_ca_system_score_codex":0.000081270024,"about_ca_system_score_gemma":0.000013500691,"threshold_uncertainty_score":0.6636491},"labels":[],"label_agreement":null},{"id":"W1537799777","doi":"10.7202/1105357ar","title":"LA PERCEPTION DU RISQUE D’ÊTRE ARRÊTÉ CHEZ LES CAMIONNEURS ET TRANSPORTEURS ROUTIERS","year":2001,"lang":"fr","type":"article","venue":"Assurances :","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Humanities; Political science; Philosophy","score_opus":0.06677083715056875,"score_gpt":0.3590834296888816,"score_spread":0.2923125925383128,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1537799777","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9441414,0.0017181132,0.0027977172,0.01317459,0.0046797656,0.00024158414,0.0001566122,0.000118770964,0.032971483],"genre_scores_gemma":[0.98749495,0.0047780788,0.0006962,0.00044403336,0.00040887075,0.00001880117,0.000026307696,0.00005324351,0.0060795452],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99510664,0.0009389646,0.0011932901,0.0011098234,0.0009607236,0.0006905827],"domain_scores_gemma":[0.9968962,0.0012954209,0.00048304454,0.0007354879,0.00026134972,0.0003285156],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.004008806,0.0004997953,0.0007339388,0.000333011,0.00046232954,0.00065490353,0.0010606019,0.0005673335,0.0031107953],"category_scores_gemma":[0.00043716465,0.00044747753,0.00053613615,0.00091864564,0.0007837649,0.0013748491,0.00005597438,0.0007115135,0.0015080549],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007947855,0.0002445248,0.15568191,0.000009464939,0.000022793429,0.00024114273,0.0033718594,0.0038890785,0.00012293803,0.00032233793,0.0041093263,0.8319051],"study_design_scores_gemma":[0.0011217076,0.0002585132,0.34722704,0.00033539045,0.00016357627,0.00047403923,0.013283049,0.00402325,0.000053658663,0.015597995,0.6165215,0.0009402965],"about_ca_topic_score_codex":0.0028418389,"about_ca_topic_score_gemma":0.0043409276,"teacher_disagreement_score":0.83096486,"about_ca_system_score_codex":0.00025549022,"about_ca_system_score_gemma":0.00021003112,"threshold_uncertainty_score":0.9997977},"labels":[],"label_agreement":null},{"id":"W1541720588","doi":"10.2139/ssrn.712062","title":"Testing Explanations of Preference Reversal: A Model","year":2005,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal; Université de Montréal; Université du Québec à Montréal","funders":"","keywords":"Preference; Psychology; Econometrics; Economics; Microeconomics","score_opus":0.23211127011483162,"score_gpt":0.38856080744715793,"score_spread":0.1564495373323263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1541720588","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9517616,0.00026314578,0.043918587,0.00061854493,0.00009742001,0.0000559805,0.000006417868,0.000020591633,0.00325771],"genre_scores_gemma":[0.99031156,0.00010694499,0.008292228,0.000059401103,0.000102254184,0.0000017639247,5.294491e-7,0.000010619569,0.0011147251],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99734485,0.000065989116,0.0007689161,0.00024794342,0.00064642093,0.000925853],"domain_scores_gemma":[0.9981185,0.00054683146,0.0005009815,0.00032180123,0.00042725742,0.00008460157],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004678373,0.00010946687,0.00022746237,0.00029110152,0.00017719904,0.00012495731,0.00080513157,0.0000626756,0.00006016403],"category_scores_gemma":[0.0020933484,0.000083687846,0.00011458913,0.00043765228,0.000046529763,0.0005354754,0.00007093709,0.00080843753,0.00011142441],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018261091,0.00006982882,0.0017870471,3.6331167e-7,0.000011809219,6.6672794e-7,0.00019322197,0.02018684,0.00060776534,0.014800777,0.00054777483,0.96177566],"study_design_scores_gemma":[0.0002763011,0.0001197148,0.00040022825,0.000018882047,0.000016639175,0.00017474216,0.00084503,0.05655962,0.00010358724,0.9401977,0.0011659861,0.00012158921],"about_ca_topic_score_codex":0.000018104214,"about_ca_topic_score_gemma":0.00041915744,"teacher_disagreement_score":0.96165407,"about_ca_system_score_codex":0.00039385865,"about_ca_system_score_gemma":0.0018007364,"threshold_uncertainty_score":0.35123038},"labels":[],"label_agreement":null},{"id":"W1543954364","doi":"10.3386/w14020","title":"Measuring the Output and Prices of the Lottery Sector: An Application of Implicit Expected Utility Theory","year":2008,"lang":"en","type":"preprint","venue":"National Bureau of Economic Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Lottery; Econometrics; Economics; Mathematical economics; Computer science; Microeconomics","score_opus":0.6097145243407278,"score_gpt":0.5383874558340881,"score_spread":0.07132706850663972,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1543954364","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9886506,0.00022813135,0.00024510815,0.00031813973,0.00020523588,0.0006620189,0.00014696625,0.000007645785,0.009536115],"genre_scores_gemma":[0.99940753,0.00007533069,0.00020654363,0.000014502249,0.00011724003,0.00005477647,0.000015050254,0.000014537839,0.000094477684],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9952045,0.00079703215,0.0014108926,0.0007510075,0.0016150628,0.00022149693],"domain_scores_gemma":[0.990144,0.0055267275,0.0011760712,0.0014261885,0.0016555403,0.00007145083],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.014606115,0.00017901273,0.0005419811,0.00054410676,0.00022439529,0.00011574385,0.00249474,0.0002568329,0.0000817241],"category_scores_gemma":[0.0025901746,0.00010938949,0.00023049189,0.00028680466,0.0010066687,0.000206466,0.0014031164,0.00062603684,0.000013864965],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011197659,0.0010653627,0.13060798,0.00020585625,0.00037148473,0.0000011132016,0.0060291127,0.0193119,0.0071306736,0.23088889,0.004587449,0.59868044],"study_design_scores_gemma":[0.00017517566,0.000038943952,0.10073017,0.000039649018,0.00000954298,0.0000054257844,0.0004722007,0.006310806,0.0019185207,0.8899064,0.00028562624,0.00010752548],"about_ca_topic_score_codex":0.00065151503,"about_ca_topic_score_gemma":0.00018574386,"teacher_disagreement_score":0.6590175,"about_ca_system_score_codex":0.00021947728,"about_ca_system_score_gemma":0.000880636,"threshold_uncertainty_score":0.5062217},"labels":[],"label_agreement":null},{"id":"W1555008460","doi":"10.1007/s11238-017-9597-9","title":"Conditional expected utility","year":2017,"lang":"en","type":"article","venue":"Theory and Decision","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Expected utility hypothesis; Subjective expected utility; Von Neumann–Morgenstern utility theorem; Mathematical economics; Axiom; Preference; Class (philosophy); Mathematics; Decision theory; Separable space; Utility theory; Representation theorem; Preference theory; Conditional probability; Consistency (knowledge bases); Discrete mathematics; Computer science; Artificial intelligence; Statistics","score_opus":0.15982006671841248,"score_gpt":0.45042826275737896,"score_spread":0.2906081960389665,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1555008460","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95805675,0.00009280984,0.029229958,0.00011499755,0.0006109892,0.000082769395,0.00004464071,0.000035217865,0.011731886],"genre_scores_gemma":[0.99759513,0.000013087241,0.0015187588,0.0001556953,0.00009447262,0.0000038002381,0.0000044243743,0.000007918473,0.0006067004],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9978255,0.00018344073,0.00054740126,0.00058256433,0.00066619203,0.00019491544],"domain_scores_gemma":[0.9931557,0.0046244585,0.00033561868,0.0015057623,0.00020710049,0.00017134732],"candidate_categories":["metaresearch","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0066245147,0.00014701062,0.00030278065,0.00015424874,0.0012033598,0.0010743621,0.0010275169,0.00011561616,0.0026818875],"category_scores_gemma":[0.0092586465,0.000101307254,0.0001160632,0.00007601053,0.0004415953,0.00070335926,0.00045509086,0.00014026208,0.0009937347],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045712414,0.00004766797,0.0041010906,2.992225e-7,0.0000033393237,0.000015532252,0.000086487256,0.0000031633242,0.00007970983,0.037956186,0.003190912,0.95405847],"study_design_scores_gemma":[0.00038912866,0.000038742513,0.1254107,0.000012444024,0.000006404549,0.000022913126,0.00019454607,0.00026242668,0.00012293056,0.86391973,0.009501344,0.00011868908],"about_ca_topic_score_codex":0.000005872322,"about_ca_topic_score_gemma":0.0000102795975,"teacher_disagreement_score":0.9539398,"about_ca_system_score_codex":0.000014124852,"about_ca_system_score_gemma":0.000035439967,"threshold_uncertainty_score":0.9999626},"labels":[],"label_agreement":null},{"id":"W1560211103","doi":"10.1016/s0079-7421(02)80011-1","title":"Real-world estimation: Estimation modes and seeding effects","year":2002,"lang":"en","type":"book-chapter","venue":"˜The œPsychology of learning and motivation/˜The œpsychology of learning and motivation","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":34,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; University of Alberta","keywords":"Seeding; Estimation; Metric (unit); Set (abstract data type); Computer science; Range (aeronautics); Inference; Algorithm; Mathematics; Artificial intelligence; Econometrics; Machine learning; Engineering","score_opus":0.08959038753598943,"score_gpt":0.38240254512252264,"score_spread":0.29281215758653323,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1560211103","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90672797,0.0010628031,0.020432444,0.0029521708,0.00064990605,0.00092891935,0.000013133695,0.00017821748,0.06705442],"genre_scores_gemma":[0.9527682,0.0010736306,0.0024389888,0.00021687355,0.00012922665,0.000026646861,0.00005539726,0.000082431456,0.043208614],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99492896,0.00072596106,0.0018237418,0.001357224,0.0007387543,0.0004253646],"domain_scores_gemma":[0.98872334,0.0070539275,0.0028490722,0.0007019292,0.0005318288,0.00013991164],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0043618917,0.0006369018,0.0011602559,0.0012021844,0.0010733964,0.00018834345,0.00053432456,0.0007957143,0.00013712906],"category_scores_gemma":[0.0024356497,0.00047085123,0.00019908979,0.0004102123,0.0016891373,0.00035612637,0.00022067306,0.001747738,0.00003335026],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032169992,0.0001408355,0.10683243,0.00011806111,0.00025105383,0.000008771465,0.0023635628,0.010037094,0.0011541389,0.007343833,0.0022569064,0.8691716],"study_design_scores_gemma":[0.0054530683,0.0026052438,0.65129876,0.002060037,0.0008574178,0.00047274728,0.0015929341,0.0581555,0.00009754268,0.1956921,0.07972057,0.0019941016],"about_ca_topic_score_codex":0.000039702874,"about_ca_topic_score_gemma":0.000018700704,"teacher_disagreement_score":0.8671775,"about_ca_system_score_codex":0.00003719641,"about_ca_system_score_gemma":0.000041379335,"threshold_uncertainty_score":0.99977434},"labels":[],"label_agreement":null},{"id":"W1562845750","doi":"10.3389/fpsyg.2015.00728","title":"Four converging measures of temporal discounting and their relationships with intelligence, executive functions, thinking dispositions, and behavioral outcomes","year":2015,"lang":"en","type":"article","venue":"Frontiers in Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":68,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Centre of Excellence for Child and Youth Mental Health; York University","funders":"","keywords":"Temporal discounting; Psychology; Discounting; Intertemporal choice; Cognition; Delay discounting; Set (abstract data type); Variance (accounting); Executive functions; Sample (material); Task (project management); Cognitive psychology; Function (biology); Impulsivity; Developmental psychology; Econometrics; Neuroscience; Mathematics","score_opus":0.21716648586567816,"score_gpt":0.3985975209715493,"score_spread":0.18143103510587116,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1562845750","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.81506073,0.0005061354,0.18224075,0.00051051925,0.0009423448,0.0001495376,0.000020906366,0.000019037781,0.00055002276],"genre_scores_gemma":[0.98160255,0.000026309339,0.01816436,0.000081198414,0.000019093286,0.0000119733895,0.0000060480056,0.000012841445,0.00007562933],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9980636,0.00028078275,0.00068015035,0.00045586744,0.00030365272,0.00021592985],"domain_scores_gemma":[0.9985993,0.00040829138,0.0003467581,0.00036306094,0.00017652447,0.00010610172],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002674082,0.00018015286,0.0004696958,0.0006198006,0.00018895707,0.00012829724,0.000295429,0.0001355437,0.000006171286],"category_scores_gemma":[0.00043580864,0.00012217335,0.000048603517,0.00045281218,0.00046060112,0.00047380844,0.000099821984,0.00031719005,0.0000040619507],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010158777,0.00005820213,0.8627346,9.676186e-7,0.000011658295,0.00000590366,0.002540083,0.000032406595,0.000003532216,0.0001949827,0.0017291426,0.13258691],"study_design_scores_gemma":[0.0011484689,0.0003792548,0.44671166,0.00010472164,0.0000551464,0.00013508042,0.09402249,0.0011523062,0.000020665902,0.45310003,0.0027544538,0.00041571553],"about_ca_topic_score_codex":0.000075133095,"about_ca_topic_score_gemma":0.00024023835,"teacher_disagreement_score":0.45290503,"about_ca_system_score_codex":0.000042085478,"about_ca_system_score_gemma":0.00005104808,"threshold_uncertainty_score":0.4982085},"labels":[],"label_agreement":null},{"id":"W1564198999","doi":"10.2139/ssrn.899006","title":"Updating Preferences with Multiple Priors","year":2006,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":92,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Prior probability; Econometrics; Computer science; Mathematics; Bayesian probability; Statistics; Artificial intelligence","score_opus":0.04017279883567929,"score_gpt":0.32446387942160865,"score_spread":0.28429108058592933,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1564198999","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98769146,0.00029897233,0.0074183806,0.00031006135,0.00021924675,0.00008361293,0.000003016325,0.000035573958,0.003939672],"genre_scores_gemma":[0.99686056,0.00006691875,0.0012935603,0.000038587612,0.00025397487,0.0000028153058,0.000001984429,0.000017560571,0.0014640519],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9962399,0.00011865315,0.00073602836,0.00040000665,0.0008936692,0.0016117293],"domain_scores_gemma":[0.99827254,0.0005168498,0.00053655286,0.00034052355,0.00024794598,0.00008558348],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0046694046,0.0001814927,0.00028215075,0.00025630576,0.00040787522,0.0006104588,0.00086935534,0.000075714306,0.0001339831],"category_scores_gemma":[0.00046983708,0.000111287445,0.00012069313,0.00043463372,0.00008196519,0.0005472772,0.00006752597,0.001123365,0.00024637967],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000096428455,0.000106784864,0.13572553,4.9252253e-7,0.000022824228,0.000010062093,0.0000893052,0.0010922971,0.00018252978,0.013391771,0.0006194592,0.8486625],"study_design_scores_gemma":[0.00067222,0.0003864393,0.010309128,0.00002057261,0.000019988669,0.0005225858,0.0040609217,0.00050734234,0.00012041231,0.9769189,0.0062045874,0.0002569496],"about_ca_topic_score_codex":0.00020157528,"about_ca_topic_score_gemma":0.006124621,"teacher_disagreement_score":0.9635271,"about_ca_system_score_codex":0.00037042712,"about_ca_system_score_gemma":0.001332702,"threshold_uncertainty_score":0.5886668},"labels":[],"label_agreement":null},{"id":"W1564922926","doi":"","title":"Hedonics in Consumer Behavior","year":2007,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Happiness; Outcome (game theory); Subjective well-being; Psychology; Economics; Social psychology; Marketing; Public economics; Business; Microeconomics","score_opus":0.06854347415585278,"score_gpt":0.40010851785424706,"score_spread":0.3315650436983943,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1564922926","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9912759,0.001155066,0.0047221077,0.00025115904,0.00077001326,0.000108134576,0.0000023070656,0.000019608997,0.0016957083],"genre_scores_gemma":[0.99765044,0.00049120706,0.00033712832,0.00013711017,0.00013238336,0.0000023973848,7.693301e-7,0.000019633779,0.0012289354],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99492955,0.000104507366,0.0011915585,0.00039890074,0.00087013526,0.0025053371],"domain_scores_gemma":[0.99816793,0.0006351463,0.00037538665,0.00044013152,0.00020789127,0.00017349124],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.019825285,0.0001797365,0.00033809614,0.0006730511,0.00018689044,0.00028465342,0.000980968,0.00015204852,0.00023493094],"category_scores_gemma":[0.00089922664,0.00013941996,0.00020024611,0.0006924948,0.00008952211,0.00040217693,0.00009407509,0.0020891377,0.00066786376],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005723692,0.00013929876,0.07484697,1.499862e-7,0.000007061654,0.00006578099,0.00008118394,0.000024179657,0.000114303155,0.008427454,0.00020949882,0.9160269],"study_design_scores_gemma":[0.0010376702,0.00024604282,0.02807409,0.000014282076,0.000025999492,0.0015685175,0.0036860192,0.000070612,0.000105107385,0.9408441,0.023999233,0.00032828597],"about_ca_topic_score_codex":0.000065343425,"about_ca_topic_score_gemma":0.006467348,"teacher_disagreement_score":0.9324167,"about_ca_system_score_codex":0.001080709,"about_ca_system_score_gemma":0.0015193392,"threshold_uncertainty_score":0.907638},"labels":[],"label_agreement":null},{"id":"W1573767894","doi":"10.4000/books.pufc.13957","title":"La théorie de la décision et la psychologie du sens commun","year":2015,"lang":"fr","type":"book-chapter","venue":"Presses universitaires de Franche-Comté eBooks","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Francophone University Association","funders":"","keywords":"Nothing; Epistemology; Folk psychology; Argument (complex analysis); Action (physics); Simple (philosophy); Philosophy; Decision theory; Psychology; Sociology; Economics","score_opus":0.08015620350634348,"score_gpt":0.36541425236656927,"score_spread":0.28525804886022577,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1573767894","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09360418,0.0017270038,0.0045650424,0.0021764995,0.001335614,0.00048489854,0.00040914537,0.00031788842,0.8953797],"genre_scores_gemma":[0.95830745,0.0011932884,0.0056709256,0.00058355974,0.0003156736,0.000008862805,0.000045226123,0.00018072668,0.033694282],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9922559,0.0026484767,0.0012233781,0.0015236541,0.0013231038,0.0010254484],"domain_scores_gemma":[0.9796139,0.015578402,0.000951729,0.0023684022,0.0007036648,0.0007839049],"candidate_categories":["metaepi_narrow","scholarly_communication","research_integrity","insufficient_payload"],"consensus_categories":["research_integrity","insufficient_payload"],"category_scores_codex":[0.007526037,0.0011526439,0.0014537319,0.0008554742,0.0007305133,0.0011738852,0.0038384625,0.002417929,0.0015882922],"category_scores_gemma":[0.001634583,0.0011275881,0.0008136452,0.00014870634,0.0026708096,0.0006236989,0.0020871828,0.0026943497,0.0009190006],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00061552157,0.00028246784,0.0039949543,0.000043797336,0.00020571897,0.0027425627,0.0020432067,0.0009587286,0.00015477711,0.13722803,0.031408712,0.8203215],"study_design_scores_gemma":[0.0012386695,0.00018805437,0.0008306787,0.0005074166,0.0002655169,0.0004490052,0.0009689701,0.00038616228,0.000046741086,0.43693018,0.55739653,0.0007920664],"about_ca_topic_score_codex":0.00041356578,"about_ca_topic_score_gemma":0.00014151883,"teacher_disagreement_score":0.8647033,"about_ca_system_score_codex":0.00066372025,"about_ca_system_score_gemma":0.0012400709,"threshold_uncertainty_score":0.99986297},"labels":[],"label_agreement":null},{"id":"W1576290844","doi":"10.1002/bdm.1792","title":"Extreme Outcomes Sway Risky Decisions from Experience","year":2013,"lang":"en","type":"article","venue":"Journal of Behavioral Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":117,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Alberta Gambling Research Institute, University of Calgary; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health","keywords":"Context (archaeology); Outcome (game theory); Psychology; Risk-seeking; Actuarial science; Social psychology; Economics; Microeconomics; Geography","score_opus":0.25457423032658,"score_gpt":0.45132422197669936,"score_spread":0.19674999165011936,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1576290844","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97025037,0.00029585822,0.02414725,0.00026732095,0.0043106,0.00028409637,0.000041989773,0.000046948528,0.00035554805],"genre_scores_gemma":[0.91559833,0.00004366936,0.08342809,0.00035451588,0.00027686235,0.000013621954,0.0000013299865,0.000055407687,0.0002281666],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9887774,0.0003178201,0.004804611,0.000970225,0.0044009364,0.00072901417],"domain_scores_gemma":[0.98193175,0.010111512,0.003158725,0.0018820004,0.0022618806,0.00065411563],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0032354286,0.0005844201,0.0015835525,0.0015202323,0.000501359,0.0022529624,0.0038312997,0.00037120335,0.009733296],"category_scores_gemma":[0.0075475154,0.0003876143,0.001219808,0.0012619777,0.00023944888,0.0032377471,0.00081631547,0.0008833464,0.0028653992],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010003722,0.00033098902,0.14045422,2.0700219e-7,0.000012912146,0.00017615366,0.00076813344,0.00023498767,0.0011728394,0.000023065208,0.0090426495,0.8476838],"study_design_scores_gemma":[0.0017582374,0.0004840493,0.6257657,0.0005285926,0.00014488079,0.0002995914,0.0061937687,0.0011823869,0.00032385445,0.34998837,0.0124085415,0.00092207576],"about_ca_topic_score_codex":0.00025604715,"about_ca_topic_score_gemma":0.000087112414,"teacher_disagreement_score":0.8467617,"about_ca_system_score_codex":0.00027177163,"about_ca_system_score_gemma":0.00019920741,"threshold_uncertainty_score":0.9998576},"labels":[],"label_agreement":null},{"id":"W1576518232","doi":"10.1515/auk-2007-0204","title":"Non-deteriorating Choice Without Full Transitivity","year":2007,"lang":"en","type":"article","venue":"Analyse & Kritik","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Transitive relation; Rationality; Rationalizability; Status quo; Mathematical economics; Rational choice theory (criminology); Ecological rationality; Social choice theory; Element (criminal law); Economics; Positive economics; Epistemology; Mathematics; Psychology; Philosophy; Political science; Law; Combinatorics","score_opus":0.11043492620018362,"score_gpt":0.43356819537507685,"score_spread":0.3231332691748932,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1576518232","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9701783,0.000040851362,0.019953705,0.00020661097,0.000350745,0.000107860295,0.000015561824,0.000060812967,0.009085559],"genre_scores_gemma":[0.9954819,0.000003470413,0.0033102827,0.0004696266,0.0002643822,0.0000032027763,0.0000047989197,0.000020961294,0.0004413947],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99672073,0.00008815416,0.0010614414,0.000750769,0.0008808829,0.00049800414],"domain_scores_gemma":[0.99707395,0.0011915561,0.00031720704,0.0008416774,0.0003138142,0.00026182085],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0053582247,0.00023448319,0.0005554806,0.00044162775,0.00029904908,0.0005391281,0.0007181514,0.00014647827,0.0004507314],"category_scores_gemma":[0.0009528113,0.00019097976,0.00033583265,0.0009858126,0.00012495604,0.00064270257,0.0001001396,0.00027273336,0.0009348146],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006905064,0.00013478991,0.1168565,0.0000023342163,0.000023662542,0.000116558804,0.00053912436,0.00008919248,0.01874651,0.00003180464,0.0010092596,0.8623812],"study_design_scores_gemma":[0.004053123,0.0011878649,0.8080296,0.0002977649,0.00058368355,0.0003479893,0.011030551,0.026438849,0.02167309,0.057114393,0.06589828,0.0033447894],"about_ca_topic_score_codex":0.00041522278,"about_ca_topic_score_gemma":0.0035792582,"teacher_disagreement_score":0.85903645,"about_ca_system_score_codex":0.000069585396,"about_ca_system_score_gemma":0.00007253104,"threshold_uncertainty_score":0.99984306},"labels":[],"label_agreement":null},{"id":"W1577708642","doi":"10.15353/rea.v4i1.1535","title":"Weak* Axiom of Independence and the Non-Expected Utility Theory","year":2012,"lang":"en","type":"article","venue":"Review of Economic Analysis","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Axiom independence; Expected utility hypothesis; Axiom; Von Neumann–Morgenstern utility theorem; Mathematical economics; Zermelo–Fraenkel set theory; Independence (probability theory); Subjective expected utility; Axiom of choice; Constructive set theory; Prospect theory; Urelement; Context (archaeology); Mathematics; Decision theory; Independence of irrelevant alternatives; Function (biology); Economics; Set (abstract data type); Set theory; Computer science; Social choice theory; Statistics; Microeconomics","score_opus":0.07526997619906828,"score_gpt":0.40044637413979967,"score_spread":0.3251763979407314,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1577708642","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9428014,0.047847614,0.002167397,0.000251699,0.00016220096,0.00024549814,0.000042162203,0.0000064297847,0.006475569],"genre_scores_gemma":[0.9872384,0.012181382,0.0002597662,0.00011673775,0.000028704115,0.000006727977,0.0000027976084,0.000004943788,0.00016055847],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9971955,0.00044354977,0.0015549946,0.00034015437,0.00028541952,0.00018041236],"domain_scores_gemma":[0.9949917,0.0023569162,0.0012522157,0.001143433,0.00015782232,0.00009792078],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.014474627,0.00014325467,0.0013403073,0.00027865617,0.000066865556,0.00003827379,0.00077652343,0.00006798214,0.002581547],"category_scores_gemma":[0.0015303737,0.00008133976,0.0007089898,0.0006810528,0.00043790176,0.00031047853,0.00022688977,0.00010901704,0.00013954329],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011918292,0.00013673506,0.2060594,0.00020491787,0.0008722055,3.3861093e-7,0.0005284512,0.00008124466,0.00001238337,0.013453572,0.0011322221,0.77739936],"study_design_scores_gemma":[0.0034969167,0.0001753207,0.63284224,0.0026878344,0.017652605,0.000039319104,0.00594062,0.031123636,0.00059418945,0.26752675,0.036269657,0.0016509205],"about_ca_topic_score_codex":0.00013614628,"about_ca_topic_score_gemma":0.000040760464,"teacher_disagreement_score":0.77574843,"about_ca_system_score_codex":0.00003214725,"about_ca_system_score_gemma":0.00006443999,"threshold_uncertainty_score":0.99833024},"labels":[],"label_agreement":null},{"id":"W1580902776","doi":"10.1371/journal.pone.0161477","title":"Myopic Loss Aversion under Ambiguity and Gender Effects","year":2016,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Ministero dell’Istruzione, dell’Università e della Ricerca; Ministero dello Sviluppo Economico; Generalitat Valenciana; York University","keywords":"Ambiguity; Loss aversion; Ambiguity aversion; Risk aversion (psychology); Psychology; Econometrics; Social psychology; Expected utility hypothesis; Economics; Computer science; Microeconomics; Financial economics","score_opus":0.27385934381546245,"score_gpt":0.3583481884171427,"score_spread":0.08448884460168027,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1580902776","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99634916,0.00006570167,0.0010445545,0.0007619153,0.00017517505,0.00012307464,0.000009009232,0.000043505584,0.0014278932],"genre_scores_gemma":[0.9970426,0.000046038353,0.0009144294,0.00031114244,0.00007066426,0.000004309483,4.9842305e-7,0.000010938608,0.0015993587],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99817747,0.0000973492,0.00031169932,0.00048210513,0.0007071181,0.00022428353],"domain_scores_gemma":[0.9977337,0.0013305161,0.00011995564,0.00053391577,0.00012913975,0.00015278159],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00083050906,0.00012419577,0.00028171367,0.00014273444,0.0001252255,0.0001473605,0.00034624094,0.0000999447,0.00047540438],"category_scores_gemma":[0.0009599588,0.000072753675,0.00005893525,0.00016025279,0.0001209216,0.00030339436,0.00023169245,0.00007843206,0.001839793],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011823563,0.0014949946,0.17436141,0.000033230546,0.00010061801,0.00005583926,0.00029715005,0.0000038019273,0.05269924,0.0018423104,0.0046887374,0.76430446],"study_design_scores_gemma":[0.0021072042,0.00032579142,0.3578251,0.00027244995,0.0001469824,0.0000125879305,0.00011116366,0.0002177833,0.029351482,0.60731184,0.0017566256,0.00056100613],"about_ca_topic_score_codex":0.000007669243,"about_ca_topic_score_gemma":0.0000084443145,"teacher_disagreement_score":0.76374346,"about_ca_system_score_codex":0.00005723761,"about_ca_system_score_gemma":0.00002665358,"threshold_uncertainty_score":0.99893737},"labels":[],"label_agreement":null},{"id":"W1582972446","doi":"10.1111/j.1751-9004.2011.00343.x","title":"Hindsight Bias, Visual Aids, and Legal Decision Making: Timing is Everything","year":2011,"lang":"en","type":"article","venue":"Social and Personality Psychology Compass","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"National Science Foundation","keywords":"Hindsight bias; Processing fluency; Psychology; CLARITY; Cognitive psychology; Context (archaeology); Overconfidence effect; Debiasing; Cognitive bias; Social psychology; Fluency; Cognition","score_opus":0.4071035614528277,"score_gpt":0.4846050736421363,"score_spread":0.07750151218930856,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1582972446","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98896074,0.00021238849,0.0017602011,0.0013198861,0.0010016961,0.00009947445,0.00003546908,0.00004574929,0.006564369],"genre_scores_gemma":[0.99322724,0.000017901535,0.0029415817,0.0032704899,0.00026632712,0.0000043713476,0.0000023429982,0.000015997248,0.0002537209],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.997061,0.00031746435,0.00073053036,0.000929376,0.0005709031,0.0003907096],"domain_scores_gemma":[0.99816346,0.000902417,0.00032851836,0.0002853286,0.00016099862,0.00015926643],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0027362255,0.00026096212,0.0005695408,0.00024197776,0.000787293,0.00035852965,0.0004770741,0.0003131513,0.0012382633],"category_scores_gemma":[0.00031987185,0.00021287365,0.00018245378,0.0003267874,0.00048546967,0.00044001572,0.00025767542,0.00039327843,0.00012954553],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039085626,0.00022127664,0.12601599,0.00000402483,0.000035343306,0.000046812762,0.010168113,1.8929208e-7,0.000055543747,0.0025225452,0.017184757,0.8433545],"study_design_scores_gemma":[0.0011769494,0.0003036426,0.71935076,0.00004965471,0.000056420144,0.00019875013,0.003262049,0.0004595419,0.000017717826,0.20973119,0.06482105,0.0005722928],"about_ca_topic_score_codex":0.00016264778,"about_ca_topic_score_gemma":0.0000833109,"teacher_disagreement_score":0.84278226,"about_ca_system_score_codex":0.000032760967,"about_ca_system_score_gemma":0.00004287451,"threshold_uncertainty_score":0.99967474},"labels":[],"label_agreement":null},{"id":"W1588403970","doi":"10.1002/bdm.1874","title":"A Goal‐Priming Approach to Cognitive Consistency: Applications to Judgment","year":2015,"lang":"en","type":"article","venue":"Journal of Behavioral Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Consistency (knowledge bases); Priming (agriculture); Psychology; Cognition; Cognitive psychology; Preference; Wishful thinking; Task (project management); Process (computing); Social psychology; Computer science; Artificial intelligence; Statistics; Mathematics","score_opus":0.30705424950436955,"score_gpt":0.4760887536961202,"score_spread":0.16903450419175065,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1588403970","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7019922,0.000115734096,0.29380745,0.0002036997,0.0009389473,0.00058264914,0.000030437306,0.000025194226,0.0023036483],"genre_scores_gemma":[0.83172065,0.0000026560072,0.16704693,0.0007503858,0.00025691433,0.0000429174,0.0000011803395,0.000036285786,0.00014205296],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99245226,0.00020658359,0.0028115697,0.00080482534,0.0031950527,0.00052972883],"domain_scores_gemma":[0.9916941,0.0017615019,0.0013409824,0.00084769406,0.0031941885,0.001161513],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.006779051,0.0003697402,0.000997614,0.0017654892,0.0003014193,0.0010021082,0.0017824055,0.00018580671,0.00010630117],"category_scores_gemma":[0.0033215163,0.0002851192,0.00047641236,0.001902658,0.0000897308,0.0007141015,0.0006808002,0.00049117696,0.0009912872],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004653574,0.00063198863,0.0028264525,0.0000012743366,0.000011423469,0.00006465824,0.0016739818,0.0023316005,0.00024876348,0.00014665323,0.010108877,0.98148894],"study_design_scores_gemma":[0.012799449,0.010486857,0.0515356,0.004398453,0.0018354664,0.0059704706,0.1293878,0.0038152554,0.0016839023,0.40666643,0.3656303,0.005790016],"about_ca_topic_score_codex":0.000013775776,"about_ca_topic_score_gemma":0.000018394505,"teacher_disagreement_score":0.97569895,"about_ca_system_score_codex":0.0004668146,"about_ca_system_score_gemma":0.00048344088,"threshold_uncertainty_score":0.9999601},"labels":[],"label_agreement":null},{"id":"W1590853164","doi":"10.7202/1091847ar","title":"Insurance demand under ambiguityand conflict for extreme risks: Evidencefrom a large representative survey","year":2012,"lang":"en","type":"article","venue":"Assurances et gestion des risques","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"AXA Research Fund","keywords":"Ambiguity; Actuarial science; Business; Economics; Computer science","score_opus":0.5916606046342158,"score_gpt":0.5082275678968755,"score_spread":0.08343303673734026,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1590853164","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94666535,0.002492192,0.046634447,0.0007353455,0.00096431817,0.0004782667,0.0006593629,0.00010822669,0.0012625094],"genre_scores_gemma":[0.99411666,0.0006718585,0.0036790061,0.0002941716,0.0001712439,0.00009894131,0.000045029286,0.00003107345,0.00089199754],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9952183,0.0013805584,0.0010641906,0.00079408946,0.0008803799,0.00066250353],"domain_scores_gemma":[0.9871829,0.0102358945,0.00063510623,0.0007411152,0.00094371283,0.0002612644],"candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.01279811,0.00032878912,0.0006506783,0.00026349587,0.00047190386,0.0006730727,0.00071585283,0.00021301035,0.00018705596],"category_scores_gemma":[0.010351125,0.00025378834,0.000235843,0.0006396811,0.00033486838,0.0025943492,0.00013681593,0.00024983726,0.00023963158],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000318367,0.00025269506,0.861667,0.000009377428,0.00004621951,0.0000023821242,0.0014667461,0.001959419,0.00013078903,0.00052336906,0.023840915,0.10978273],"study_design_scores_gemma":[0.0007116657,0.0001232083,0.9445356,0.00010715485,0.000028700122,0.0000119022925,0.0006478598,0.0019345602,0.00056270935,0.038955253,0.012016003,0.00036537426],"about_ca_topic_score_codex":0.0009408369,"about_ca_topic_score_gemma":0.0020824766,"teacher_disagreement_score":0.10941736,"about_ca_system_score_codex":0.000109232475,"about_ca_system_score_gemma":0.00007564054,"threshold_uncertainty_score":0.9999914},"labels":[],"label_agreement":null},{"id":"W1591308282","doi":"10.4000/cpl.4948","title":"Reasoning from or reasoning about beliefs: Truth-based or possibility-based compatibility judgments and Handley et al.’s (2006) litmus test of the suppositional conditional","year":2010,"lang":"en","type":"article","venue":"Current psychology letters","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Wetenschappelijk Onderzoek","keywords":"Compatibility (geochemistry); Litmus; Social psychology; Psychology; Epistemology; Computer science; Philosophy","score_opus":0.10271541425082097,"score_gpt":0.4385167133523023,"score_spread":0.3358012991014813,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1591308282","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9832769,0.000038003625,0.0031420747,0.008066039,0.002955647,0.00029214696,0.0021152333,0.000045559478,0.00006841774],"genre_scores_gemma":[0.98114365,0.0000021310511,0.0061979815,0.012252352,0.000093489434,0.000028609169,0.00025283895,0.000018477916,0.000010476438],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9961312,0.00043442825,0.0011056283,0.0011477483,0.00081020116,0.0003708305],"domain_scores_gemma":[0.9924947,0.0051464313,0.0007098996,0.0012079435,0.00025436716,0.00018665593],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0024015212,0.00030498148,0.0005088328,0.00021375407,0.0003772856,0.00021976182,0.00092446775,0.00015281732,0.00095083215],"category_scores_gemma":[0.0033258717,0.00018942665,0.00020900932,0.00037670662,0.001134307,0.00024691047,0.00012946963,0.00075785053,0.000046642745],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010875077,0.0013234402,0.9061209,0.000012244867,0.000029631616,0.000015737785,0.00017165462,0.0002119685,0.014262784,0.00024662932,0.03968351,0.036833994],"study_design_scores_gemma":[0.0031396567,0.00018310874,0.98325586,0.00022979293,0.00004357881,0.000023953255,0.00006140002,0.003033855,0.0011752275,0.0024909119,0.006025096,0.00033758144],"about_ca_topic_score_codex":0.000050265775,"about_ca_topic_score_gemma":0.00018013804,"teacher_disagreement_score":0.077134944,"about_ca_system_score_codex":0.00006721431,"about_ca_system_score_gemma":0.00028221298,"threshold_uncertainty_score":0.99996245},"labels":[],"label_agreement":null},{"id":"W1592323927","doi":"10.2139/ssrn.1805564","title":"Priors and Desires","year":2011,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Institute for Advanced Research","funders":"","keywords":"Prior probability; Computer science; Artificial intelligence; Bayesian probability","score_opus":0.15808632024470376,"score_gpt":0.36253297975958676,"score_spread":0.204446659514883,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1592323927","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9912972,0.0008790958,0.004164392,0.00014646181,0.00028670853,0.000043265158,8.4839496e-7,0.000017163826,0.0031648509],"genre_scores_gemma":[0.9973557,0.00068806746,0.0007229789,0.00006379904,0.00008396926,8.840434e-7,1.10479064e-7,0.000011038984,0.0010734728],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99760634,0.00009034055,0.00047387517,0.00027227748,0.00040739204,0.001149761],"domain_scores_gemma":[0.9990636,0.00019632283,0.00023534201,0.00026046834,0.00011698878,0.00012724368],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005321688,0.000115604686,0.00019908526,0.00022627202,0.00023327474,0.0002221632,0.0005784567,0.00006698471,0.00021824504],"category_scores_gemma":[0.00054932776,0.00007912374,0.000096255564,0.00019637407,0.00008653038,0.0003805244,0.00008670249,0.00078774954,0.0002444391],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000035467725,0.00003123527,0.015600524,1.4658389e-7,0.000011947471,0.0000069778644,0.00033864536,9.434515e-7,0.00003611704,0.021669345,0.00014693126,0.9621217],"study_design_scores_gemma":[0.00021368168,0.00021542661,0.0077189654,0.000005063452,0.000012316828,0.00070500193,0.0023014662,0.000037032478,0.000062002786,0.9852261,0.0033876095,0.0001153505],"about_ca_topic_score_codex":0.00003872025,"about_ca_topic_score_gemma":0.00033326345,"teacher_disagreement_score":0.96355677,"about_ca_system_score_codex":0.00017534492,"about_ca_system_score_gemma":0.0006916816,"threshold_uncertainty_score":0.34224236},"labels":[],"label_agreement":null},{"id":"W1596875802","doi":"10.1023/a:1026249026940","title":"Newcomb's Hidden Regress","year":2003,"lang":"en","type":"article","venue":"Theory and Decision","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Acadia University","funders":"","keywords":"Overdetermined system; Underdetermined system; Mathematical economics; Set (abstract data type); Computer science; Mathematics; Algorithm; Applied mathematics","score_opus":0.10397390808836886,"score_gpt":0.40386303184065714,"score_spread":0.29988912375228827,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1596875802","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9559432,0.00065084145,0.018444128,0.00005712866,0.00086217053,0.00010203583,0.000006390567,0.000046496152,0.0238876],"genre_scores_gemma":[0.99134225,0.000052189906,0.0062114657,0.00033603256,0.000051250787,0.0000035377498,8.693823e-7,0.000016042446,0.0019863388],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9971905,0.00048459487,0.0006852812,0.00065611716,0.00070880575,0.00027469758],"domain_scores_gemma":[0.99139667,0.007066532,0.00019736018,0.0009692319,0.00015082739,0.0002193645],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0100270705,0.00019204894,0.00036837478,0.00029058606,0.00030576755,0.00046544525,0.0005894152,0.00014063904,0.0016546116],"category_scores_gemma":[0.006568519,0.00012726833,0.00016574045,0.00041644016,0.00016786136,0.00040724565,0.0001689561,0.00017018881,0.0014063796],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019832388,0.000039002185,0.0007473358,3.5979068e-7,0.0000033596045,0.000017742166,0.00013230783,0.00000964344,0.000059457627,0.12768658,0.003423207,0.8676827],"study_design_scores_gemma":[0.00041798374,0.00007254341,0.0013234883,0.000022871838,0.000011569147,0.00006866174,0.00051010423,0.00004537541,0.0002607848,0.9381299,0.05896144,0.00017528722],"about_ca_topic_score_codex":0.000002983109,"about_ca_topic_score_gemma":0.0000054817,"teacher_disagreement_score":0.8675074,"about_ca_system_score_codex":0.000022499366,"about_ca_system_score_gemma":0.000042375847,"threshold_uncertainty_score":0.9993711},"labels":[],"label_agreement":null},{"id":"W1598606007","doi":"10.3389/fpsyg.2015.00916","title":"Prior task experience affects temporal prediction and estimation","year":2015,"lang":"en","type":"article","venue":"Frontiers in Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Task (project management); Estimation; Machine learning; Computer science; Artificial intelligence; Psychology","score_opus":0.10917942323400276,"score_gpt":0.4265777763646589,"score_spread":0.3173983531306561,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1598606007","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87673354,0.00025338694,0.11509015,0.0004181874,0.0058762887,0.00015164996,0.0000071994664,0.000034884502,0.0014346866],"genre_scores_gemma":[0.95255196,0.000015980371,0.04696438,0.00026129672,0.00005196626,0.000020351075,0.0000044660787,0.0000081127055,0.00012147125],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9983395,0.0001512112,0.00043055599,0.0005559131,0.00031867618,0.0002041788],"domain_scores_gemma":[0.99909735,0.00009807002,0.00016995573,0.00043239785,0.00006340616,0.00013880857],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015605163,0.00011303637,0.0002599795,0.00041212968,0.00005651825,0.0001063366,0.0003480291,0.00015578241,0.000022159578],"category_scores_gemma":[0.0009954397,0.00009509232,0.00003111581,0.0003941475,0.00019289306,0.00042306032,0.00006766182,0.00013779062,0.000065595385],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000070861824,0.00003972677,0.23626162,4.075238e-7,0.0000012903021,0.000009826034,0.0009400474,0.000046020905,0.000017866514,0.000015438385,0.08160033,0.68099654],"study_design_scores_gemma":[0.003335838,0.00076025154,0.25162333,0.00004079312,0.000014118459,0.0001644899,0.004679618,0.057014335,0.00005080796,0.56453216,0.117329106,0.00045511124],"about_ca_topic_score_codex":0.000012246738,"about_ca_topic_score_gemma":0.000011708532,"teacher_disagreement_score":0.68054146,"about_ca_system_score_codex":0.000056793026,"about_ca_system_score_gemma":0.000036896727,"threshold_uncertainty_score":0.3877752},"labels":[],"label_agreement":null},{"id":"W1599627703","doi":"10.1017/s1930297500002825","title":"Cognition in the woods: Biases in probability judgments by search and rescue planners","year":2012,"lang":"en","type":"article","venue":"Judgment and Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Saint Mary's University","funders":"","keywords":"Subject (documents); Psychology; Unpacking; Social psychology; Wilderness; Cognitive psychology; Computer science; Linguistics","score_opus":0.2396090586714311,"score_gpt":0.4301681761063678,"score_spread":0.19055911743493673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1599627703","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99736756,0.0006450316,0.00026381452,0.0002638123,0.00023233538,0.0004352974,0.0000234375,0.00001292174,0.00075580936],"genre_scores_gemma":[0.99758494,0.00008094609,0.0017653473,0.00046012818,0.000044894918,0.000028407112,0.0000048610787,0.000009700815,0.000020801112],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9967006,0.00031073735,0.0008657968,0.0005720531,0.0010576666,0.0004931469],"domain_scores_gemma":[0.99503535,0.0042599896,0.00009991912,0.0004299911,0.00005317279,0.00012156122],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009165516,0.00019493527,0.0003274482,0.0004605936,0.00019141419,0.00054264703,0.00040829473,0.00012659482,0.000092852206],"category_scores_gemma":[0.0019427573,0.0001230818,0.000054419008,0.00058241654,0.00012355555,0.000618784,0.00028761287,0.00028125828,0.00005359784],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023462709,0.00030755153,0.18843232,0.0000039365746,0.0000028503532,0.0000100392235,0.0014435948,0.00024670496,0.000088588655,0.00011589829,0.002785618,0.80632824],"study_design_scores_gemma":[0.004127481,0.0004102748,0.6809383,0.001135494,0.000044688273,0.0000965685,0.0161316,0.015115019,0.0002674573,0.2723763,0.008325549,0.0010312471],"about_ca_topic_score_codex":0.000066930435,"about_ca_topic_score_gemma":0.00029784857,"teacher_disagreement_score":0.805297,"about_ca_system_score_codex":0.00008222391,"about_ca_system_score_gemma":0.00002523298,"threshold_uncertainty_score":0.5232758},"labels":[],"label_agreement":null},{"id":"W1600338540","doi":"","title":"The Effect of an Additional Alternative on Measured Risk Preferences in a Field Experiment","year":2005,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University","funders":"","keywords":"Quarter (Canadian coin); Econometrics; Economics; Actuarial science; Geography","score_opus":0.1273206389860561,"score_gpt":0.4487921919657543,"score_spread":0.3214715529796982,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1600338540","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97631997,0.00007794004,0.0000014378762,0.00016211973,0.00058055646,0.0007377538,0.00058514165,0.000011045608,0.021524059],"genre_scores_gemma":[0.9975106,0.0011694261,0.0002591895,0.0000238411,0.00021345944,0.00044597022,0.000042671512,0.000024397716,0.0003104403],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9934037,0.002077456,0.0014838828,0.0012743176,0.001199861,0.0005607994],"domain_scores_gemma":[0.97583926,0.021426886,0.0007251699,0.0016363596,0.00020558845,0.00016672243],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.012985145,0.00033628917,0.000781363,0.00084310997,0.00022148249,0.00045133868,0.002525309,0.0003866274,0.0009397143],"category_scores_gemma":[0.009996345,0.00022636942,0.00027549954,0.00020588719,0.00037272353,0.00018662559,0.0009797273,0.0018619917,0.000058749254],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007457879,0.0001553173,0.003654768,0.0000036782085,0.00002542199,0.000009391151,0.00036775513,0.02361108,0.000008437808,0.000038931386,0.00026011487,0.97111934],"study_design_scores_gemma":[0.009806123,0.01793538,0.10626436,0.0034681053,0.00006911107,0.000032684828,0.010775217,0.20564465,0.027016534,0.5109198,0.10412511,0.003942897],"about_ca_topic_score_codex":0.00033052496,"about_ca_topic_score_gemma":0.0032463763,"teacher_disagreement_score":0.96717644,"about_ca_system_score_codex":0.00074127025,"about_ca_system_score_gemma":0.00042727945,"threshold_uncertainty_score":0.99997354},"labels":[],"label_agreement":null},{"id":"W1608426784","doi":"","title":"Social Aggregation Without the Expected Utility Hypothesis","year":2004,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Expected utility hypothesis; Subjective expected utility; Impossibility; Mathematical economics; Von Neumann–Morgenstern utility theorem; Utility theory; Arrow's impossibility theorem; Social preferences; Social choice theory; Value (mathematics); Pareto principle; Expected value; Bernoulli's principle; Economics; Prospect theory; Observer (physics); Econometrics; Mathematics; Microeconomics; Statistics","score_opus":0.10159677749987656,"score_gpt":0.3345527780842371,"score_spread":0.23295600058436056,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1608426784","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8937284,0.00033410816,0.053320333,0.019110411,0.00059453223,0.0006446114,0.0001098612,0.00027519828,0.03188255],"genre_scores_gemma":[0.9839923,0.00007122476,0.011157961,0.00015500622,0.000074978554,0.00007554376,0.00008272827,0.000047701764,0.0043425965],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.987769,0.007445228,0.0013816694,0.0014327487,0.0015264391,0.0004448972],"domain_scores_gemma":[0.9844888,0.006118309,0.0015660927,0.0038890126,0.0037550586,0.00018275174],"candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.01776635,0.0004564215,0.0006856108,0.00032476927,0.0011596843,0.0020447571,0.0039177337,0.0005096139,0.0006047301],"category_scores_gemma":[0.012737872,0.00034621469,0.00057376863,0.00079917005,0.0006527644,0.00026478164,0.0020927053,0.00096673967,0.00038865153],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003655845,0.00055582175,0.0046771844,0.000016835582,0.000052401745,0.0000045975576,0.01481115,0.000119480814,0.00014888837,0.012851781,0.003766846,0.96295846],"study_design_scores_gemma":[0.00097075413,7.826668e-7,0.051417127,0.0009706611,0.00013788776,0.000019986308,0.0013314865,0.008730763,0.009302749,0.8954582,0.030605743,0.0010538624],"about_ca_topic_score_codex":0.0009986091,"about_ca_topic_score_gemma":0.0021843386,"teacher_disagreement_score":0.9619046,"about_ca_system_score_codex":0.00028903165,"about_ca_system_score_gemma":0.0006871682,"threshold_uncertainty_score":0.99989897},"labels":[],"label_agreement":null},{"id":"W161674510","doi":"10.1017/cbo9780511816789.025","title":"Motivation, decision making, and consciousness: from psychodynamics to subliminal priming and emotional constraint satisfaction","year":2007,"lang":"en","type":"book-chapter","venue":"Cambridge University Press eBooks","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Subliminal stimuli; Psychodynamics; Psychology; Consciousness; Priming (agriculture); Social psychology; Cognitive psychology; Psychotherapist","score_opus":0.0987491629230933,"score_gpt":0.3198567486593416,"score_spread":0.2211075857362483,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W161674510","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6034366,0.00007571174,0.059833474,0.000049714778,0.00089082,0.0005462752,0.0009240655,0.00008728511,0.33415607],"genre_scores_gemma":[0.67219764,0.00014284308,0.02362893,0.0005365434,0.00037375864,0.0000014820644,0.00009788667,0.00011378197,0.30290714],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9968428,0.00005595969,0.000705581,0.001228217,0.0008768019,0.0002906279],"domain_scores_gemma":[0.99579513,0.0020871814,0.0005971972,0.0006301882,0.0005648596,0.0003254709],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00086616393,0.0004370912,0.00060543255,0.000884174,0.00042930208,0.00047703486,0.00047703486,0.0005168039,0.00003993067],"category_scores_gemma":[0.00041990363,0.00046190066,0.00014311493,0.00003883698,0.00048181656,0.00028206728,0.0005561865,0.00045999695,0.000025078087],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037544154,0.000013522312,0.0018132677,0.000008156926,0.00004857064,0.0001237221,0.00016146281,0.00002965058,0.00003087034,0.17381455,0.005296577,0.8182842],"study_design_scores_gemma":[0.0042305244,0.00057526765,0.15229253,0.003539645,0.0007582713,0.0005334614,0.0022084927,0.0040429756,0.000057374527,0.028170014,0.79987496,0.0037165014],"about_ca_topic_score_codex":0.00016015476,"about_ca_topic_score_gemma":0.00012431738,"teacher_disagreement_score":0.8145677,"about_ca_system_score_codex":0.00030901984,"about_ca_system_score_gemma":0.00013159179,"threshold_uncertainty_score":0.9997833},"labels":[],"label_agreement":null},{"id":"W1623916541","doi":"10.5860/llm.v28i2.7055","title":"Risk-taking in Academic Libraries: The Implications of Prospect Theory","year":2014,"lang":"en","type":"article","venue":"Library Leadership & Management","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Cognitive reframing; Pace; Prospect theory; Perspective (graphical); Context (archaeology); Dynamics (music); Value (mathematics); Academic community; Engineering ethics; Public relations; Management science; Business; Political science; Sociology; Computer science; Economics; Engineering; Psychology; Social science; Finance","score_opus":0.2280112674352634,"score_gpt":0.3726053140095901,"score_spread":0.14459404657432673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1623916541","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8301612,0.000735818,0.008551043,0.022719098,0.0005713745,0.0011538821,0.000029120374,0.00023061737,0.13584785],"genre_scores_gemma":[0.9925126,0.000050683102,0.0025279287,0.0016829581,0.00009462011,0.00005270776,0.0000047167596,0.000026465228,0.0030473392],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9970122,0.00057466386,0.0009668127,0.0005830988,0.00049559696,0.00036760356],"domain_scores_gemma":[0.99494475,0.0025993953,0.0010839673,0.0012781438,0.00001918666,0.00007457024],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003342839,0.00018815827,0.00031354954,0.00045775293,0.00017107677,0.00034496305,0.0023948818,0.00010941018,0.00060720666],"category_scores_gemma":[0.0008889255,0.00012137698,0.00015347434,0.0011839072,0.00027900678,0.0013402059,0.00055308983,0.0004473469,0.00026566023],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040912306,0.000047695725,0.12553625,0.000010786411,0.000013565475,0.000001493751,0.0010173948,0.00030431862,0.0000053157773,0.3548589,0.0048937295,0.51326966],"study_design_scores_gemma":[0.00019287562,0.00002514305,0.27236512,0.000048779715,0.000018705181,0.0000010243328,0.0043401583,0.0003187547,0.00007980531,0.7069187,0.015566689,0.00012421142],"about_ca_topic_score_codex":0.000005332063,"about_ca_topic_score_gemma":0.000005143636,"teacher_disagreement_score":0.51314545,"about_ca_system_score_codex":0.000019268087,"about_ca_system_score_gemma":0.000028921479,"threshold_uncertainty_score":0.66484874},"labels":[],"label_agreement":null},{"id":"W1655156919","doi":"10.3917/ecop.182.0001","title":"L'économie expérimentale comme outil d'aide à la décision","year":2008,"lang":"fr","type":"article","venue":"Économie & prévision","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Center for Interuniversity Research and Analysis on Organizations","funders":"","keywords":"Humanities; Philosophy","score_opus":0.2638391690564877,"score_gpt":0.38966216462164754,"score_spread":0.12582299556515986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1655156919","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93140674,0.0051151044,0.0021463379,0.008104475,0.008906909,0.00073200354,0.0002061576,0.00020518251,0.04317709],"genre_scores_gemma":[0.8705879,0.0023129114,0.019149955,0.0026801336,0.0010581663,0.000044015793,0.000059665894,0.00017386621,0.10393342],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99137026,0.0008031426,0.003108273,0.0024384833,0.00089219457,0.0013876684],"domain_scores_gemma":[0.9893575,0.005481219,0.00107449,0.0027555465,0.00032962332,0.0010016627],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0041091177,0.0010394248,0.0016810246,0.00084713276,0.0013143246,0.0010790286,0.0025754797,0.0010403077,0.006347845],"category_scores_gemma":[0.0013947962,0.0010046122,0.0010364669,0.00072117295,0.0013507432,0.0025244355,0.0015836422,0.0010418453,0.026603451],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002874762,0.0008519353,0.0061604655,0.00001198209,0.000040373736,0.00033855392,0.0007225539,0.00085584825,0.00035761745,0.001393295,0.10902849,0.8799514],"study_design_scores_gemma":[0.0027973119,0.0006535452,0.0044073323,0.0004244119,0.00009630633,0.00080061756,0.0008442817,0.011090784,0.002232786,0.052969605,0.92232406,0.0013589554],"about_ca_topic_score_codex":0.0014443129,"about_ca_topic_score_gemma":0.00020616225,"teacher_disagreement_score":0.87859243,"about_ca_system_score_codex":0.0014994614,"about_ca_system_score_gemma":0.001177084,"threshold_uncertainty_score":0.9999858},"labels":[],"label_agreement":null},{"id":"W1656179029","doi":"10.1016/j.jeca.2012.01.003","title":"Ramsey meets Laibson and Itô: Effects of hyperbolic discounting on stochastic growth","year":2012,"lang":"en","type":"article","venue":"The Journal of Economic Asymmetries","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Discounting; Economics; Hyperbolic discounting; Logarithm; Mathematical economics; Econometrics; Growth model; Consumption (sociology); Mathematics","score_opus":0.058123423392874046,"score_gpt":0.35527617611946016,"score_spread":0.29715275272658614,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1656179029","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9956381,0.0013396922,0.0004865211,0.00047414983,0.001323829,0.00009628091,0.0000069477014,0.0000046666937,0.00062982517],"genre_scores_gemma":[0.99919045,0.0001003266,0.00020350584,0.00009923683,0.00032753177,7.219613e-7,1.8181176e-7,0.000015117749,0.00006294621],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99802613,0.00018496715,0.0010390496,0.00014133846,0.0003390716,0.00026945688],"domain_scores_gemma":[0.99025893,0.007800936,0.0013801957,0.00031926448,0.00009823032,0.00014245928],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0054188007,0.0001691494,0.00059344666,0.00050066976,0.00015127032,0.0001481648,0.00065806974,0.000069235444,0.00003327955],"category_scores_gemma":[0.003407766,0.00009658497,0.00015221495,0.0002062959,0.00023129814,0.0007352057,0.00015450902,0.00022739034,0.000074417985],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016344428,0.00066918915,0.09216842,0.00006312576,0.00038717588,0.000012651058,0.00935102,0.0040187817,0.0020221088,0.025540968,0.009269092,0.85486305],"study_design_scores_gemma":[0.01038811,0.0064843474,0.44604728,0.0017575135,0.0017610561,0.0018946374,0.020590467,0.0041600345,0.054594636,0.4327887,0.016922833,0.0026103891],"about_ca_topic_score_codex":0.000029077817,"about_ca_topic_score_gemma":0.000012222081,"teacher_disagreement_score":0.85225266,"about_ca_system_score_codex":0.0000784774,"about_ca_system_score_gemma":0.000056881636,"threshold_uncertainty_score":0.40796608},"labels":[],"label_agreement":null},{"id":"W1656873868","doi":"10.1037/e667842007-001","title":"Could Behavioral Economics Help Improve Diet Quality for Nutrition Assistance Program Participants?","year":2007,"lang":"en","type":"dataset","venue":"PsycEXTRA Dataset","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":80,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Food and Nutrition Service; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; University of Alberta; Economic Research Service; Washington State University; U.S. Department of Agriculture","keywords":"Quality (philosophy); Behavioral economics; Supplemental Nutrition Assistance Program; Behavioural economics; Psychology; Gerontology; Public economics; Medicine; Economics; Food insecurity; Microeconomics; Biology; Food security; Ecology","score_opus":0.3674282890381557,"score_gpt":0.5439569691639515,"score_spread":0.1765286801257958,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1656873868","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009858391,0.00017699983,0.0002851295,0.00023497353,0.0038437266,0.0026581376,0.98282695,0.000097846656,0.000017830032],"genre_scores_gemma":[0.0003585264,0.0002600816,0.0044880165,0.0005107458,0.00093602174,0.0011300149,0.9921636,0.00006419789,0.00008878347],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9907454,0.0002641458,0.003666347,0.0026554859,0.001180822,0.0014877496],"domain_scores_gemma":[0.98983455,0.002123216,0.002331242,0.0045735803,0.00047085606,0.0006665828],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.008452921,0.0009307653,0.0017337563,0.0005977252,0.00046711997,0.0018886789,0.003522166,0.0011365484,0.0009690105],"category_scores_gemma":[0.0015184765,0.0008431762,0.0006445056,0.00050981523,0.00043992256,0.0009558532,0.0005015674,0.0009184869,0.0013839513],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009737664,0.0024001517,0.000039386185,0.00006630723,0.00003172526,0.000018962934,0.0000075100265,0.0000037813109,0.0000113558535,0.000019158728,0.82906425,0.16736363],"study_design_scores_gemma":[0.0014228977,0.0011368133,0.00012689516,0.000084293635,0.00028319663,0.000009270507,0.00017101549,0.00009028231,0.000035987778,0.0066665905,0.98889345,0.0010792831],"about_ca_topic_score_codex":0.00048409816,"about_ca_topic_score_gemma":0.0049992152,"teacher_disagreement_score":0.16628435,"about_ca_system_score_codex":0.00038639206,"about_ca_system_score_gemma":0.00030956202,"threshold_uncertainty_score":0.9999442},"labels":[],"label_agreement":null},{"id":"W1694187867","doi":"","title":"Dealing with Entrepreneurial Uncerstainity: Do Current Measures of Overconfidence Tell the Whole Story?","year":2007,"lang":"en","type":"article","venue":"ASAC","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Laurentian University","funders":"","keywords":"Overconfidence effect; Cognitive bias; Psychology; Entrepreneurship; Strengths and weaknesses; Cognition; Calibration; Social psychology; Econometrics; Economics; Statistics; Mathematics","score_opus":0.18752720604733228,"score_gpt":0.40334083806233884,"score_spread":0.21581363201500656,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1694187867","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99063885,0.0005142084,0.0057524233,0.0002745971,0.00084314944,0.0001441547,0.000014081353,0.000020815332,0.0017977456],"genre_scores_gemma":[0.9993572,0.000026249274,0.00027709067,0.000064356806,0.00013676964,0.0000016915404,6.693162e-7,0.000009346673,0.0001266279],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9975559,0.00011380308,0.0005417314,0.0004105335,0.0011238523,0.00025417216],"domain_scores_gemma":[0.99625105,0.0021693686,0.00038610742,0.00076464517,0.00033137886,0.000097456876],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005187721,0.00013783711,0.00025771267,0.00014670135,0.00019257008,0.00018807132,0.000812273,0.000052467043,0.00016586712],"category_scores_gemma":[0.0012238465,0.00007660374,0.0001128721,0.0003282361,0.00023299168,0.0002105064,0.00011924266,0.0002383883,0.00015285556],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017540433,0.000057266203,0.024690622,0.0000014482633,0.000008942795,0.000010196148,0.00085921434,0.00066927256,0.0004912622,0.0009090515,0.0016055048,0.9705218],"study_design_scores_gemma":[0.0017534733,0.0006243909,0.04777086,0.00028481008,0.00013875801,0.00004680418,0.009331227,0.00041644226,0.012027532,0.1106669,0.816119,0.00081981096],"about_ca_topic_score_codex":0.00007955871,"about_ca_topic_score_gemma":0.0002156934,"teacher_disagreement_score":0.969702,"about_ca_system_score_codex":0.00005087326,"about_ca_system_score_gemma":0.00012814935,"threshold_uncertainty_score":0.312381},"labels":[],"label_agreement":null},{"id":"W1734675635","doi":"","title":"Thoughts on quantifying overconfidence in economic experiments","year":2013,"lang":"en","type":"article","venue":"Munich Personal RePEc Archive (Ludwig Maximilian University of Munich)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Deutscher Akademischer Austauschdienst","keywords":"Overconfidence effect; Test (biology); Sample (material); Measure (data warehouse); Actuarial science; Psychology; Econometrics; Computer science; Economics; Social psychology; Data mining","score_opus":0.1581254074852033,"score_gpt":0.35715686949781217,"score_spread":0.19903146201260888,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1734675635","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97762996,0.000083731495,0.00017013459,0.00045907998,0.00033540995,0.00034467274,0.00008963775,0.00003861711,0.020848747],"genre_scores_gemma":[0.99264383,0.00015928954,0.003637305,0.00013009661,0.00005643907,0.0000016584551,0.000013458739,0.000024945168,0.0033329967],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9964728,0.00043581548,0.00074055244,0.001026912,0.00079045095,0.0005335222],"domain_scores_gemma":[0.9960821,0.0016311511,0.0004931482,0.001367242,0.00014274854,0.00028356115],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0011688063,0.000340353,0.00068861863,0.0007953707,0.00036613218,0.0001494274,0.0024367792,0.00015793799,0.0020847544],"category_scores_gemma":[0.00041510697,0.00034773382,0.00037842535,0.00032068676,0.00054131955,0.00084280886,0.0008280582,0.0004869563,0.0019521294],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019238833,0.0021162692,0.09310261,0.000048437836,0.00021277057,0.00061204477,0.06431865,0.0040838905,0.012380911,0.007393934,0.031146536,0.78266007],"study_design_scores_gemma":[0.009160447,0.001994086,0.40718168,0.0014960993,0.00011495085,0.00013059111,0.17899242,0.10960314,0.002664719,0.14527746,0.13977061,0.003613807],"about_ca_topic_score_codex":0.005431766,"about_ca_topic_score_gemma":0.0041033938,"teacher_disagreement_score":0.77904624,"about_ca_system_score_codex":0.00033519723,"about_ca_system_score_gemma":0.00021343752,"threshold_uncertainty_score":0.9998975},"labels":[],"label_agreement":null},{"id":"W1751271164","doi":"10.1177/076737011202700105","title":"Les routes multiples d'auto-expression <i>versus</i> d'inter-expression dans le choix du consommateur","year":2012,"lang":"fr","type":"article","venue":"Recherche et Applications en Marketing (French Edition)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Humanities; Philosophy; Mathematics","score_opus":0.21211662293894892,"score_gpt":0.42002670305211337,"score_spread":0.20791008011316445,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1751271164","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.30053708,0.004378202,0.61087906,0.01365961,0.008725039,0.0020708593,0.0009559168,0.0007482212,0.05804603],"genre_scores_gemma":[0.761754,0.0015622847,0.21583879,0.0003358791,0.004169495,0.0011470639,0.0005003363,0.00016800252,0.014524169],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9889568,0.005786524,0.0018284873,0.001342884,0.0010166601,0.0010686404],"domain_scores_gemma":[0.958693,0.03709721,0.0011557024,0.0017161791,0.0006951043,0.00064276904],"candidate_categories":["metaresearch","metaepi_narrow","sts","research_integrity","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.023828462,0.0007226514,0.00074825017,0.00044369473,0.0013612054,0.00084806397,0.001807542,0.0016903805,0.0022387423],"category_scores_gemma":[0.014872566,0.0006835385,0.00047788877,0.0011375571,0.00062242406,0.002228221,0.00087484095,0.002280176,0.0018639389],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020011597,0.0020738018,0.012348027,0.00010728199,0.000047496123,0.000004753761,0.0031456698,0.00035304468,0.04964508,0.0023299465,0.0997493,0.8299955],"study_design_scores_gemma":[0.0019620857,0.0000975801,0.013604423,0.0011729271,0.00017952106,0.00008206265,0.005394293,0.003330122,0.0288082,0.011612398,0.932383,0.0013733992],"about_ca_topic_score_codex":0.00087160635,"about_ca_topic_score_gemma":0.00016826933,"teacher_disagreement_score":0.8326337,"about_ca_system_score_codex":0.00086523127,"about_ca_system_score_gemma":0.0004914124,"threshold_uncertainty_score":0.9999389},"labels":[],"label_agreement":null},{"id":"W1776244204","doi":"10.1002/bdm.1795","title":"Altering the Shape of Punishment Distributions Affects Decision Making in a Modified Iowa Gambling Task","year":2013,"lang":"en","type":"article","venue":"Journal of Behavioral Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Trent University; McMaster University; Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Punishment (psychology); Skew; Iowa gambling task; Variance (accounting); Psychology; Preference; Task (project management); Affect (linguistics); Social psychology; Analysis of variance; Perception; Econometrics; Cognitive psychology; Statistics; Cognition; Economics; Computer science; Mathematics; Communication; Neuroscience","score_opus":0.13856622509164848,"score_gpt":0.4314551819299026,"score_spread":0.2928889568382541,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1776244204","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93666494,0.0003295831,0.060391292,0.00020096429,0.0017352888,0.0005024217,0.000027516719,0.000019903375,0.00012811847],"genre_scores_gemma":[0.9741769,0.00004325308,0.025443602,0.000092534465,0.00016548856,0.00001844351,0.0000012515457,0.00004377201,0.000014788449],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9908539,0.00040259122,0.00414315,0.0007166232,0.00314511,0.0007385973],"domain_scores_gemma":[0.9872999,0.0067017656,0.003203011,0.0012546376,0.0012942926,0.00024634931],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.007827435,0.0004794934,0.0012780332,0.0017156039,0.00037338416,0.0012766406,0.0027067354,0.0002905858,0.00071008655],"category_scores_gemma":[0.0034582398,0.00030836658,0.0008197068,0.0020194233,0.00021242295,0.001739704,0.00091209676,0.0010041383,0.00011303616],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028828578,0.00037833006,0.013763425,0.0000040215423,0.000011321283,0.00013317629,0.00056689896,0.009188701,0.003124032,0.00011582001,0.0012882805,0.9711377],"study_design_scores_gemma":[0.005112563,0.001894005,0.46768278,0.008726379,0.00036967522,0.0014500532,0.0076524876,0.102394216,0.0012569783,0.3990611,0.002633805,0.0017659484],"about_ca_topic_score_codex":0.000045865985,"about_ca_topic_score_gemma":0.00008981985,"teacher_disagreement_score":0.96937174,"about_ca_system_score_codex":0.00046358764,"about_ca_system_score_gemma":0.00021579115,"threshold_uncertainty_score":0.9999368},"labels":[],"label_agreement":null},{"id":"W1786148330","doi":"","title":"Group and individual risk preferences: a lottery-choice experiment","year":2006,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Center for Interuniversity Research and Analysis on Organizations","funders":"","keywords":"Lottery; Preference; Risk aversion (psychology); Voting; Order (exchange); Psychology; Social psychology; Actuarial science; Group decision-making; Group (periodic table); Economics; Microeconomics; Expected utility hypothesis; Financial economics; Political science","score_opus":0.19000050829632203,"score_gpt":0.4283557189651707,"score_spread":0.23835521066884868,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1786148330","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9763793,0.00039507434,0.000017389486,0.00013279382,0.00090297166,0.0007940001,0.00039137446,0.000051631927,0.020935478],"genre_scores_gemma":[0.9935022,0.0024627326,0.0023386676,0.000080570084,0.00036195965,0.00027656587,0.00007391019,0.00007029768,0.0008331146],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9918376,0.0010118351,0.0020967168,0.00264397,0.0013314283,0.001078455],"domain_scores_gemma":[0.99071646,0.005502218,0.0008762487,0.0022963686,0.00021189694,0.00039683198],"candidate_categories":["metaepi_narrow","scholarly_communication","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.010455102,0.0005855585,0.0011584061,0.0015195636,0.0003847962,0.0022580249,0.0028084123,0.0008190374,0.0002837781],"category_scores_gemma":[0.0028710987,0.0005231921,0.00030226214,0.00031162787,0.0007146421,0.0003594349,0.004774317,0.0025668086,0.00008397946],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000061802384,0.00023927794,0.091706455,0.000012061565,0.00003706273,0.000022045133,0.0004449776,0.0015535521,0.000012840688,0.00005127799,0.0006847923,0.90517384],"study_design_scores_gemma":[0.0034313945,0.00091918465,0.38364765,0.0007457879,0.00009436492,0.000053175696,0.004607968,0.013886062,0.000172616,0.43383792,0.15550199,0.0031018872],"about_ca_topic_score_codex":0.0014227371,"about_ca_topic_score_gemma":0.003283164,"teacher_disagreement_score":0.90207195,"about_ca_system_score_codex":0.0007074826,"about_ca_system_score_gemma":0.00046483107,"threshold_uncertainty_score":0.9997343},"labels":[],"label_agreement":null},{"id":"W1806059501","doi":"10.1002/bdm.1863","title":"When Does Framing Influence Preferences, Risk Perceptions, and Risk Attitudes? The Explicated Valence Account","year":2015,"lang":"en","type":"article","venue":"Journal of Behavioral Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":42,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"York University; Defence Research and Development Canada","funders":"York University; Government of Canada; Defence Research and Development Canada","keywords":"Framing effect; Framing (construction); Prospect theory; Risk perception; Perception; Risk-seeking; Psychology; Valence (chemistry); Social psychology; Economics; Loss aversion; Positive economics; Microeconomics; Engineering; Chemistry","score_opus":0.1262111218641538,"score_gpt":0.4200131924037594,"score_spread":0.2938020705396056,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1806059501","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9875091,0.0007047849,0.010142555,0.000114402945,0.0011582156,0.00023303322,0.00006821042,0.000032121687,0.00003761252],"genre_scores_gemma":[0.97299016,0.00071832293,0.025914771,0.00008950238,0.00020169938,0.000007955903,6.7110716e-7,0.000028233171,0.0000486826],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9928395,0.0006558561,0.0024806967,0.0007230158,0.0028496666,0.00045123068],"domain_scores_gemma":[0.9894738,0.0036382845,0.003297805,0.0011602144,0.002025019,0.00040485017],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.011411691,0.00038669474,0.00076612935,0.0006660608,0.000716005,0.0019437281,0.0024077098,0.0002567957,0.000284278],"category_scores_gemma":[0.00653951,0.0001982554,0.00032524284,0.00070191355,0.00036679715,0.002187063,0.0007273781,0.0012417207,0.00016329112],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013355029,0.00010328884,0.42923877,8.982191e-7,0.00000922106,0.000025419116,0.0013664116,0.0013327372,0.000058401627,0.000007275555,0.0015285397,0.5661955],"study_design_scores_gemma":[0.0010260409,0.0005800709,0.7838513,0.00052481267,0.00033518937,0.00043735086,0.008365598,0.0017093526,0.000032893935,0.19576299,0.0068394677,0.0005348985],"about_ca_topic_score_codex":0.00022783471,"about_ca_topic_score_gemma":0.0002883,"teacher_disagreement_score":0.5656606,"about_ca_system_score_codex":0.0002243068,"about_ca_system_score_gemma":0.00026760288,"threshold_uncertainty_score":0.99909234},"labels":[],"label_agreement":null},{"id":"W1810802980","doi":"10.1007/s11166-015-9216-5","title":"Probabilistic sophistication and reverse Bayesianism","year":2015,"lang":"en","type":"article","venue":"Journal of Risk and Uncertainty","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":31,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Axiom; Sophistication; Mathematical economics; Probabilistic logic; Subjective expected utility; Expected utility hypothesis; Representation (politics); Decision theory; Computer science; Mathematics; Economics; Microeconomics; Artificial intelligence; Sociology; Political science","score_opus":0.11563006113090726,"score_gpt":0.37266609677122825,"score_spread":0.25703603564032096,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1810802980","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.995111,0.00038060662,0.0031018301,0.0005396907,0.00039284682,0.000048772297,0.000010452279,0.0000043083637,0.00041050668],"genre_scores_gemma":[0.9962703,0.00017139899,0.0032657634,0.00007149257,0.0001266252,4.3183354e-7,3.3617872e-7,0.000004236849,0.000089422836],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99855864,0.00012685315,0.00060590444,0.00017117066,0.00043703336,0.00010037355],"domain_scores_gemma":[0.9976128,0.00082163024,0.0006014557,0.00018488514,0.0005271632,0.00025209202],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035963305,0.00008381355,0.00026311065,0.0001556319,0.00008861188,0.0001892921,0.00019351355,0.00005805094,0.000028670243],"category_scores_gemma":[0.0067162956,0.000052788462,0.000055161927,0.00013487105,0.00011932176,0.00024509057,0.00005247675,0.00016589688,0.000017230677],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020323794,0.00006588555,0.015719391,0.000002145593,0.000008152884,0.000029768235,0.0011376555,0.0009788512,0.00001960548,0.0019734225,0.010641467,0.9692204],"study_design_scores_gemma":[0.0008330443,0.000304236,0.01632658,0.000030258923,0.00006866053,0.00026831232,0.0016078898,0.00508867,0.000005250458,0.9319203,0.043420497,0.0001262917],"about_ca_topic_score_codex":0.000043041196,"about_ca_topic_score_gemma":0.000021187818,"teacher_disagreement_score":0.9690941,"about_ca_system_score_codex":0.00005008597,"about_ca_system_score_gemma":0.000117742,"threshold_uncertainty_score":0.8040518},"labels":[],"label_agreement":null},{"id":"W1813082302","doi":"10.1002/bdm.1844","title":"‘Put Your Money Where Your Mouth Is!’: Effects of Streaks on Confidence and Betting in a Binary Choice Task","year":2014,"lang":"en","type":"article","venue":"Journal of Behavioral Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Medical Research Council","keywords":"Roulette; Stochastic game; Psychology; Outcome (game theory); Task (project management); Randomness; Social psychology; Confidence interval; Econometrics; Cognitive psychology; Statistics; Economics; Mathematical economics; Mathematics","score_opus":0.08297874841532561,"score_gpt":0.41757058493766,"score_spread":0.33459183652233443,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1813082302","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99627876,0.0005592459,0.0015638472,0.00014115777,0.0010793254,0.00023020459,0.000016997406,0.000014987258,0.00011547321],"genre_scores_gemma":[0.9923109,0.00005450408,0.0071120244,0.00023376799,0.00017541362,0.0000030378415,4.0365597e-7,0.000040735318,0.00006924204],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9931698,0.00039696688,0.0029075593,0.000751144,0.0022736161,0.0005009248],"domain_scores_gemma":[0.98946464,0.005930544,0.0027441354,0.00083647453,0.000719838,0.00030436626],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0049707238,0.00043106845,0.0013117618,0.0015890542,0.0001918354,0.00051265367,0.0013329589,0.00031810143,0.00008424497],"category_scores_gemma":[0.0039125644,0.0003267685,0.0004085284,0.0008825633,0.00015743161,0.00096694235,0.00041410592,0.00086942565,0.000044960285],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003694426,0.00038512304,0.08189202,0.00001574129,0.000008502304,0.00022769129,0.0010138737,0.0011097903,0.00577442,0.000037255595,0.00084980467,0.9083163],"study_design_scores_gemma":[0.00836168,0.0059148585,0.880949,0.012669063,0.00040968638,0.0005045571,0.0050604544,0.014132379,0.0035620215,0.06267384,0.004076315,0.0016861197],"about_ca_topic_score_codex":0.00009735472,"about_ca_topic_score_gemma":0.00006589137,"teacher_disagreement_score":0.9066302,"about_ca_system_score_codex":0.00014508519,"about_ca_system_score_gemma":0.00012725298,"threshold_uncertainty_score":0.99991846},"labels":[],"label_agreement":null},{"id":"W1822084430","doi":"10.1287/moor.2014.0709","title":"Analogy in Decision Making","year":2015,"lang":"en","type":"article","venue":"Mathematics of Operations Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Analogy; Generality; Mathematics; Preference; Mathematical economics; Operator (biology); Artificial intelligence; Computer science; Epistemology","score_opus":0.6559170799496467,"score_gpt":0.6101930257580186,"score_spread":0.04572405419162806,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1822084430","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97431123,0.00005153002,0.0150545705,0.0002688072,0.00013155435,0.00022315989,0.000008515349,0.000008850296,0.009941805],"genre_scores_gemma":[0.9201548,0.0000048900483,0.07939351,0.000013232361,0.000024200133,0.000016281305,0.0000012809458,0.000010378147,0.00038140017],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9961592,0.0002593701,0.0011124774,0.00033008514,0.0018545571,0.00028429253],"domain_scores_gemma":[0.9944325,0.0030444125,0.0000666924,0.0008847576,0.0014583769,0.00011327739],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.015026576,0.0000894366,0.00033738857,0.0014373234,0.00012196427,0.00036855187,0.0010457813,0.00009380637,0.000352267],"category_scores_gemma":[0.019995224,0.00006699241,0.00006329988,0.001705843,0.00017209003,0.00033843692,0.00039263137,0.00026584862,0.0008430058],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001024168,0.0016035441,0.008617802,0.000016903929,0.0000121916155,0.000065217326,0.01123533,0.09484501,0.0010080297,0.06497646,0.016903417,0.80061364],"study_design_scores_gemma":[0.00046866262,0.00016532106,0.0011131426,0.00014222751,0.0000027005806,0.000020184478,0.0066547883,0.20776927,0.0002508989,0.78163886,0.0016357016,0.00013825385],"about_ca_topic_score_codex":0.000064852415,"about_ca_topic_score_gemma":0.00093155395,"teacher_disagreement_score":0.8004754,"about_ca_system_score_codex":0.0001198092,"about_ca_system_score_gemma":0.000314564,"threshold_uncertainty_score":0.999935},"labels":[],"label_agreement":null},{"id":"W1851457994","doi":"10.1002/hipo.22318","title":"An Allais paradox without mental time travel","year":2014,"lang":"en","type":"article","venue":"Hippocampus","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; York University","funders":"National Institute of Mental Health; Canadian Institutes of Health Research; Université de Genève; National Science Foundation; National Institutes of Health; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Agence Nationale de la Recherche","keywords":"Regret; Certainty; Psychology; Chronesthesia; Anticipation (artificial intelligence); Cognitive psychology; Temporal lobe; Episodic memory; Irrational number; Cognition; Neuroscience; Philosophy; Computer science; Epilepsy","score_opus":0.056841196635600916,"score_gpt":0.3709184966585977,"score_spread":0.31407730002299683,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1851457994","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9848269,0.000023586379,0.0016569312,0.00028098346,0.00083683897,0.0001344481,0.000020319389,0.00008495692,0.012134985],"genre_scores_gemma":[0.9948764,0.0000030050016,0.0024908509,0.0005780561,0.00018464398,0.0000067983774,0.000012374798,0.000025795514,0.0018221152],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9972438,0.00022118793,0.0006485741,0.0007271644,0.00079805887,0.0003612124],"domain_scores_gemma":[0.99783397,0.00043478337,0.00023476446,0.001090539,0.000106035266,0.0002998862],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0024399243,0.00021746228,0.00042366365,0.00020368822,0.00022626642,0.0004877784,0.0010883216,0.00013431313,0.0017858247],"category_scores_gemma":[0.00042756446,0.00016573488,0.00015493156,0.00026074107,0.00013214457,0.000428257,0.000095110365,0.00015052424,0.010520602],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004534578,0.00013987065,0.009105491,5.1059453e-7,0.000005385597,0.000005517314,0.0003997159,0.000054555105,0.0021936453,0.00022563258,0.011412423,0.9764119],"study_design_scores_gemma":[0.0023772165,0.0012191773,0.06700124,0.000049408744,0.000062951534,0.00021306607,0.0009585822,0.07210384,0.001791436,0.65814614,0.19464913,0.0014277927],"about_ca_topic_score_codex":0.000023992503,"about_ca_topic_score_gemma":0.00002660818,"teacher_disagreement_score":0.9749841,"about_ca_system_score_codex":0.00004851944,"about_ca_system_score_gemma":0.000045800858,"threshold_uncertainty_score":0.9991267},"labels":[],"label_agreement":null},{"id":"W1852307141","doi":"10.2139/ssrn.2028146","title":"Towards a Purely Behavioral Definition of Loss Aversion","year":2012,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Loss aversion; Prospect theory; Expected utility hypothesis; Isoelastic utility; Risk aversion (psychology); Intuition; Economics; Ambiguity aversion; Cumulative prospect theory; Mathematical economics; Preference; Subjective expected utility; Econometrics; Microeconomics; Psychology; Computer science","score_opus":0.13981529564130787,"score_gpt":0.39163071546207434,"score_spread":0.2518154198207665,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1852307141","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9842068,0.0021611128,0.008287871,0.0003549011,0.0027599253,0.00020462113,0.00007654787,0.000033037875,0.0019152054],"genre_scores_gemma":[0.99558824,0.0019553306,0.0015414805,0.00003619081,0.0004958346,0.0000071346417,0.000025988646,0.000045096785,0.00030472418],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.992919,0.00034715104,0.0018088722,0.00068420894,0.0019241148,0.0023166102],"domain_scores_gemma":[0.99563503,0.0002492239,0.002108502,0.0009751417,0.00077168347,0.00026039733],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.011327017,0.00044272692,0.0009292105,0.00080256065,0.0002504042,0.00040317088,0.002085752,0.0006657933,0.00048453134],"category_scores_gemma":[0.000531209,0.00035276604,0.00090779876,0.0003724169,0.00017833889,0.0005012665,0.00096040376,0.005055454,0.000432845],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002600106,0.0006317382,0.0066350196,0.000009390939,0.00008942367,0.000020885846,0.00049957674,0.00016272815,0.00015554146,0.024576832,0.0007290669,0.9662298],"study_design_scores_gemma":[0.00048440084,0.00032525626,0.0013090271,0.00010236992,0.00018500697,0.00059739425,0.00122178,0.00004268719,0.000120106895,0.9937374,0.00148754,0.00038703188],"about_ca_topic_score_codex":0.00023203096,"about_ca_topic_score_gemma":0.0003342538,"teacher_disagreement_score":0.96916056,"about_ca_system_score_codex":0.0016482908,"about_ca_system_score_gemma":0.0048040613,"threshold_uncertainty_score":0.9998924},"labels":[],"label_agreement":null},{"id":"W1859258661","doi":"10.22329/il.v20i3.2283","title":"Stanovich's Who Is Rational? Studies of Individual Differences in Reasoning","year":2000,"lang":"en","type":"article","venue":"Informal Logic","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Epistemology; Psychology; Social psychology; Philosophy","score_opus":0.2548337427983532,"score_gpt":0.420949601165849,"score_spread":0.16611585836749582,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1859258661","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9842054,0.00023831478,0.000020528412,0.00018177745,0.00013162696,0.00008473925,0.000045083554,0.000014664669,0.015077856],"genre_scores_gemma":[0.9973853,0.00009586557,0.00079874485,0.00050978863,0.000028138194,0.000005915975,0.0000031390778,0.0000033345302,0.001169729],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9976088,0.00005054678,0.0010147538,0.00023860382,0.00086202286,0.00022532059],"domain_scores_gemma":[0.998418,0.00078915997,0.0002740654,0.0002849667,0.0001835796,0.00005023287],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0018124471,0.0001338527,0.00042398702,0.00028601137,0.00009934316,0.0001785529,0.0006952478,0.000084081454,0.0022407747],"category_scores_gemma":[0.0008350449,0.000088614426,0.00008671333,0.0005110449,0.00017214908,0.0007582838,0.00013992321,0.0001353208,0.0003226852],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007248722,0.000057145015,0.15679544,0.0000031590291,0.000016266142,0.000007681922,0.005412713,0.0004712176,0.000005484559,0.0021889098,0.0021521677,0.8328173],"study_design_scores_gemma":[0.0009164268,0.0004612432,0.838316,0.0001530317,0.000019507588,0.000018097899,0.008885164,0.0017169787,0.00021530644,0.13424578,0.014619318,0.00043313517],"about_ca_topic_score_codex":0.00002131793,"about_ca_topic_score_gemma":0.00006034495,"teacher_disagreement_score":0.83238417,"about_ca_system_score_codex":0.000024821118,"about_ca_system_score_gemma":0.00007646652,"threshold_uncertainty_score":0.9986713},"labels":[],"label_agreement":null},{"id":"W1865669801","doi":"10.2139/ssrn.1598444","title":"Causal Reasoning in Financial Reporting and Voluntary Disclosure","year":2011,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Voluntary disclosure; Causal reasoning; Key (lock); Psychology; Causal chain; Motivated reasoning; Finance; Business; Computer science; Cognition; Political science; Epistemology","score_opus":0.09341045711007619,"score_gpt":0.3551084396708432,"score_spread":0.26169798256076704,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1865669801","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99627036,0.000666296,0.0011920751,0.00013683889,0.00039655974,0.00005713377,0.0000014660488,0.000013716751,0.0012655543],"genre_scores_gemma":[0.99842405,0.00022319368,0.0006875844,0.00005618984,0.00017511113,0.0000017860269,5.4089423e-7,0.0000139130325,0.00041761037],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99607235,0.00012173452,0.0015380043,0.00040781085,0.00046144272,0.0013986414],"domain_scores_gemma":[0.998088,0.0001698304,0.0012403906,0.0002776324,0.000109248314,0.00011487319],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.013003515,0.000152528,0.00035330222,0.00031419244,0.00023252738,0.00017258927,0.0004287927,0.000109120374,0.00008988356],"category_scores_gemma":[0.004610498,0.00011546727,0.00011148445,0.0003498006,0.00006862876,0.00051372737,0.00012362917,0.0015767834,0.000034695167],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000068634836,0.000046263183,0.43273205,4.4712564e-7,0.000006738473,0.00010976526,0.00066454447,0.0000090387875,0.000034037494,0.006524403,0.000129,0.5596751],"study_design_scores_gemma":[0.0003355366,0.00019447072,0.17319505,0.000035055476,0.000011957302,0.0016911716,0.0021920966,0.00017022052,0.000021426424,0.82140815,0.0005693726,0.00017549415],"about_ca_topic_score_codex":0.00035991432,"about_ca_topic_score_gemma":0.00603205,"teacher_disagreement_score":0.81488377,"about_ca_system_score_codex":0.0003469988,"about_ca_system_score_gemma":0.0013415026,"threshold_uncertainty_score":0.6850427},"labels":[],"label_agreement":null},{"id":"W1868583142","doi":"10.3982/te800","title":"The evolution of decision and experienced utilities","year":2011,"lang":"en","type":"article","venue":"Theoretical Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Social Sciences and Humanities Research Council; Simon Fraser University","funders":"Social Sciences and Humanities Research Council of Canada; National Science Foundation","keywords":"Incentive; Economics; Microeconomics; Utility theory; Expected utility hypothesis; Public economics; Mathematical economics","score_opus":0.08113580645377999,"score_gpt":0.33657132646442,"score_spread":0.25543552001064,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1868583142","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97586936,0.00013673495,0.0032160566,0.00007855437,0.0004301787,0.00009147273,0.000010525854,0.000014978623,0.020152144],"genre_scores_gemma":[0.9977634,0.00008439314,0.0020053294,0.00003338177,0.000025418532,0.0000059754607,2.34331e-7,0.000008935599,0.000072947034],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99833477,0.00008676584,0.0008241113,0.00035657088,0.00017413536,0.00022363535],"domain_scores_gemma":[0.99599373,0.0028576055,0.00022488608,0.0006830582,0.00012336811,0.00011735852],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025926048,0.00012249801,0.00027783628,0.00010251509,0.00021120704,0.00013792241,0.00072845427,0.00009334013,0.00058197277],"category_scores_gemma":[0.0020049063,0.00007378804,0.00010205707,0.00011709334,0.002118196,0.00022756314,0.0002738765,0.00009622351,0.000104881045],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014177871,0.00001802816,0.0007691133,2.8318004e-7,0.0000023949508,4.175266e-7,0.0007275001,0.0000040680684,0.000012485155,0.7221762,0.000040319956,0.2761074],"study_design_scores_gemma":[0.00015581222,0.00010217166,0.0032876956,0.0000065452286,0.0000062483387,0.000010706872,0.005952609,0.0029930305,0.00038626502,0.9860544,0.0009483071,0.00009617193],"about_ca_topic_score_codex":0.000025496263,"about_ca_topic_score_gemma":0.000021933049,"teacher_disagreement_score":0.27601123,"about_ca_system_score_codex":0.00006704877,"about_ca_system_score_gemma":0.00006744855,"threshold_uncertainty_score":0.78045815},"labels":[],"label_agreement":null},{"id":"W1881113879","doi":"10.2139/ssrn.2609347","title":"A Practitioner's Guide to Nudging","year":2013,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":127,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Quest University Canada; University of Toronto","funders":"","keywords":"Psychology","score_opus":0.044093369937114345,"score_gpt":0.38613912861252064,"score_spread":0.3420457586754063,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1881113879","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9243904,0.00017924549,0.05872197,0.008305852,0.00069642323,0.00017138937,0.0000017253617,0.000038980907,0.0074940273],"genre_scores_gemma":[0.9872783,0.00012436377,0.0021733437,0.0010619091,0.00035964712,0.000011914494,6.076635e-7,0.000019975623,0.008969959],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99614024,0.00012286074,0.0007944143,0.00037345663,0.00081580266,0.0017532096],"domain_scores_gemma":[0.9980488,0.0004406027,0.00034486398,0.00044673885,0.0004652575,0.00025378357],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00629291,0.00015139635,0.00024807194,0.00042052596,0.00035611604,0.00091013935,0.00093487644,0.00007003143,0.0012370726],"category_scores_gemma":[0.0022523322,0.00011066958,0.00017129851,0.0005100661,0.000029028786,0.001010126,0.00012212987,0.0010861411,0.009558254],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012651135,0.000047971385,0.0010434221,1.4072619e-7,0.000016381995,0.000004517704,0.000092592476,0.00038138713,0.00052723876,0.009114486,0.03487482,0.95388436],"study_design_scores_gemma":[0.0002290948,0.0001866171,0.0010372887,0.000009992644,0.000009014256,0.00064906914,0.0027551919,0.00030320152,0.000049732636,0.8967923,0.09779906,0.00017945585],"about_ca_topic_score_codex":0.00022632796,"about_ca_topic_score_gemma":0.0004099967,"teacher_disagreement_score":0.95370495,"about_ca_system_score_codex":0.0007994616,"about_ca_system_score_gemma":0.0012471526,"threshold_uncertainty_score":0.9996759},"labels":[],"label_agreement":null},{"id":"W1882539431","doi":"10.1002/cjas.1280","title":"The subjective valuation of coins and bills","year":2014,"lang":"en","type":"article","venue":"Canadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l Administration","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Brock University","funders":"","keywords":"Valuation (finance); Economics; Representativeness heuristic; Humanities; Philosophy; Mathematics; Finance","score_opus":0.2800842834621254,"score_gpt":0.40967951739696495,"score_spread":0.12959523393483957,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1882539431","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9890025,0.00021553364,0.0028611424,0.0015892602,0.00069022126,0.00016037776,0.00003538374,0.000003615664,0.005441927],"genre_scores_gemma":[0.9961901,0.000023310173,0.0034261248,0.000098592674,0.00011955652,0.000003234918,8.005666e-7,0.000006245927,0.00013203765],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99638766,0.000581147,0.0012988229,0.0004939347,0.00058943295,0.0006489981],"domain_scores_gemma":[0.99269384,0.0032179237,0.0015081187,0.0003051036,0.001266385,0.0010086565],"candidate_categories":["metaresearch","sts","scholarly_communication"],"consensus_categories":["sts"],"category_scores_codex":[0.018357826,0.00020453538,0.00040421155,0.000706093,0.002444338,0.001212601,0.0015172622,0.0001019441,0.00005016154],"category_scores_gemma":[0.013592093,0.00013634245,0.00014307804,0.0017570934,0.008790209,0.0010860885,0.0000303557,0.00022212292,0.0000053293384],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018705687,0.00011842437,0.1670028,0.00003139118,0.00006159749,0.0001393549,0.03694195,0.004119633,0.0025850101,0.2609275,0.00097391644,0.5269114],"study_design_scores_gemma":[0.00042012977,0.009208593,0.09059892,0.00019918366,0.00006021317,0.001594805,0.03142323,0.011869673,0.0026389856,0.8451694,0.0063767773,0.0004400409],"about_ca_topic_score_codex":0.00301384,"about_ca_topic_score_gemma":0.40560603,"teacher_disagreement_score":0.584242,"about_ca_system_score_codex":0.00037513915,"about_ca_system_score_gemma":0.00692006,"threshold_uncertainty_score":0.9998242},"labels":[],"label_agreement":null},{"id":"W1893249250","doi":"10.1002/cjas.1286","title":"The reversing influence of involvement on the framing effect: The role of emotions and negativity","year":2014,"lang":"en","type":"article","venue":"Canadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l Administration","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Framing effect; Framing (construction); Moderation; Psychology; Negativity effect; Social psychology; Humanities; Philosophy; History","score_opus":0.12235277587360686,"score_gpt":0.362216426689113,"score_spread":0.23986365081550615,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1893249250","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9939451,0.00016307193,0.00021219766,0.002605923,0.00025335583,0.00020650584,0.000022411663,0.0000019012483,0.0025894912],"genre_scores_gemma":[0.9991606,0.00001343464,0.00061803183,0.00011631397,0.000056335797,0.0000037204572,2.406045e-7,0.0000040326113,0.000027289858],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99681383,0.0008004489,0.0009870965,0.0003487662,0.0005643268,0.00048554776],"domain_scores_gemma":[0.9896743,0.0073802522,0.0014256221,0.0003938029,0.00065527164,0.00047069407],"candidate_categories":["metaresearch","sts"],"consensus_categories":["sts"],"category_scores_codex":[0.018163979,0.00017720375,0.00031945066,0.00032347965,0.0035765134,0.00076774077,0.0018425465,0.0000666666,0.000020702515],"category_scores_gemma":[0.012529692,0.000088727626,0.00013061415,0.0014351531,0.0094856415,0.0006314037,0.000041987027,0.00029065835,0.0000017122691],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017305982,0.00011869784,0.20775646,0.000045708937,0.000070238566,0.000043134598,0.040551115,0.013795531,0.0062038037,0.37871593,0.0003520974,0.35217422],"study_design_scores_gemma":[0.00039701437,0.0149225965,0.19916756,0.00090116565,0.000107998516,0.0005378608,0.10172243,0.0147417765,0.015787756,0.6441827,0.0070108776,0.0005202712],"about_ca_topic_score_codex":0.004348717,"about_ca_topic_score_gemma":0.25617552,"teacher_disagreement_score":0.35165393,"about_ca_system_score_codex":0.000281398,"about_ca_system_score_gemma":0.0025703146,"threshold_uncertainty_score":0.9977207},"labels":[],"label_agreement":null},{"id":"W1899520281","doi":"","title":"CONTEXTUAL CONTROL OF ACCRUAL THRESHOLDS","year":2006,"lang":"en","type":"article","venue":"Proceedings of Fechner Day","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Discriminative model; Stimulus (psychology); Psychology; Accrual; Context effect; Stimulus control; Cognitive psychology; Computer science; Social psychology; Artificial intelligence; Mathematics; Neuroscience","score_opus":0.056033858537471164,"score_gpt":0.3402327385139502,"score_spread":0.284198879976479,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1899520281","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9683047,0.00010004192,0.000692587,0.0002063854,0.00022731471,0.00018274105,0.000053324176,0.00004175888,0.030191133],"genre_scores_gemma":[0.9981128,0.0000032973232,0.0007614086,0.00006574844,0.000106535794,0.0000088139495,0.0000013948817,0.00001566055,0.000924326],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9971615,0.000010550534,0.0011979722,0.00043593528,0.0009279074,0.00026615278],"domain_scores_gemma":[0.9972162,0.0006178195,0.00082255277,0.00024238444,0.0010294543,0.000071585695],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027772537,0.00017916308,0.00061047886,0.00036106905,0.00006914623,0.00014429187,0.0010520597,0.00015621353,0.00022396698],"category_scores_gemma":[0.0011132605,0.00013233823,0.00022110883,0.00050276186,0.00026524966,0.0005204894,0.00015404657,0.00015111096,0.000076008524],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003050133,0.0006851564,0.35605204,0.000022635591,0.000038047812,0.0000041828075,0.00047967743,0.000075661446,0.12249841,0.055042796,0.07461153,0.39018485],"study_design_scores_gemma":[0.006322658,0.0012029186,0.11820841,0.0002669095,0.00020050936,0.0000659859,0.003497174,0.0026802875,0.17060186,0.6121973,0.08348645,0.0012695866],"about_ca_topic_score_codex":0.00005623806,"about_ca_topic_score_gemma":0.000009375664,"teacher_disagreement_score":0.5571545,"about_ca_system_score_codex":0.000023640632,"about_ca_system_score_gemma":0.000045194138,"threshold_uncertainty_score":0.5396597},"labels":[],"label_agreement":null},{"id":"W1953073323","doi":"10.2139/ssrn.1757240","title":"Effects of Spikes in the Price of Gasoline on Behavioral Intentions: A Mental Accounting Explanation","year":2011,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University; University of Alberta","funders":"","keywords":"Mental accounting; Psychology; Gasoline; Behavioral economics; Economics; Accounting; Actuarial science; Microeconomics; Engineering","score_opus":0.08391627872076415,"score_gpt":0.370578488770261,"score_spread":0.2866622100494969,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1953073323","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99779195,0.00021330074,0.0009719375,0.0000706272,0.0002544569,0.0001520836,0.0000024228248,0.000004148458,0.0005390951],"genre_scores_gemma":[0.9995772,0.00017093617,0.00014198263,0.000027017715,0.00003766912,0.0000047805124,9.2737014e-7,0.0000070295614,0.00003244439],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99749583,0.00017462077,0.00078708166,0.00018338194,0.0007826386,0.00057646685],"domain_scores_gemma":[0.99835247,0.0005382671,0.00067611894,0.00022772538,0.00018012863,0.000025262656],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006050619,0.00010597099,0.00023179856,0.00043482127,0.00008811983,0.00005320916,0.00076929474,0.000054717962,0.00003414359],"category_scores_gemma":[0.0008164956,0.00006538789,0.00015074274,0.00043245897,0.000058704558,0.00033095546,0.00004667637,0.0006537004,0.0000140382745],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006221166,0.0034505606,0.06343263,0.000010539787,0.00003551143,0.00002214535,0.008024622,0.000041924603,0.011671676,0.033366356,0.00022979066,0.8790921],"study_design_scores_gemma":[0.0026107333,0.004085475,0.08317317,0.00032691628,0.00011642035,0.0005274213,0.0332354,0.00033393374,0.012597789,0.8623235,0.00029964122,0.00036954877],"about_ca_topic_score_codex":0.000103251354,"about_ca_topic_score_gemma":0.00053064985,"teacher_disagreement_score":0.87872255,"about_ca_system_score_codex":0.00021087742,"about_ca_system_score_gemma":0.00032877986,"threshold_uncertainty_score":0.28400394},"labels":[],"label_agreement":null},{"id":"W195370548","doi":"","title":"Utility: Anticipated, Experienced, and Remembered","year":2015,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Quest University Canada","funders":"","keywords":"Pleasure; Context (archaeology); Normative; Pain and pleasure; Expected utility hypothesis; Marginal utility; Psychology; Action (physics); Value (mathematics); Social psychology; Subjective expected utility; Utility maximization; Positive economics; Economics; Epistemology; Mathematical economics; Microeconomics; Philosophy; Computer science; Psychotherapist","score_opus":0.21730538265588908,"score_gpt":0.42070613985828387,"score_spread":0.20340075720239478,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W195370548","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9917377,0.0012422425,0.0029464476,0.0005721459,0.00057538575,0.00006615276,0.0000019322097,0.000026284888,0.0028316576],"genre_scores_gemma":[0.99774253,0.00032910178,0.00026936707,0.00010476358,0.00014079924,0.0000016636312,5.167953e-7,0.000012913866,0.0013983548],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9963441,0.00017042148,0.00068617123,0.00042044264,0.0008560294,0.0015228388],"domain_scores_gemma":[0.9983945,0.00021892342,0.00029005253,0.00041919053,0.00035000066,0.00032737246],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008715976,0.00016024691,0.0003144107,0.00023430714,0.00023059298,0.0005059848,0.00067243126,0.00009613998,0.000111726156],"category_scores_gemma":[0.0019940012,0.000114651055,0.00009850038,0.00038414996,0.0001425736,0.00057111925,0.00015063786,0.00092595606,0.0002256681],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000117153606,0.00006041544,0.013969979,2.775947e-7,0.000015851267,0.000017322809,0.0008799422,0.000017208666,0.00008158696,0.006508542,0.0012631336,0.9770686],"study_design_scores_gemma":[0.0007030266,0.0002799908,0.00075818604,0.000008135895,0.00001443043,0.0011552757,0.01703099,0.0009113897,0.000069747315,0.95839196,0.020488976,0.00018791527],"about_ca_topic_score_codex":0.000055246514,"about_ca_topic_score_gemma":0.0004957136,"teacher_disagreement_score":0.97688067,"about_ca_system_score_codex":0.00024218614,"about_ca_system_score_gemma":0.0016632007,"threshold_uncertainty_score":0.4879223},"labels":[],"label_agreement":null},{"id":"W1956640694","doi":"10.1111/j.1540-5982.2011.01650.x","title":"A simple explanation of some key time preference anomalies","year":2011,"lang":"fr","type":"article","venue":"Canadian Journal of Economics/Revue canadienne d économique","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Humanities; Context (archaeology); Preference; Economics; Mathematical economics; Philosophy; Microeconomics; Geography","score_opus":0.4353922798807204,"score_gpt":0.25875474403527104,"score_spread":0.17663753584544933,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1956640694","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9865583,0.0017135617,0.000076407305,0.0010810833,0.004872672,0.00029439043,0.0012549133,0.0000063512434,0.0041422737],"genre_scores_gemma":[0.9937144,0.00029507533,0.0014959072,0.00035827767,0.00064919714,0.000007496433,0.000018788765,0.00007057763,0.0033902617],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9946207,0.00025074463,0.003244743,0.00071581017,0.000015881727,0.0011521516],"domain_scores_gemma":[0.99158674,0.00073770003,0.003060814,0.0009879146,0.00089504063,0.0027318154],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003010102,0.0005275526,0.0015354475,0.0020403003,0.00024024445,0.00034036482,0.0021484795,0.0005427015,0.0066788625],"category_scores_gemma":[0.0013054501,0.0006062958,0.000604549,0.0003452145,0.00072505546,0.0024630723,0.00006958358,0.00055379653,0.0004754868],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005168435,0.0002177372,0.031818997,0.00010671669,0.00049178203,0.0007667359,0.0191021,0.0054663448,0.00010187561,0.5269519,0.010177185,0.40428177],"study_design_scores_gemma":[0.0009266067,0.001143721,0.0035304048,0.00037625426,0.0001752041,0.00080506643,0.0020861842,0.0032350945,0.0006856519,0.9199059,0.0662756,0.0008542856],"about_ca_topic_score_codex":0.20737089,"about_ca_topic_score_gemma":0.91338384,"teacher_disagreement_score":0.70601296,"about_ca_system_score_codex":0.0021585624,"about_ca_system_score_gemma":0.006470845,"threshold_uncertainty_score":0.99963886},"labels":[],"label_agreement":null},{"id":"W1963395863","doi":"10.1111/j.2044-8295.2011.02047.x","title":"Framing effects and risk‐sensitive decision making","year":2011,"lang":"en","type":"article","venue":"British Journal of Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":70,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph; University of Lethbridge","funders":"","keywords":"Framing (construction); Framing effect; Prospect theory; Psychology; Risk-seeking; Social psychology; Decision theory; Risk perception; Perception; Economics; Microeconomics; Engineering","score_opus":0.08641672518660555,"score_gpt":0.409250412450968,"score_spread":0.32283368726436246,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1963395863","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96112233,0.0011665705,0.03337703,0.000026147618,0.0020564925,0.00006318558,0.000006726396,0.000009129088,0.0021723602],"genre_scores_gemma":[0.9673357,0.00065293314,0.031490378,0.00032993694,0.00015519037,6.19577e-7,1.0674214e-7,0.000014809296,0.000020329519],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9974653,0.00038235608,0.0010521375,0.000385974,0.00046078704,0.00025346034],"domain_scores_gemma":[0.9958102,0.0022929262,0.001055168,0.0002745772,0.00041406418,0.00015305362],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0039730477,0.00012984854,0.0004960542,0.0004030914,0.00018543254,0.0002217213,0.00052878266,0.00017644318,0.00021500129],"category_scores_gemma":[0.0048621865,0.00011961125,0.00017476667,0.00026437326,0.00018843147,0.0003887911,0.0001221466,0.00051410147,0.00009528761],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014788154,0.000079570425,0.027056495,9.3027916e-7,0.000017550045,0.001632056,0.00034455664,0.0000026744713,0.00006229688,0.000021503009,0.0031820047,0.96745247],"study_design_scores_gemma":[0.0009704766,0.0005088235,0.7758945,0.0003375793,0.00005006193,0.018112833,0.00031382695,0.000050101426,0.00007011964,0.20094259,0.0025719875,0.00017707514],"about_ca_topic_score_codex":0.00003335853,"about_ca_topic_score_gemma":0.000088260436,"teacher_disagreement_score":0.9672754,"about_ca_system_score_codex":0.000021688462,"about_ca_system_score_gemma":0.000030302504,"threshold_uncertainty_score":0.58208424},"labels":[],"label_agreement":null},{"id":"W1964086661","doi":"10.2139/ssrn.894101","title":"Measuring Performance in a Dynamic World: Conditional Mean-Variance Fundamentals","year":2006,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; University of Alberta","funders":"","keywords":"Variance (accounting); Econometrics; Conditional variance; Statistics; Economics; Mathematics; Autoregressive conditional heteroskedasticity; Accounting; Volatility (finance)","score_opus":0.05477964124988577,"score_gpt":0.33501113062242943,"score_spread":0.28023148937254366,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1964086661","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9914137,0.00072565145,0.0040963693,0.00042220746,0.00039320727,0.00009670051,0.00000841255,0.000021630127,0.0028221193],"genre_scores_gemma":[0.99522084,0.00018085034,0.00028979048,0.00008218771,0.00015842798,0.000006639475,0.000005728385,0.000018675384,0.004036847],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.995641,0.00013722946,0.001037897,0.00043876565,0.0010229851,0.0017221443],"domain_scores_gemma":[0.9987195,0.00030387437,0.00043922104,0.00030727524,0.00015067123,0.00007944321],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0068645165,0.00019908522,0.0003364718,0.00080427434,0.00031302782,0.0004147505,0.0008097757,0.00006872122,0.00028471113],"category_scores_gemma":[0.00014761048,0.00016659278,0.00016231899,0.0008456445,0.000086350745,0.0007916961,0.00007713429,0.0013608438,0.00047887277],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026335017,0.0005020042,0.12816103,0.0000036890433,0.000047656536,0.000058789377,0.0001769534,0.018315237,0.0012354319,0.061677247,0.00060050975,0.7889581],"study_design_scores_gemma":[0.0008548601,0.00010282692,0.048271526,0.00004400446,0.00000921003,0.00051608984,0.0005451885,0.003138999,0.00007101233,0.94208324,0.004106364,0.0002566783],"about_ca_topic_score_codex":0.000060111088,"about_ca_topic_score_gemma":0.009351761,"teacher_disagreement_score":0.88040596,"about_ca_system_score_codex":0.0019931903,"about_ca_system_score_gemma":0.0011930692,"threshold_uncertainty_score":0.67934567},"labels":[],"label_agreement":null},{"id":"W1964233664","doi":"10.3758/bf03193398","title":"Effects of instruction presentation mode in comparative judgments","year":2006,"lang":"en","type":"article","venue":"Memory & Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Psychology; Stimulus (psychology); Cognitive psychology; Randomized controlled trial; Audiology","score_opus":0.10045935363489521,"score_gpt":0.4071029732870954,"score_spread":0.30664361965220016,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1964233664","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9907186,0.00002094437,0.0012070875,0.000023888617,0.00037226727,0.00029389578,0.000012196825,0.00001769013,0.0073334384],"genre_scores_gemma":[0.999311,0.0000025997808,0.00045470078,0.000022362048,0.000046691428,0.000022579477,0.00003125338,0.0000052167215,0.000103618404],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9983474,0.00016001004,0.0005987103,0.00029074596,0.00048445366,0.000118682125],"domain_scores_gemma":[0.9988726,0.00049721077,0.00030763168,0.00015390063,0.0001426247,0.000026074202],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038498832,0.00009671438,0.0002385558,0.0003750762,0.000053349315,0.00006512192,0.00014665302,0.00006450667,0.00005404284],"category_scores_gemma":[0.00017730147,0.00008662404,0.00006223082,0.00042339755,0.00006284464,0.0004900778,0.000033268843,0.00008318949,0.000113521884],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005314092,0.0012232789,0.01548617,0.000038684233,0.000015609528,0.000024725996,0.0014690071,0.011590381,0.18926282,0.0003945193,0.0018908753,0.77807254],"study_design_scores_gemma":[0.0033138504,0.00017495501,0.3575397,0.00014134076,0.000048642,0.000009293128,0.001162144,0.008950314,0.37923256,0.24899456,0.00015741694,0.00027519767],"about_ca_topic_score_codex":0.00021570928,"about_ca_topic_score_gemma":0.0001839575,"teacher_disagreement_score":0.77779734,"about_ca_system_score_codex":0.000040664392,"about_ca_system_score_gemma":0.000022452752,"threshold_uncertainty_score":0.35324258},"labels":[],"label_agreement":null},{"id":"W1964373575","doi":"10.1007/s10683-011-9293-5","title":"Risk aversion and framing effects","year":2011,"lang":"en","type":"article","venue":"Experimental Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":70,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Center for Interuniversity Research and Analysis on Organizations","funders":"Agence Nationale de la Recherche","keywords":"Lottery; Framing effect; Framing (construction); Normative; Stochastic game; Economics; Risk aversion (psychology); Psychology; Social psychology; Incentive; Loss aversion; Salient; Econometrics; Microeconomics; Expected utility hypothesis; Mathematical economics; Computer science; Political science; Artificial intelligence","score_opus":0.09156778749823381,"score_gpt":0.3437459284481459,"score_spread":0.2521781409499121,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1964373575","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9879265,0.00028311595,0.0002086869,0.0000120155355,0.0009856699,0.00012964531,0.000010163283,0.000035831792,0.010408407],"genre_scores_gemma":[0.9947913,0.000058307905,0.00472541,0.00015186546,0.000059331607,0.000007580417,0.0000013777492,0.000017693206,0.00018712899],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99858314,0.000065680004,0.00046445453,0.0005531142,0.00011521121,0.00021838889],"domain_scores_gemma":[0.99867415,0.00041022612,0.00026328646,0.00046004154,0.000023187675,0.00016911051],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00072550715,0.00016978651,0.00028173794,0.00016257174,0.00022116616,0.00020280793,0.00040116993,0.000101687176,0.0005620755],"category_scores_gemma":[0.0001917124,0.00014904859,0.00010412496,0.00007470634,0.00012565462,0.00050432736,0.00031615223,0.00012440821,0.0009067191],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002037421,0.0003886265,0.059566386,0.0000027338199,0.00003317279,0.00002739539,0.007829262,0.00004583035,0.00226305,0.0033279264,0.0018372937,0.9244746],"study_design_scores_gemma":[0.005264681,0.0020415573,0.100071535,0.00007571151,0.000091251655,0.00016802948,0.022130996,0.018189676,0.4516159,0.34079328,0.05703365,0.0025237305],"about_ca_topic_score_codex":0.000101236496,"about_ca_topic_score_gemma":0.000011103202,"teacher_disagreement_score":0.9219509,"about_ca_system_score_codex":0.00008975275,"about_ca_system_score_gemma":0.00002056532,"threshold_uncertainty_score":0.9998712},"labels":[],"label_agreement":null},{"id":"W1964499747","doi":"10.3758/s13421-013-0318-5","title":"Act first, think later: The presence and absence of inferential planning in problem solving","year":2013,"lang":"en","type":"article","venue":"Memory & Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Problem solver; Heuristics; Irrational number; Solver; Psychology; Maximization; Ball (mathematics); Mathematical optimization; Cognitive psychology; Computer science; Social psychology; Mathematics","score_opus":0.08864594523575228,"score_gpt":0.34869097728367643,"score_spread":0.2600450320479242,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1964499747","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9958548,0.000052661955,0.00027202096,0.0003017794,0.00015394716,0.00027977,0.000004888463,0.00001689612,0.0030632247],"genre_scores_gemma":[0.9992666,0.000011962151,0.0004948462,0.000064925494,0.000031843352,0.00001557671,0.000002496651,0.000005992412,0.00010575987],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.998548,0.000094937706,0.00050810055,0.00029868176,0.0003805422,0.0001697493],"domain_scores_gemma":[0.9980979,0.0011907163,0.00024575627,0.00026102707,0.0001620763,0.00004253539],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012220403,0.00010098948,0.0001832687,0.000155893,0.00014259582,0.0003039832,0.0003410766,0.00006530472,0.00036653248],"category_scores_gemma":[0.0007204285,0.00006478301,0.000041744595,0.00022365944,0.00012767232,0.0007021409,0.00016787554,0.00015955405,0.00012114605],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000713548,0.000141697,0.07415026,0.000025436142,0.000010925342,0.000019408903,0.0099296495,0.001568142,0.0050628497,0.00006141952,0.0024561246,0.9065027],"study_design_scores_gemma":[0.0009794335,0.00018082447,0.7098709,0.0007049948,0.000028498534,0.000049683218,0.005776614,0.020407515,0.0041064015,0.25685254,0.0006283309,0.00041428],"about_ca_topic_score_codex":0.00013198619,"about_ca_topic_score_gemma":0.00011659515,"teacher_disagreement_score":0.9060885,"about_ca_system_score_codex":0.000012932164,"about_ca_system_score_gemma":0.000028686434,"threshold_uncertainty_score":0.40132734},"labels":[],"label_agreement":null},{"id":"W1965607475","doi":"10.1506/car.25.3.6","title":"Debiasing Scale Compatibility Effects when Investors Use Nonfinancial Measures to Screen Potential Investments*","year":2008,"lang":"en","type":"article","venue":"Contemporary Accounting Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Compatibility (geochemistry); Business; Scale (ratio); Finance; Actuarial science; Engineering; Geography","score_opus":0.41434849713991234,"score_gpt":0.44236783766142707,"score_spread":0.028019340521514724,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1965607475","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9931645,0.00017428982,0.0013355104,0.00091583905,0.00086454034,0.0010656705,0.000042009895,0.00012489286,0.002312778],"genre_scores_gemma":[0.99308985,0.0000048710776,0.0043700715,0.00077410904,0.00038126248,0.0000353703,0.000016908587,0.000050937262,0.0012766101],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99045146,0.0014839263,0.0014355315,0.0015584606,0.004073709,0.0009969091],"domain_scores_gemma":[0.9914154,0.0038580876,0.00035811577,0.0017596465,0.0019744264,0.00063436764],"candidate_categories":["metaresearch","metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.014963196,0.00037011583,0.00079718325,0.0014105152,0.0018166765,0.0015849072,0.0021658565,0.0002598808,0.000096519514],"category_scores_gemma":[0.01974055,0.00031665803,0.00027674058,0.0017313897,0.00079419505,0.0024720153,0.001259961,0.0008912897,0.0012496648],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000490957,0.0003742387,0.7253251,0.000013650165,0.000021663887,0.0002517785,0.0021111697,0.00012251253,0.0034380988,0.00007117077,0.15030657,0.1174731],"study_design_scores_gemma":[0.0019124264,0.0004520512,0.8648602,0.00038445526,0.000014339411,0.000075256816,0.00074371975,0.0018448577,0.0040667253,0.030145938,0.094455436,0.0010446102],"about_ca_topic_score_codex":0.0030280915,"about_ca_topic_score_gemma":0.00043839766,"teacher_disagreement_score":0.1395351,"about_ca_system_score_codex":0.0002846653,"about_ca_system_score_gemma":0.0010480474,"threshold_uncertainty_score":0.99992853},"labels":[],"label_agreement":null},{"id":"W1965630026","doi":"10.1111/1911-3838.12022","title":"The Impact of Better-than-Average Bias and Relative Performance Pay on Performance Outcome Satisfaction","year":2014,"lang":"en","type":"article","venue":"Accounting Perspectives","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Psychology; Operationalization; Expectancy theory; Job satisfaction; Social psychology; Humanities; Philosophy","score_opus":0.08668877675148916,"score_gpt":0.3836835178172323,"score_spread":0.29699474106574314,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1965630026","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99646616,0.000045736568,0.00014852465,0.00025222133,0.00027762077,0.00012442189,0.000006059766,0.00003188068,0.002647368],"genre_scores_gemma":[0.9992955,0.0000743821,0.00018849537,0.00002637911,0.00011863764,0.000005134733,4.784218e-7,0.000016341366,0.00027465765],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9978529,0.00014420444,0.0006403542,0.00049437454,0.0005875199,0.0002806419],"domain_scores_gemma":[0.9955217,0.0028954078,0.0006428295,0.00058099366,0.00030514144,0.000053921318],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033368303,0.00021588127,0.00034684152,0.00023363948,0.00062948087,0.0004022702,0.0003988328,0.00008610412,0.000048521124],"category_scores_gemma":[0.0023615907,0.0001075867,0.00017457636,0.00035506088,0.0002775352,0.0010348541,0.00012441809,0.0003366322,0.00011880038],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000049757204,0.000017543276,0.66486216,0.0000014469003,0.000012521657,1.8254671e-7,0.001312191,0.0005115161,0.000055664717,0.00021289437,0.000069049056,0.33289507],"study_design_scores_gemma":[0.00024608112,0.00034689662,0.9812888,0.000036574078,0.000009335463,0.000008817772,0.0014343236,0.011591355,0.00011711628,0.00449805,0.00026046226,0.00016219815],"about_ca_topic_score_codex":0.00020796424,"about_ca_topic_score_gemma":0.00003446498,"teacher_disagreement_score":0.3327329,"about_ca_system_score_codex":0.00013936686,"about_ca_system_score_gemma":0.000036304995,"threshold_uncertainty_score":0.48415214},"labels":[],"label_agreement":null},{"id":"W1965965555","doi":"10.3758/bf03195464","title":"MouseTrace: A better mousetrap for catching decision processes","year":2002,"lang":"en","type":"article","venue":"Behavior Research Methods, Instruments, & Computers","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":40,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"University of Toronto; University of Toledo","keywords":"Variety (cybernetics); Computer science; Process (computing); Decision process; Extension (predicate logic); Artificial intelligence; Machine learning; Data mining; Management science; Engineering; Programming language","score_opus":0.5684489168392943,"score_gpt":0.5922242640286576,"score_spread":0.02377534718936325,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1965965555","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8457837,0.00019432622,0.14937428,0.0008410505,0.0017181557,0.0015861383,0.00011616031,0.0001562532,0.00022993138],"genre_scores_gemma":[0.41510904,0.000086092565,0.58290285,0.00033474242,0.00026390242,0.0004852188,0.000016729462,0.00009673727,0.0007046731],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9895173,0.0014371782,0.0019513381,0.0020200575,0.0035221928,0.0015519812],"domain_scores_gemma":[0.9834776,0.011954306,0.00048440747,0.0019134434,0.0016255999,0.0005446562],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.015455726,0.0005320722,0.0009184345,0.001969523,0.0012722567,0.002309587,0.00350613,0.00034966937,0.0006428729],"category_scores_gemma":[0.007883179,0.00044007486,0.00045032348,0.0025216704,0.000455346,0.0012463507,0.0010302507,0.0010454191,0.00058991567],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000075920114,0.0005583933,0.0060815685,0.000016388156,0.000018146466,0.000027924592,0.0006365227,0.000063833875,0.0007933435,0.000061303646,0.02628039,0.9653863],"study_design_scores_gemma":[0.007258874,0.0025564425,0.011353202,0.0006815183,0.00019018952,0.0004083626,0.0035869018,0.042333916,0.012767389,0.15140507,0.764283,0.003175112],"about_ca_topic_score_codex":0.00010096606,"about_ca_topic_score_gemma":0.00005381763,"teacher_disagreement_score":0.96221113,"about_ca_system_score_codex":0.00042375168,"about_ca_system_score_gemma":0.00019335543,"threshold_uncertainty_score":0.9998051},"labels":[],"label_agreement":null},{"id":"W1966428987","doi":"10.1016/j.addbeh.2014.04.026","title":"Discounting of money and sex: Effects of commodity and temporal position in stimulant-dependent men and women","year":2014,"lang":"en","type":"article","venue":"Addictive Behaviors","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":81,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Lethbridge","funders":"National Institute on Drug Abuse","keywords":"Delay discounting; Discounting; Addiction; Impulsivity; Psychology; Temporal discounting; Economics; Developmental psychology; Psychiatry","score_opus":0.023712582037255334,"score_gpt":0.326662955939349,"score_spread":0.3029503739020937,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1966428987","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9991645,0.000052267835,0.00029035847,0.000016967748,0.000059497404,0.00021525763,0.000070584916,0.00000791262,0.00012264207],"genre_scores_gemma":[0.99971247,0.00001332373,0.00020764284,0.000011823744,0.000009447302,0.000009084298,0.000004600228,0.000008789108,0.00002283602],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99836594,0.00017980339,0.0005341475,0.00037944032,0.00036537743,0.00017531138],"domain_scores_gemma":[0.9982368,0.001025281,0.00032732982,0.00023721691,0.000072274735,0.00010110515],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015643439,0.00013926545,0.00045556333,0.00025525605,0.00006810364,0.000067627254,0.00015123533,0.000086798645,0.000012183338],"category_scores_gemma":[0.00031189914,0.00011280189,0.000028528082,0.00014363062,0.00028728673,0.00031745053,0.00021473285,0.00013228494,0.0000012064061],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000072988914,0.00016090849,0.76977754,0.000012913582,0.000006560567,0.0000072296643,0.0033377914,0.000021223219,0.0045342175,0.0000879238,0.000024717969,0.22195601],"study_design_scores_gemma":[0.0014837974,0.0007576772,0.975304,0.000121730285,0.00004794813,0.000014429591,0.0033913106,0.0025740552,0.003989612,0.012084324,0.000019372332,0.00021176344],"about_ca_topic_score_codex":0.00041708053,"about_ca_topic_score_gemma":0.00005861539,"teacher_disagreement_score":0.22174424,"about_ca_system_score_codex":0.000044872726,"about_ca_system_score_gemma":0.00001806682,"threshold_uncertainty_score":0.45999277},"labels":[],"label_agreement":null},{"id":"W1966720862","doi":"10.1177/0272989x03256004","title":"Fast and Frugal Models of Clinical Judgment in Novice and Expert Physicians","year":2003,"lang":"en","type":"article","venue":"Medical Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute of Infection and Immunity","funders":"","keywords":"Vignette; Heuristic; Matching (statistics); Psychology; Value (mathematics); Clinical judgment; Logistic regression; Medicine; Applied psychology; Social psychology; Computer science; Statistics; Artificial intelligence; Mathematics; Medical physics; Pathology","score_opus":0.18905995399552714,"score_gpt":0.481086002958928,"score_spread":0.2920260489634009,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1966720862","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94510704,0.00041566236,0.050832056,0.00028468636,0.0006392149,0.00012805867,0.0000055083133,0.000013767679,0.0025740159],"genre_scores_gemma":[0.98030335,0.00020936671,0.018402893,0.00095918996,0.00006996161,0.000005176241,3.131417e-7,0.0000148935405,0.00003488674],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99430287,0.00035555052,0.0021502385,0.00084429776,0.0020271605,0.00031990476],"domain_scores_gemma":[0.9907487,0.007851345,0.0004171309,0.000567534,0.00014984244,0.00026543395],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.008880311,0.0002001188,0.0008394054,0.00033639683,0.00009329917,0.00014593874,0.00055283547,0.0002791235,0.0003800885],"category_scores_gemma":[0.013281549,0.00014716694,0.00013692041,0.0004979268,0.0003270941,0.00032807112,0.00035101775,0.0003987208,0.000031840114],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006894096,0.0001725252,0.011287985,0.0000017335692,0.0000035788566,0.000042735435,0.00035399044,0.00021727181,0.000013785259,0.0011180919,0.0007040941,0.98601526],"study_design_scores_gemma":[0.003918147,0.00046165014,0.043095853,0.0014355448,0.00002313929,0.00011842104,0.0035218818,0.1933836,0.00007855868,0.7379009,0.015361076,0.0007012368],"about_ca_topic_score_codex":0.000022899982,"about_ca_topic_score_gemma":0.00011637359,"teacher_disagreement_score":0.985314,"about_ca_system_score_codex":0.000027089502,"about_ca_system_score_gemma":0.000120020944,"threshold_uncertainty_score":0.99503},"labels":[],"label_agreement":null},{"id":"W1966993054","doi":"10.1136/ip.2003.003624","title":"Do children’s intentions to risk take relate to actual risk taking?","year":2004,"lang":"en","type":"article","venue":"Injury Prevention","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":44,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"Canadian Institutes of Health Research","keywords":"Human factors and ergonomics; Suicide prevention; Poison control; Forensic engineering; Injury prevention; Psychology; Occupational safety and health; Environmental health; Risk analysis (engineering); Engineering; Medicine","score_opus":0.06755703274500012,"score_gpt":0.40286026832787264,"score_spread":0.3353032355828725,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1966993054","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95680964,0.000023553483,0.03922741,0.0004626354,0.0013423732,0.0005877417,0.00025217436,0.000120829376,0.0011736536],"genre_scores_gemma":[0.9888454,0.000022862729,0.009557313,0.00021550347,0.00016324343,0.00004852555,0.000011132364,0.00002930638,0.0011067025],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9961467,0.00033244488,0.0011355579,0.00096208625,0.0010195546,0.0004036613],"domain_scores_gemma":[0.9969507,0.00029295502,0.0010090818,0.0011027857,0.00030075392,0.00034375905],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0045726043,0.00025433704,0.0003601586,0.0007673281,0.00047490504,0.0006374407,0.0009434083,0.00017887008,0.0008381773],"category_scores_gemma":[0.008270217,0.0002179728,0.00040402223,0.0010749424,0.000050235925,0.0005792562,0.0003719062,0.00041315836,0.00755827],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016555187,0.00026206233,0.019734122,4.7209667e-7,0.000027752578,0.0000031839027,0.0005959037,0.0032658244,0.0003462686,0.00040882116,0.004411743,0.9707783],"study_design_scores_gemma":[0.0008535715,0.0010751777,0.5918012,0.00017617614,0.00014824647,0.000026481464,0.0004332436,0.00004960488,0.0011622746,0.3879242,0.01572895,0.00062082685],"about_ca_topic_score_codex":0.00025732783,"about_ca_topic_score_gemma":0.00040861132,"teacher_disagreement_score":0.97015744,"about_ca_system_score_codex":0.00024978153,"about_ca_system_score_gemma":0.00010758297,"threshold_uncertainty_score":0.9932145},"labels":[],"label_agreement":null},{"id":"W1968966047","doi":"10.1126/science.1238041","title":"Poverty Impedes Cognitive Function","year":2013,"lang":"en","type":"article","venue":"Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2909,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Economic and Social Research Council","keywords":"Poverty; Tamil; Cognition; Perspective (graphical); Poverty rate; Economics; Business; Demographic economics; Economic growth; Psychology; Computer science","score_opus":0.11925443234987178,"score_gpt":0.40424292129877165,"score_spread":0.2849884889488999,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1968966047","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97859776,0.00003333371,0.002174895,0.00034964853,0.0010567737,0.00013245227,0.000005202575,0.000041750405,0.01760821],"genre_scores_gemma":[0.9970601,0.0000022557235,0.00041138602,0.0009846307,0.000052805688,0.000009926328,4.6637177e-7,0.0000040908044,0.001474298],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99757975,0.000035520145,0.00034860807,0.0006091451,0.0011112436,0.00031575628],"domain_scores_gemma":[0.99795085,0.00060075946,0.00014909799,0.00041571076,0.0007008792,0.00018269828],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0023281462,0.00009617153,0.00014106632,0.00030408666,0.00041494978,0.001155206,0.00089889846,0.000039643204,0.0027542736],"category_scores_gemma":[0.0033779794,0.000062736144,0.00006447429,0.001319747,0.0005462699,0.0019464716,0.0002280085,0.00009383457,0.012397803],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007239924,0.000025989022,0.006607544,1.6601787e-7,8.552241e-7,9.5080185e-7,0.00010533232,0.000007835883,0.00393773,0.00023960351,0.0049963607,0.9840704],"study_design_scores_gemma":[0.00034998104,0.00026534765,0.4440228,0.00002560889,0.00001504193,0.000021449881,0.00334784,0.0034906426,0.0034104616,0.5252811,0.019387752,0.00038200014],"about_ca_topic_score_codex":0.00005892818,"about_ca_topic_score_gemma":0.000013997268,"teacher_disagreement_score":0.9836884,"about_ca_system_score_codex":0.0000421189,"about_ca_system_score_gemma":0.00016456922,"threshold_uncertainty_score":0.9998817},"labels":[],"label_agreement":null},{"id":"W1969204312","doi":"10.1007/s40429-015-0045-z","title":"Using Behavior Economics to Understand Alcohol Use Disorders: a Concise Review and Identification of Research Priorities","year":2015,"lang":"en","type":"review","venue":"Current Addiction Reports","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; St. Joseph’s Healthcare Hamilton","funders":"National Institute on Drug Abuse; National Institutes of Health","keywords":"Psychology; Discounting; Psychological intervention; Reinforcement; Delay discounting; Randomized controlled trial; Identification (biology); Clinical psychology; Medicine; Psychiatry; Impulsivity; Social psychology","score_opus":0.768445325675827,"score_gpt":0.6113633404578281,"score_spread":0.15708198521799888,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1969204312","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004643977,0.9896314,0.00020635361,0.000023116587,0.0025485058,0.0025906519,0.0002692837,0.000035485777,0.000051194776],"genre_scores_gemma":[0.00070763216,0.99850696,0.00017060271,0.00000792781,0.00010905754,0.00012945411,0.00008097983,0.00004889041,0.00023848543],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9925101,0.00055090175,0.0041162083,0.0013298751,0.0011360409,0.00035691055],"domain_scores_gemma":[0.99242985,0.00092929864,0.0029296852,0.0016289102,0.0017211201,0.00036112982],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.010436705,0.00041303787,0.0021765379,0.0013563666,0.00024090821,0.0007248769,0.00047694755,0.0002713737,0.000083345534],"category_scores_gemma":[0.0047105183,0.0003479715,0.00039317273,0.0014315931,0.00032613895,0.00079013355,0.00045280906,0.00050347747,0.000052934854],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000035870057,0.00008038478,0.00016569695,0.0013667849,0.000019368941,0.000008794626,0.00006774584,0.000007855701,1.5479587e-7,0.0000335562,0.0057483404,0.99249774],"study_design_scores_gemma":[0.00007822983,0.00004918342,0.000056293386,0.014470328,0.0011138218,0.00022041981,0.00013513007,0.00002426309,3.4544618e-7,0.0028760186,0.98062843,0.0003475312],"about_ca_topic_score_codex":0.000042216405,"about_ca_topic_score_gemma":0.00003997431,"teacher_disagreement_score":0.9921502,"about_ca_system_score_codex":0.000635398,"about_ca_system_score_gemma":0.0012058114,"threshold_uncertainty_score":0.99989724},"labels":[],"label_agreement":null},{"id":"W1969624676","doi":"10.1006/obhd.2000.2941","title":"Choice Environment, Market Complexity, and Consumer Behavior: A Theoretical and Empirical Approach for Incorporating Decision Complexity into Models of Consumer Choice","year":2001,"lang":"en","type":"article","venue":"Organizational Behavior and Human Decision Processes","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":335,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Context (archaeology); Consumer choice; Econometric model; Consumer behaviour; Task (project management); Choice set; Empirical research; Econometrics; Construct (python library); Computer science; Management science; Psychology; Economics; Microeconomics; Social psychology; Mathematics; Statistics","score_opus":0.15523496886584218,"score_gpt":0.3955967711956773,"score_spread":0.24036180232983514,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1969624676","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9398336,0.0005770732,0.058084473,0.00007861619,0.000072859824,0.00081210234,0.00022911519,0.0000418634,0.00027031545],"genre_scores_gemma":[0.93868166,0.00021650923,0.060568962,0.00012607856,0.00005590945,0.0000878447,0.000126174,0.00005702821,0.000079825324],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9952472,0.00013911349,0.0016134838,0.0013537309,0.001285838,0.00036066215],"domain_scores_gemma":[0.99257874,0.0049357223,0.0006400672,0.00057973125,0.0008740203,0.0003917402],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0016390532,0.0004696116,0.00087510754,0.00046586557,0.0010144047,0.0006532934,0.00064572314,0.00029962132,0.001009724],"category_scores_gemma":[0.0029915029,0.0003837329,0.000090048474,0.0006447986,0.0024599424,0.00080088474,0.0007794212,0.00025792024,0.000008825531],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023035897,0.001054567,0.8921451,0.00004329012,0.000017441154,0.0000074014324,0.00031670157,0.000027529111,0.00039251376,0.012117441,0.001392336,0.092255294],"study_design_scores_gemma":[0.0025297871,0.000343423,0.30353525,0.00010647755,0.00031747215,0.00022760672,0.000433881,0.0036568234,0.00014822144,0.6851957,0.0027392048,0.0007661748],"about_ca_topic_score_codex":0.000046781533,"about_ca_topic_score_gemma":0.00011326226,"teacher_disagreement_score":0.67307824,"about_ca_system_score_codex":0.000057171732,"about_ca_system_score_gemma":0.00014614481,"threshold_uncertainty_score":0.9999035},"labels":[],"label_agreement":null},{"id":"W1969725632","doi":"10.1016/s0377-2217(02)00468-x","title":"Incorporating wealth information into a multiple criteria decision making model","year":2003,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":34,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Operations research; Artificial intelligence; Mathematics","score_opus":0.29484286713895896,"score_gpt":0.5033476173833448,"score_spread":0.2085047502443858,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1969725632","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.79009396,0.000054134514,0.19702908,0.0004862542,0.00043772144,0.00013568059,0.000008657729,0.000007745077,0.011746742],"genre_scores_gemma":[0.86368823,0.000010597295,0.13581488,0.00023377624,0.00013706884,0.0000013174089,0.0000024542478,0.000015815009,0.00009589223],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99197435,0.002091283,0.002135038,0.0002613201,0.003222476,0.00031553206],"domain_scores_gemma":[0.991665,0.0028751441,0.0006788516,0.00041076838,0.0041260123,0.00024420346],"candidate_categories":["metaresearch","scholarly_communication","insufficient_payload"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.044420514,0.00014412716,0.0002907662,0.0011920138,0.00074565713,0.0018903394,0.0010790129,0.000043602995,0.00038547523],"category_scores_gemma":[0.038098354,0.000105681094,0.000140886,0.0008211567,0.00013134755,0.0028139064,0.0002420829,0.00067985395,0.00087564136],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040550777,0.00015201802,0.0036436706,0.000005546392,0.000012402165,0.000106625484,0.0023466332,0.091918185,0.0017407495,0.007137686,0.025364192,0.86716676],"study_design_scores_gemma":[0.0029869985,0.0012116061,0.010172237,0.0005764451,0.000012177702,0.0005980382,0.004257119,0.54611486,0.0005095157,0.36026078,0.07270801,0.0005922064],"about_ca_topic_score_codex":0.0000033432132,"about_ca_topic_score_gemma":0.000009080089,"teacher_disagreement_score":0.8665746,"about_ca_system_score_codex":0.00021609521,"about_ca_system_score_gemma":0.0008766802,"threshold_uncertainty_score":0.9999023},"labels":[],"label_agreement":null},{"id":"W1970169623","doi":"10.1037/a0015104","title":"The Impact of Human Intuition in Psychology","year":2009,"lang":"en","type":"article","venue":"Review of General Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Intuition; Counterintuitive; Psychology; Epistemology; Behaviorism; Social psychology; Cognitive psychology; Cognitive science; Philosophy","score_opus":0.2124151168656351,"score_gpt":0.5842482105776459,"score_spread":0.3718330937120108,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1970169623","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.962758,0.022214739,0.00016360324,0.0024736067,0.00036445135,0.000235682,0.000009200559,0.0000072662206,0.011773432],"genre_scores_gemma":[0.9697494,0.027768284,0.00035117156,0.001977652,0.00006714407,0.000005451772,0.000004823725,0.0000064500045,0.000069655645],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99704677,0.0004492052,0.0016072845,0.00039592394,0.00026416668,0.00023663715],"domain_scores_gemma":[0.99770856,0.00026571777,0.0007352585,0.0010438716,0.00019295859,0.000053638105],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0038616417,0.00013817851,0.0006888384,0.00024360474,0.000053049665,0.000017037313,0.00096960564,0.00011529569,0.0003935746],"category_scores_gemma":[0.0005986721,0.000077075616,0.0003678131,0.00066650065,0.00019006702,0.000084772335,0.000039659037,0.00017500446,0.00009045071],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003139928,0.00015731742,0.0017496754,0.000008671618,0.000004890095,0.0000026648438,0.000015968344,0.000008553914,0.004108549,0.0009004157,0.04031732,0.9526946],"study_design_scores_gemma":[0.00082511344,0.002106372,0.3443612,0.0007368277,0.000017824384,0.00007709974,0.000009286498,0.000042498974,0.000110168985,0.6278646,0.023632847,0.00021619837],"about_ca_topic_score_codex":0.000030051842,"about_ca_topic_score_gemma":0.000018908837,"teacher_disagreement_score":0.95247835,"about_ca_system_score_codex":0.00002709913,"about_ca_system_score_gemma":0.00003433483,"threshold_uncertainty_score":0.43093657},"labels":[],"label_agreement":null},{"id":"W1970449261","doi":"10.3758/mc.36.6.1066","title":"Different developmental patterns of simple deductive and probabilistic inferential reasoning","year":2008,"lang":"en","type":"article","venue":"Memory & Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":42,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan; Université du Québec à Montréal","funders":"","keywords":"Probabilistic logic; Psychology; Categorical variable; Counterexample; Inference; Cognitive psychology; Developmental psychology; Artificial intelligence; Statistics; Mathematics; Computer science","score_opus":0.12609961536672115,"score_gpt":0.3491721473266582,"score_spread":0.22307253195993704,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1970449261","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99736136,0.000011894495,0.0012115228,0.000019437222,0.00017923959,0.00017364729,0.000051884293,0.000021177162,0.000969862],"genre_scores_gemma":[0.9993713,0.000010670933,0.00041164985,0.00002888087,0.00004434502,0.00001354032,0.000031860873,0.000008986883,0.000078761776],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99842924,0.00008985254,0.0005130648,0.00037080218,0.0004417429,0.00015527527],"domain_scores_gemma":[0.99893713,0.00037728102,0.00022677137,0.00015482034,0.00022381662,0.00008015449],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037028713,0.00013198507,0.00026713847,0.00016993337,0.00018019337,0.00006255298,0.00015499178,0.000057917307,0.0004776704],"category_scores_gemma":[0.00085191533,0.00010421399,0.00006280774,0.00012571283,0.00012157926,0.00023933551,0.00012847908,0.000094653675,0.000052276977],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021135027,0.00051237387,0.14251442,0.000019074721,0.00003479476,0.000039018767,0.0032701283,0.00005475736,0.0060638636,0.00014922634,0.00045573676,0.8466753],"study_design_scores_gemma":[0.0013515139,0.00025111993,0.9130687,0.00013642023,0.000077098455,0.00026049468,0.003853288,0.00065374264,0.01456669,0.065048255,0.0002825877,0.00045010005],"about_ca_topic_score_codex":0.000031894284,"about_ca_topic_score_gemma":0.00007374601,"teacher_disagreement_score":0.84622514,"about_ca_system_score_codex":0.000046900193,"about_ca_system_score_gemma":0.00006025727,"threshold_uncertainty_score":0.5230156},"labels":[],"label_agreement":null},{"id":"W1971209104","doi":"10.3758/cabn.6.4.277","title":"Affective guidance in the Iowa gambling task","year":2006,"lang":"en","type":"article","venue":"Cognitive Affective & Behavioral Neuroscience","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":52,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; University of Victoria","funders":"","keywords":"Iowa gambling task; Task (project management); Psychology; Preference; Set (abstract data type); Affect (linguistics); Cognition; Cognitive psychology; Social psychology; Applied psychology; Computer science; Engineering; Psychiatry","score_opus":0.1733290497462471,"score_gpt":0.4386190688870892,"score_spread":0.26529001914084205,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1971209104","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98919684,0.00013465693,0.004339989,0.00019885866,0.0011771275,0.0010727727,0.00011025998,0.0000846893,0.003684804],"genre_scores_gemma":[0.99843615,0.000004911388,0.000112817506,0.0008506162,0.00015662081,0.00017745908,0.000005681873,0.00003280692,0.00022292866],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9928905,0.0012976521,0.0009520921,0.0019663542,0.0019592068,0.00093418796],"domain_scores_gemma":[0.9936856,0.0040857005,0.00054519577,0.00084621203,0.0006903028,0.00014697673],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.004952223,0.0005049458,0.00060225494,0.0007335684,0.0007173713,0.0011624377,0.0021317098,0.00015709856,0.00005589896],"category_scores_gemma":[0.0039959503,0.0003494706,0.00033028805,0.003227382,0.0011897497,0.0014342548,0.0004233947,0.0007447972,0.00037571357],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023709514,0.0024678188,0.345088,0.0000037802113,0.0000021454025,0.0008802449,0.001766543,0.0005107249,0.04672001,0.0010383137,0.0018056317,0.5994797],"study_design_scores_gemma":[0.001012855,0.00081488583,0.95915306,0.00010117782,0.000044655557,0.000117945,0.0019404532,0.00088231085,0.0045263576,0.029442227,0.0013159714,0.0006480831],"about_ca_topic_score_codex":0.00055166316,"about_ca_topic_score_gemma":0.0006704956,"teacher_disagreement_score":0.61406505,"about_ca_system_score_codex":0.0001909392,"about_ca_system_score_gemma":0.00015631858,"threshold_uncertainty_score":0.99989575},"labels":[],"label_agreement":null},{"id":"W1973674528","doi":"10.1016/j.jebo.2013.08.001","title":"Human economic choice as costly information processing","year":2013,"lang":"en","type":"article","venue":"Journal of Economic Behavior & Organization","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"University of Toronto; University of Minnesota; National Science Foundation","keywords":"Stylized fact; Ambiguity; Certainty; Computer science; Task (project management); Artificial neural network; Value (mathematics); Process (computing); Cognitive psychology; Economics; Artificial intelligence; Psychology; Machine learning","score_opus":0.06033256151471374,"score_gpt":0.3782801113689977,"score_spread":0.317947549854284,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1973674528","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.996525,0.000014116725,0.0004254525,0.00045805253,0.001331375,0.0002651601,0.000008912114,0.000031105053,0.0009408596],"genre_scores_gemma":[0.9986231,0.0000072824246,0.00044173747,0.00022222921,0.00037215336,0.0000060554316,0.000018950082,0.000032605472,0.0002759371],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99664086,0.00007361516,0.0024051082,0.0002614464,0.00034401048,0.0002749671],"domain_scores_gemma":[0.9962288,0.00013894326,0.0020856848,0.00040599625,0.00091510575,0.0002254351],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0014562206,0.00022409538,0.0004917,0.00055766257,0.00032093388,0.0018734514,0.0009358827,0.00018406159,0.007136251],"category_scores_gemma":[0.0005052373,0.00017633247,0.00014908671,0.0001954819,0.000070366514,0.0072588534,0.00013223925,0.0002619314,0.009955808],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017641845,0.00022509824,0.25887695,0.000007043612,0.000027068743,0.000007361263,0.001418963,0.0045600333,0.007954547,0.0005917875,0.020864962,0.70544857],"study_design_scores_gemma":[0.0042635794,0.0009888515,0.87168473,0.00013889489,0.00043417444,0.0012411495,0.004202577,0.0026039218,0.0185123,0.038791202,0.055418175,0.0017204395],"about_ca_topic_score_codex":0.00016967473,"about_ca_topic_score_gemma":0.000029519393,"teacher_disagreement_score":0.7037281,"about_ca_system_score_codex":0.0008313965,"about_ca_system_score_gemma":0.00035373948,"threshold_uncertainty_score":0.9991627},"labels":[],"label_agreement":null},{"id":"W1974084640","doi":"10.1016/j.jcps.2014.09.003","title":"The preference‐signaling effect of search","year":2014,"lang":"en","type":"article","venue":"Journal of Consumer Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta; University of Northern British Columbia","funders":"","keywords":"Preference; Set (abstract data type); Choice set; Sight; Normative; Contrast (vision); Consumer choice; Economics; Psychology; Microeconomics; Computer science; Artificial intelligence; Econometrics; Epistemology","score_opus":0.20292431059418853,"score_gpt":0.4811094195206591,"score_spread":0.2781851089264706,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1974084640","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9930182,0.0004482465,0.0018725491,0.00068900746,0.0016126022,0.000059910257,0.0000015497723,0.0000032951134,0.0022946445],"genre_scores_gemma":[0.99912673,0.00007829688,0.00044759622,0.00012555059,0.00009900426,8.420969e-7,8.411865e-8,0.0000070071906,0.000114903574],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9966692,0.0010294503,0.0012341508,0.00018960927,0.00066411746,0.00021352664],"domain_scores_gemma":[0.9893093,0.008610479,0.0008944005,0.0005352988,0.00054677087,0.00010371633],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.013689598,0.00010598717,0.0004904148,0.00027183202,0.00011990043,0.000110452704,0.0012157607,0.000102679056,0.00020412165],"category_scores_gemma":[0.0031648655,0.000051799652,0.00023369667,0.00025841774,0.00030791713,0.00012273912,0.00006689175,0.0003657554,0.00017357498],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003759819,0.000033624827,0.032116443,0.0000013578799,0.000027502421,0.000004901048,0.00008580751,0.000031696036,0.002633243,0.00021338818,0.0057308385,0.95874524],"study_design_scores_gemma":[0.00692245,0.008027463,0.09004839,0.00022407949,0.00024792,0.0014443793,0.00042101907,0.0006360678,0.0184686,0.28335026,0.58965147,0.0005579143],"about_ca_topic_score_codex":0.0000029832618,"about_ca_topic_score_gemma":0.000004040478,"teacher_disagreement_score":0.9581873,"about_ca_system_score_codex":0.0000126065515,"about_ca_system_score_gemma":0.000061546656,"threshold_uncertainty_score":0.47445688},"labels":[],"label_agreement":null},{"id":"W1975122737","doi":"10.1037/xlm0000092","title":"Deductive updating is not Bayesian.","year":2015,"lang":"en","type":"article","venue":"Journal of Experimental Psychology Learning Memory and Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Probabilistic logic; Counterexample; Deductive reasoning; Probabilistic argumentation; Frequentist probability; Inference; Frequentist inference; Mathematics; Statistical inference; Bayesian probability; Bayesian inference; Psychology; Statistics; Computer science; Artificial intelligence; Discrete mathematics","score_opus":0.20887245434336033,"score_gpt":0.4685886036484083,"score_spread":0.259716149305048,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1975122737","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98262745,0.00038532735,0.0011019193,0.00069465546,0.0009172876,0.000049693066,0.0000017526803,0.000010350313,0.014211554],"genre_scores_gemma":[0.996565,0.0000137921115,0.0016848162,0.0013021466,0.00021133017,0.0000016850371,0.0000012954911,0.000010203283,0.00020975989],"study_design_codex":"design_other","study_design_gemma":"qualitative","domain_scores_codex":[0.99806154,0.0003171489,0.0007208695,0.0002860055,0.00046034055,0.00015412545],"domain_scores_gemma":[0.9982757,0.0002845687,0.00076270057,0.00013279017,0.0003551236,0.00018910466],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024523616,0.00012430473,0.0002981766,0.00027554418,0.00016102406,0.00014303545,0.00022187649,0.00010980787,0.0004215203],"category_scores_gemma":[0.00082895893,0.00009954046,0.00010619956,0.00016861192,0.00015418218,0.0005786183,0.00006068328,0.00040625854,0.00012990001],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022927022,0.00069781806,0.0046586054,0.000001807286,0.00008027502,0.00019871823,0.011257239,0.00014435087,0.09535523,0.00013278697,0.017642079,0.8675384],"study_design_scores_gemma":[0.019713067,0.01377953,0.015321803,0.0004117435,0.0003205284,0.013471004,0.335604,0.0015782866,0.31596917,0.23268218,0.04931015,0.0018385331],"about_ca_topic_score_codex":0.0000014559295,"about_ca_topic_score_gemma":2.5117157e-7,"teacher_disagreement_score":0.8656999,"about_ca_system_score_codex":0.00003518719,"about_ca_system_score_gemma":0.000042943782,"threshold_uncertainty_score":0.4615352},"labels":[],"label_agreement":null},{"id":"W1975384768","doi":"10.1126/science.1160769","title":"Automatic Mental Associations Predict Future Choices of Undecided Decision-Makers","year":2008,"lang":"en","type":"article","venue":"Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":232,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Unconscious mind; Categorization; Psychology; Task (project management); Social psychology; Control (management); Cognitive psychology; Information processing; Computer science; Artificial intelligence","score_opus":0.08991233316250512,"score_gpt":0.3960210399360344,"score_spread":0.30610870677352925,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1975384768","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9941259,0.000118954245,0.0004037498,0.00034979687,0.00225873,0.00017859321,0.0000762809,0.0000618998,0.0024260953],"genre_scores_gemma":[0.9915876,0.00003343286,0.007826034,0.00012224227,0.000105600135,0.0000048599245,0.0000023066123,0.000008256243,0.00030971042],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99485826,0.00006912823,0.0010288927,0.0006971381,0.0029495696,0.00039702328],"domain_scores_gemma":[0.9960152,0.0016749966,0.00063807657,0.000903178,0.00052997103,0.0002385815],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0038283344,0.00016601461,0.00039216108,0.0006547268,0.0008753318,0.00025092094,0.0021741202,0.00009128087,0.0006531052],"category_scores_gemma":[0.005018376,0.00012117101,0.00018119696,0.0028458962,0.0010943806,0.0012514491,0.00032411533,0.00014994627,0.00042557268],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019512552,0.00026572845,0.115573496,0.0000016057967,0.000011060537,0.00001737515,0.001972635,0.00035103745,0.0017363422,0.00058094534,0.014768388,0.86470187],"study_design_scores_gemma":[0.0007966713,0.00021059283,0.8909042,0.00006419375,0.000021175703,0.000088907,0.0026251297,0.015819713,0.0017699972,0.06962935,0.017650727,0.0004193698],"about_ca_topic_score_codex":0.000024069177,"about_ca_topic_score_gemma":0.000052449483,"teacher_disagreement_score":0.8642825,"about_ca_system_score_codex":0.00020453606,"about_ca_system_score_gemma":0.0006519882,"threshold_uncertainty_score":0.7151044},"labels":[],"label_agreement":null},{"id":"W1975900334","doi":"10.1098/rsif.2013.0969","title":"Optimal indolence: a normative microscopic approach to work and leisure","year":2013,"lang":"en","type":"article","venue":"Journal of The Royal Society Interface","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Canadian Institutes of Health Research","keywords":"Normative; Lever; Work (physics); Normative model of decision-making; Function (biology); Leisure time; Control (management); Economics; Psychology; Econometrics; Microeconomics; Social psychology; Cognitive psychology; Mathematical economics; Computer science; Artificial intelligence; Epistemology; Medicine; Physics; Physical medicine and rehabilitation; Biology; Physical activity; Thermodynamics","score_opus":0.04766132528593044,"score_gpt":0.3407803298570015,"score_spread":0.2931190045710711,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1975900334","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96388143,0.00029947434,0.03261067,0.0021377678,0.0005827109,0.000166215,0.0000039054476,0.0000050321514,0.00031278428],"genre_scores_gemma":[0.9812529,0.000007921474,0.017045973,0.00029247272,0.00008429028,0.0000029232874,3.7465966e-8,0.000008359052,0.0013051],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.9981519,0.00011821284,0.00072254834,0.00020486952,0.00059116556,0.0002113299],"domain_scores_gemma":[0.9981998,0.00034874096,0.0005791575,0.0003114206,0.00039596335,0.00016492262],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015093964,0.00014722273,0.0003605922,0.000045006553,0.0001818117,0.0006103941,0.0012007345,0.00010516097,0.00012364653],"category_scores_gemma":[0.00039776828,0.000077567856,0.00033742076,0.00033012038,0.00013564921,0.00029516252,0.00046610742,0.0004918297,0.0001385699],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014072529,0.0003664086,0.041955847,0.000012144941,0.0001416194,0.00000161429,0.025347218,0.1862652,0.0007622666,0.00002138847,0.5592824,0.18570316],"study_design_scores_gemma":[0.0076784277,0.0034266557,0.4877331,0.0028377085,0.0004949454,0.0006329147,0.14922816,0.12298225,0.02263062,0.031826485,0.16719285,0.0033358957],"about_ca_topic_score_codex":0.000014426591,"about_ca_topic_score_gemma":5.240671e-7,"teacher_disagreement_score":0.44577724,"about_ca_system_score_codex":0.00009220956,"about_ca_system_score_gemma":0.00005878447,"threshold_uncertainty_score":0.58860445},"labels":[],"label_agreement":null},{"id":"W1977123702","doi":"10.1037/a0017188","title":"Decision-tree models of categorization response times, choice proportions, and typicality judgments.","year":2009,"lang":"en","type":"article","venue":"Psychological Review","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Categorization; Decision tree; Psychology; Decision tree model; Tree (set theory); Statistics; Decision tree learning; Cognitive psychology; Artificial intelligence; Social psychology; Mathematics; Machine learning; Computer science","score_opus":0.23097762735129052,"score_gpt":0.4898133821524445,"score_spread":0.258835754801154,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1977123702","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90681857,0.040468745,0.029328033,0.009632731,0.0005475485,0.001608038,0.00016766437,0.0001342221,0.011294476],"genre_scores_gemma":[0.97639,0.011815006,0.0080862185,0.0031899293,0.00003231176,0.00002116083,0.000018704959,0.000008291826,0.00043836032],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99642575,0.000441997,0.0014674967,0.00072352175,0.0007309292,0.000210291],"domain_scores_gemma":[0.9959419,0.0021279824,0.0005433076,0.0008991079,0.00030203955,0.00018570111],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004966407,0.00018032276,0.00064901076,0.00012552476,0.000095390234,0.00008998807,0.00061941217,0.0001409648,0.0023073035],"category_scores_gemma":[0.01226414,0.00011027951,0.00016929334,0.00073834375,0.00012493737,0.00029818882,0.00009076449,0.00017581666,0.00026841424],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015558765,0.0002758896,0.00030669072,0.000008406796,0.000002147597,0.0000036660936,0.000006596984,0.000012147179,0.000047689387,0.0010675396,0.030393407,0.9677202],"study_design_scores_gemma":[0.00041619054,0.00061718037,0.11508431,0.0007538207,0.00004890049,0.000034972465,0.000010470111,0.00050242816,0.000010409328,0.74394274,0.138294,0.00028455324],"about_ca_topic_score_codex":0.0000024828723,"about_ca_topic_score_gemma":0.0000016352219,"teacher_disagreement_score":0.96743566,"about_ca_system_score_codex":0.00003017618,"about_ca_system_score_gemma":0.0000305898,"threshold_uncertainty_score":0.9986047},"labels":[],"label_agreement":null},{"id":"W1979132471","doi":"10.4018/ijabe.2014040103","title":"B is for Bias","year":2014,"lang":"en","type":"article","venue":"International Journal of Applied Behavioral Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bishop's University","funders":"","keywords":"Heuristics; Rationality; Order (exchange); Bounded rationality; Rational agent; Behavioral economics; Economics; Ecological rationality; Rational expectations; Positive economics; Psychology; Computer science; Microeconomics; Epistemology; Neoclassical economics; Econometrics; Finance","score_opus":0.25516198297692766,"score_gpt":0.4432321040956254,"score_spread":0.18807012111869775,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979132471","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98579353,0.000008152218,0.0064038397,0.0012008031,0.003606646,0.00012642787,0.00008549966,0.000011755229,0.0027633319],"genre_scores_gemma":[0.9867463,0.00001740426,0.01104023,0.0011124031,0.0008634047,0.0000075092653,0.0000064910637,0.000026823333,0.00017940659],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9970666,0.000024244391,0.0017845184,0.00036583756,0.00053514,0.00022364089],"domain_scores_gemma":[0.9959967,0.0007933667,0.0016562943,0.00038572645,0.0009878575,0.00018004126],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028764273,0.00019684102,0.0005117574,0.00056170876,0.0000790532,0.0006452667,0.002023196,0.00013715004,0.000401138],"category_scores_gemma":[0.00031520598,0.00016384046,0.00049573625,0.00009711642,0.000089979454,0.0004547596,0.00015491412,0.00019848158,0.00024387376],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041226705,0.00021800993,0.0021995613,6.270156e-7,0.000037209968,0.000003349032,0.00028777774,0.0012868448,0.0003067678,0.007858447,0.0093013635,0.9780878],"study_design_scores_gemma":[0.002235105,0.00039163182,0.0014379922,0.000017396454,0.00007083064,0.00009533464,0.00049716386,0.003151254,0.0040560714,0.46566656,0.52200335,0.00037734376],"about_ca_topic_score_codex":0.0000071502936,"about_ca_topic_score_gemma":0.00001356994,"teacher_disagreement_score":0.9777104,"about_ca_system_score_codex":0.00019176693,"about_ca_system_score_gemma":0.0001371845,"threshold_uncertainty_score":0.668122},"labels":[],"label_agreement":null},{"id":"W1979248804","doi":"10.1002/bdm.626","title":"How do we evaluate future gambles? Experimental evidence on path dependency in risky intertemporal choice","year":2008,"lang":"en","type":"article","venue":"Journal of Behavioral Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Management and Science University; University of Waterloo","keywords":"Lottery; Discounting; Econometrics; Path (computing); Economics; Time preference; Intertemporal choice; Choice set; Prospect theory; Expected utility hypothesis; Value (mathematics); Mathematical economics; Computer science; Mathematics; Microeconomics; Statistics","score_opus":0.26264413727393615,"score_gpt":0.47354757966716654,"score_spread":0.2109034423932304,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979248804","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.989277,0.004257583,0.001197477,0.0006730829,0.0041893143,0.00028939484,0.000012680455,0.000026334152,0.000077123936],"genre_scores_gemma":[0.9888704,0.00056470354,0.009480841,0.00013440373,0.00070658355,0.000008893208,4.683652e-7,0.000055615,0.00017811847],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9904598,0.0006162848,0.0030439363,0.0010220214,0.0041865753,0.0006713739],"domain_scores_gemma":[0.9918974,0.0028928923,0.0026538896,0.0011973243,0.0009667092,0.00039177446],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0056484495,0.0005943064,0.001312342,0.0019670082,0.00037503205,0.0011502275,0.0026136779,0.00038075537,0.0006007361],"category_scores_gemma":[0.0025604223,0.00042245258,0.0008537914,0.0013347969,0.0001726675,0.0030705605,0.00048325458,0.0013543393,0.00017704329],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011424583,0.0008946142,0.099686265,0.0000023628033,0.000008217731,0.0019327522,0.0014277005,0.00037974046,0.0015522212,0.000021911485,0.0050850455,0.88786674],"study_design_scores_gemma":[0.018112777,0.018466642,0.68566614,0.023379674,0.00047658844,0.015717603,0.043308165,0.0049662767,0.007415326,0.12229724,0.054299235,0.0058943345],"about_ca_topic_score_codex":0.00002519598,"about_ca_topic_score_gemma":0.00007107101,"teacher_disagreement_score":0.8819724,"about_ca_system_score_codex":0.000668756,"about_ca_system_score_gemma":0.00034816423,"threshold_uncertainty_score":0.9998867},"labels":[],"label_agreement":null},{"id":"W1979776966","doi":"10.3758/mc.38.6.667","title":"Probability matching and strategy availability","year":2010,"lang":"en","type":"article","venue":"Memory & Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":90,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Matching (statistics); Deliberation; Psychology; Cognitive psychology; Social psychology; Statistics; Mathematics","score_opus":0.16883872913670897,"score_gpt":0.3793368715094194,"score_spread":0.21049814237271045,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979776966","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9852032,0.000009065899,0.0002452321,0.00020904052,0.00049997243,0.00023182192,0.000027021648,0.00006569499,0.013508945],"genre_scores_gemma":[0.9981201,0.0000017003676,0.0014082805,0.00011744007,0.00008336981,0.000012556183,0.0000070981664,0.000008222514,0.00024122541],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99805915,0.00013116485,0.00055749353,0.00061994133,0.00044221632,0.00019003155],"domain_scores_gemma":[0.9981207,0.00073490606,0.0001767797,0.0005504958,0.00028769672,0.00012942012],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0037864405,0.0001334411,0.0002232179,0.000106423,0.00021991643,0.0004402385,0.00026571035,0.00012300927,0.0015889494],"category_scores_gemma":[0.0016119136,0.00010520668,0.000073839365,0.00019201612,0.0002124699,0.00053968234,0.00011160743,0.00033021625,0.0006603056],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003680579,0.00012404742,0.00352783,0.0000048722172,0.00000240263,0.0000044187836,0.00017638502,0.000013873747,0.013564576,0.00014766863,0.00040712513,0.98199],"study_design_scores_gemma":[0.00032139427,0.00007126472,0.083262525,0.000010784244,0.00001980718,0.000036312533,0.00050888926,0.00024517463,0.0019948874,0.9112814,0.0020334548,0.00021408903],"about_ca_topic_score_codex":0.000040143925,"about_ca_topic_score_gemma":0.00038175736,"teacher_disagreement_score":0.9817759,"about_ca_system_score_codex":0.000017866938,"about_ca_system_score_gemma":0.000059977585,"threshold_uncertainty_score":0.9993237},"labels":[],"label_agreement":null},{"id":"W1980816362","doi":"10.1111/j.1747-9991.2008.00178.x","title":"Rationality Disputes – Psychology and Epistemology","year":2008,"lang":"en","type":"article","venue":"Philosophy Compass","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":39,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Rationality; Epistemology; Ecological rationality; Psychology; Bridge (graph theory); Convergence (economics); Sociology; Philosophy; Economics","score_opus":0.32920415922335594,"score_gpt":0.44124108997185263,"score_spread":0.11203693074849669,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1980816362","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9528123,0.00014097283,0.0023358068,0.015974242,0.0007757475,0.00010522344,0.000025111201,0.000047827238,0.027782744],"genre_scores_gemma":[0.99634904,0.00003401199,0.0016576208,0.0016007705,0.00022609827,0.000008708578,0.0000058790224,0.000007969105,0.000109929635],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9980402,0.0001952602,0.0006082958,0.000576034,0.00038758604,0.0001926395],"domain_scores_gemma":[0.9978004,0.0011067907,0.00020401017,0.0005943828,0.00016194326,0.00013246594],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008552463,0.00014087971,0.0003773191,0.00017859139,0.00027640743,0.00006628865,0.0005185149,0.00009232022,0.00034042087],"category_scores_gemma":[0.00047973293,0.000110047855,0.00009319337,0.00024066173,0.00046210934,0.0002097774,0.00015443692,0.00014171554,0.00066283264],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029250156,0.00083731214,0.34254766,0.000007479792,0.000053020845,0.0002904904,0.00069678115,0.00013740301,0.0004560243,0.18819632,0.06965477,0.39683026],"study_design_scores_gemma":[0.00031569268,0.00006467746,0.14638683,0.0000025682164,0.000004091124,0.00024343889,0.000006372761,0.00044056808,0.000013370198,0.82043016,0.03196414,0.00012810301],"about_ca_topic_score_codex":0.00001128372,"about_ca_topic_score_gemma":0.00000728739,"teacher_disagreement_score":0.63223386,"about_ca_system_score_codex":0.000016576918,"about_ca_system_score_gemma":0.000033445966,"threshold_uncertainty_score":0.85195935},"labels":[],"label_agreement":null},{"id":"W1981262337","doi":"10.1007/s00355-006-0188-x","title":"Variable-population extensions of social aggregation theorems","year":2006,"lang":"en","type":"article","venue":"Social Choice and Welfare","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Université de Montréal","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Variable (mathematics); Extension (predicate logic); Population; Utilitarianism; Social choice theory; Mathematical economics; Contrast (vision); Econometrics; Economics; Social policy; Public finance; Ex-ante; Random variable; Mathematics; Computer science; Statistics; Sociology; Political science; Demography; Artificial intelligence; Law","score_opus":0.04997353019053637,"score_gpt":0.3574628823402215,"score_spread":0.30748935214968515,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1981262337","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9910801,0.000042596635,0.00035956892,0.0015423876,0.0002966073,0.00009333769,0.00005874922,0.000029476068,0.006497194],"genre_scores_gemma":[0.99880457,0.000001360753,0.00031924035,0.000063027685,0.00045585036,0.0000037331733,0.000039586746,0.000009859175,0.00030274558],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99847275,0.00009592146,0.0005277115,0.00029114162,0.00045458062,0.00015790707],"domain_scores_gemma":[0.9989326,0.00029457323,0.00033914828,0.00014016953,0.00026188703,0.000031602474],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00077202386,0.00010844856,0.00026983093,0.00012926741,0.0008012204,0.00014435292,0.00018639749,0.00016049322,0.00028244383],"category_scores_gemma":[0.0003857551,0.00008939208,0.00010443116,0.00040816542,0.00010379689,0.0002771819,0.00006515686,0.00009754002,0.000018707113],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031850774,0.0001271473,0.059513792,0.0000068504232,0.000009362599,0.0000015034052,0.0006998561,0.00006769986,0.000424955,0.3147822,0.0058620996,0.6184727],"study_design_scores_gemma":[0.00028013453,0.000020482245,0.50060225,0.000007220319,0.00002412976,0.0000013988533,0.0007360927,0.00013289068,0.000021348318,0.4732308,0.024814311,0.00012892178],"about_ca_topic_score_codex":0.00089116616,"about_ca_topic_score_gemma":0.00019776492,"teacher_disagreement_score":0.6183438,"about_ca_system_score_codex":0.000030534764,"about_ca_system_score_gemma":0.000021127227,"threshold_uncertainty_score":0.61624205},"labels":[],"label_agreement":null},{"id":"W1981308105","doi":"10.1016/j.socscimed.2012.11.020","title":"Theory-informed design of values clarification methods: A cognitive psychological perspective on patient health-related decision making","year":2012,"lang":"en","type":"review","venue":"Social Science & Medicine","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":65,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"PsycINFO; Management science; Decision theory; Process (computing); Decision field theory; Psychology; Selection (genetic algorithm); Empirical research; Computer science; MEDLINE; Decision engineering; Decision support system; Artificial intelligence; Business decision mapping; Epistemology; Mathematics","score_opus":0.44008208007943994,"score_gpt":0.6067197964989756,"score_spread":0.16663771641953562,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1981308105","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0009106837,0.9111575,0.07425744,0.00041659732,0.0034670627,0.0027911253,0.00008989774,0.00009251967,0.0068171658],"genre_scores_gemma":[0.09031076,0.8894165,0.017149106,0.0015718272,0.0009961063,0.00026584783,0.000035002646,0.00011660776,0.00013821051],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9878976,0.0034067342,0.003294694,0.0014862805,0.0031089038,0.000805831],"domain_scores_gemma":[0.97368026,0.019576257,0.0042389864,0.0007504106,0.001409902,0.0003442062],"candidate_categories":["metaresearch","metaepi_narrow","sts"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.04205411,0.000563747,0.0029192828,0.0015435589,0.0009818636,0.00012091496,0.0019874482,0.00059410447,0.0005975534],"category_scores_gemma":[0.038527694,0.00032392496,0.0005340136,0.004482098,0.0034152672,0.00047100152,0.00022839084,0.0009405374,0.00020380555],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012092339,0.0001789569,0.0000026914502,0.00003399547,0.000018545743,0.0000024190108,0.011974954,0.0000017022732,0.0000011038567,0.0048236917,0.00061180023,0.98222923],"study_design_scores_gemma":[0.0011189975,0.0035764812,0.00032355185,0.020310614,0.0009128468,0.00008902092,0.032587565,0.000081241706,0.000004386716,0.83874875,0.10112314,0.0011234005],"about_ca_topic_score_codex":0.000020163496,"about_ca_topic_score_gemma":0.0000016038445,"teacher_disagreement_score":0.9811058,"about_ca_system_score_codex":0.0014462664,"about_ca_system_score_gemma":0.0011521056,"threshold_uncertainty_score":0.99992126},"labels":[],"label_agreement":null},{"id":"W1981901481","doi":"10.1037/a0027855","title":"Beyond gains and losses: The effect of need on risky choice in framed decisions.","year":2012,"lang":"en","type":"article","venue":"Journal of Personality and Social Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":70,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada; Ontario Problem Gambling Research Centre","keywords":"Framing (construction); Framing effect; Normative; Psychology; Perception; Risk perception; Social psychology; Prospect theory; Cognitive psychology; Economics; Microeconomics; Epistemology","score_opus":0.16571237882096101,"score_gpt":0.48438847261860085,"score_spread":0.31867609379763984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1981901481","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9943354,0.00044297817,0.00006439806,0.00362732,0.0006937545,0.000079478414,0.000011817536,0.0000017498853,0.00074311596],"genre_scores_gemma":[0.99847966,0.000063086074,0.00009689709,0.0010063867,0.00032368748,0.0000010580966,2.750042e-7,0.0000054064426,0.000023524739],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99752903,0.0007893523,0.00079058437,0.00018109559,0.00049300364,0.00021691681],"domain_scores_gemma":[0.99218684,0.0067825066,0.0006379464,0.00017301428,0.00011521996,0.000104495135],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008335517,0.00012277384,0.00055056403,0.00023269994,0.00017600985,0.00006939262,0.0003621945,0.00020357528,0.000089298286],"category_scores_gemma":[0.003138994,0.00006916534,0.00017357014,0.000262989,0.00042644638,0.00022738724,0.000057272882,0.00048790785,0.000009489987],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008307466,0.00023079326,0.6202214,0.0000036359504,0.000030443203,0.000007234818,0.005668906,0.0000046233545,0.00017004488,0.0005840701,0.0043949652,0.36785316],"study_design_scores_gemma":[0.0014830404,0.0006574471,0.96550757,0.000023284869,0.000034221892,0.00006272295,0.0016868381,0.000010798905,0.000019471985,0.024526905,0.0058976486,0.000090058995],"about_ca_topic_score_codex":0.000043888358,"about_ca_topic_score_gemma":0.00006527732,"teacher_disagreement_score":0.3677631,"about_ca_system_score_codex":0.0000273236,"about_ca_system_score_gemma":0.000026746951,"threshold_uncertainty_score":0.37578958},"labels":[],"label_agreement":null},{"id":"W1982834043","doi":"10.1177/154193121005400412","title":"Mapping Biases to the Components of Rationalistic and Naturalistic Decision Making","year":2010,"lang":"en","type":"article","venue":"Proceedings of the Human Factors and Ergonomics Society Annual Meeting","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Hindsight bias; Heuristics; Representativeness heuristic; Overconfidence effect; Rule of thumb; Framing (construction); Debiasing; Computer science; Confirmation bias; Cognitive bias; Framing effect; Anchoring; Psychology; Cognitive psychology; Management science; Social psychology; Cognition; Economics","score_opus":0.0847403192816197,"score_gpt":0.34436558826331587,"score_spread":0.2596252689816962,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1982834043","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9989289,0.000043484437,0.000030506946,0.00018442994,0.0004326963,0.0001846573,0.00007229792,0.00001097731,0.00011202418],"genre_scores_gemma":[0.9967994,0.0000075083544,0.0029411253,0.00011584316,0.00008841371,0.0000028823388,0.0000014565849,0.000012832887,0.000030556614],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9982019,0.000013353087,0.0007781496,0.00038557686,0.00041981155,0.00020121227],"domain_scores_gemma":[0.9966312,0.0019830172,0.0007145802,0.00019031754,0.00040452072,0.00007633576],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020514468,0.00018317922,0.00035045567,0.00011028137,0.00076947984,0.00032490797,0.00078911573,0.00010559024,0.000010727561],"category_scores_gemma":[0.0036259575,0.000102553946,0.00019070157,0.00032771926,0.00030850497,0.00029459747,0.0007347499,0.00029424514,0.0000012763038],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021909308,0.00019614969,0.7085888,0.000115637085,0.000121765544,2.9416066e-7,0.055917073,0.0008427886,0.13643736,0.014406084,0.009812132,0.07334284],"study_design_scores_gemma":[0.0005180945,0.00012729903,0.88152605,0.0008668755,0.00007582481,0.000016802902,0.03467628,0.0059331967,0.0026085498,0.06912528,0.0039641373,0.0005615842],"about_ca_topic_score_codex":0.00006608487,"about_ca_topic_score_gemma":0.000036994214,"teacher_disagreement_score":0.17293729,"about_ca_system_score_codex":0.000025603002,"about_ca_system_score_gemma":0.000018068293,"threshold_uncertainty_score":0.5918295},"labels":[],"label_agreement":null},{"id":"W1983201084","doi":"10.5539/res.v6n1p34","title":"Pre-Counterfactuals and Anticipated Emotions: Factors Affecting the First Bid in Name-Your-Own-Price Auctions","year":2014,"lang":"en","type":"article","venue":"Review of European Studies","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Ajou University","keywords":"Counterfactual thinking; Counterfactual conditional; Disappointment; Regret; Common value auction; Economics; Psychology; Unique bid auction; Microeconomics; Positive economics; Social psychology; Mathematics; Statistics","score_opus":0.2454847705496675,"score_gpt":0.44836264643387225,"score_spread":0.20287787588420475,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1983201084","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9514683,0.04527625,0.000102359685,0.00059468014,0.00031766857,0.00027569005,0.000008929302,0.000024367944,0.0019317493],"genre_scores_gemma":[0.9584968,0.04096761,0.00010610139,0.00021956852,0.00004637665,0.0000031811037,7.683351e-7,0.000014336916,0.00014526585],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9974114,0.00065690436,0.0010184781,0.00038442053,0.00033740356,0.00019141388],"domain_scores_gemma":[0.99570775,0.002882574,0.00054754876,0.000566211,0.000255408,0.000040497678],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.006432944,0.00018122174,0.0006361088,0.00015672343,0.00031424506,0.00010272642,0.00046441727,0.000019288958,0.00004921561],"category_scores_gemma":[0.011437296,0.00009704748,0.00012504648,0.000545797,0.00020986411,0.00021202378,0.00035355767,0.0001505266,0.00013025048],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017277505,0.00029446874,0.12735224,0.0014475943,0.00017958584,0.000010132477,0.017083932,0.00031250148,0.000066276094,0.00021139378,0.020390961,0.8326336],"study_design_scores_gemma":[0.00035839615,0.00023362109,0.75780576,0.01127155,0.0001653558,0.000022838378,0.005483469,0.00019829416,0.000033635046,0.0012540037,0.22276497,0.00040807945],"about_ca_topic_score_codex":0.000018217774,"about_ca_topic_score_gemma":0.00003517633,"teacher_disagreement_score":0.83222556,"about_ca_system_score_codex":0.000027479913,"about_ca_system_score_gemma":0.000010255085,"threshold_uncertainty_score":0.99688977},"labels":[],"label_agreement":null},{"id":"W1984452204","doi":"10.1016/j.jcps.2013.04.007","title":"What should we expect from a dual‐process theory of preference construction in choice?","year":2013,"lang":"en","type":"article","venue":"Journal of Consumer Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Preference; Dual (grammatical number); Process (computing); Dual process theory (moral psychology); Criticism; Associative property; Elaboration; Psychology; Cognition; Revealed preference; Cognitive psychology; Computer science; Epistemology; Economics; Microeconomics; Mathematics","score_opus":0.2963841047127266,"score_gpt":0.4644670012000779,"score_spread":0.1680828964873513,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1984452204","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.991172,0.0020914197,0.0007736356,0.001657221,0.0036490464,0.000109331064,0.0000067434844,0.000005759494,0.00053482794],"genre_scores_gemma":[0.9972128,0.00074585556,0.0014613923,0.00040632312,0.00009960497,0.000005108947,4.923875e-7,0.000010109562,0.000058300797],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9966969,0.00042668922,0.0017554163,0.00034978328,0.0005538469,0.00021739645],"domain_scores_gemma":[0.99458915,0.0026157503,0.0015236724,0.00050019304,0.0006485704,0.00012264588],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0018903128,0.00016234673,0.00068177195,0.0006886211,0.000035142504,0.00020051497,0.0007636228,0.0002182573,0.0031146735],"category_scores_gemma":[0.0012609498,0.000113918446,0.00016969934,0.00040765677,0.0003748562,0.001349828,0.000055429304,0.00044091328,0.00021316414],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021460818,0.0001898087,0.07361788,0.0000018569853,0.000033641776,0.00001833416,0.0011308269,0.000022770486,0.0018889426,0.000117346506,0.0036114322,0.91915256],"study_design_scores_gemma":[0.0018696971,0.00027708767,0.14563718,0.0002372677,0.000041727882,0.00030974296,0.0068465876,0.000046978334,0.0008564965,0.8369904,0.006665504,0.00022127418],"about_ca_topic_score_codex":0.000030126546,"about_ca_topic_score_gemma":0.000051701274,"teacher_disagreement_score":0.9189313,"about_ca_system_score_codex":0.00002842309,"about_ca_system_score_gemma":0.000114687515,"threshold_uncertainty_score":0.9977966},"labels":[],"label_agreement":null},{"id":"W1987353489","doi":"10.1007/s10584-008-9458-1","title":"Improving the way we think about projecting future energy use and emissions of carbon dioxide","year":2008,"lang":"en","type":"article","venue":"Climatic Change","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":151,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Overconfidence effect; Futures contract; Scenario planning; Relevance (law); Variety (cybernetics); Probabilistic logic; Futures studies; Task (project management); Scenario analysis; Ranking (information retrieval); Energy (signal processing); Computer science; Risk analysis (engineering); Psychology; Economics; Business; Marketing; Artificial intelligence; Social psychology; Political science","score_opus":0.23344313284463408,"score_gpt":0.35783320498038584,"score_spread":0.12439007213575176,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1987353489","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9970622,0.00095465744,0.000098526034,0.0008259524,0.00052005245,0.00018273194,0.000014252933,0.00003070671,0.0003109369],"genre_scores_gemma":[0.99754816,0.00042443862,0.0011585909,0.00019714801,0.00030244162,0.000021414851,0.0000014525626,0.000016818305,0.0003295495],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99813867,0.000118495234,0.0006500187,0.00036808455,0.00047893694,0.0002458223],"domain_scores_gemma":[0.99698955,0.001611676,0.00047708812,0.0006854009,0.00014143919,0.00009483311],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011729192,0.00015951552,0.00035183856,0.00016216325,0.00034321635,0.00012552728,0.00045695226,0.000108134496,0.00003872434],"category_scores_gemma":[0.0015726776,0.000087970184,0.00010809476,0.00037685817,0.00015249116,0.00032233025,0.000293452,0.00016126707,0.0000053896047],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026629592,0.00009908113,0.024584638,0.000029511593,0.000013052997,0.000031484644,0.026980875,0.0000059399845,0.002243193,0.00035079723,0.00107922,0.9445556],"study_design_scores_gemma":[0.005656966,0.001646363,0.39481217,0.0034432174,0.00069585594,0.0022695085,0.18303643,0.18523154,0.014835783,0.09326356,0.11063831,0.004470319],"about_ca_topic_score_codex":0.00056336174,"about_ca_topic_score_gemma":0.00017909151,"teacher_disagreement_score":0.94008523,"about_ca_system_score_codex":0.000031878684,"about_ca_system_score_gemma":0.00004286666,"threshold_uncertainty_score":0.358732},"labels":[],"label_agreement":null},{"id":"W1987409935","doi":"10.1006/jmps.2001.1374","title":"A Simple Axiomatization of Binary Rank-Dependent Utility of Gains (Losses)","year":2002,"lang":"en","type":"article","venue":"Journal of Mathematical Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Binary number; Simple (philosophy); Partition (number theory); Mathematics; Rank (graph theory); Representation (politics); Applied mathematics; Combinatorics; Arithmetic","score_opus":0.28651160125907393,"score_gpt":0.4756119854686987,"score_spread":0.18910038420962477,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1987409935","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9651163,0.00010884031,0.028301934,0.0005973673,0.00032785392,0.00009174602,0.000012026965,0.000005548491,0.00543839],"genre_scores_gemma":[0.99553955,0.000030694857,0.004181278,0.00011031332,0.000044458884,7.650317e-7,3.0560335e-7,0.000009418016,0.00008324502],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9958801,0.0002618682,0.0025826513,0.00021738502,0.0008798765,0.0001780961],"domain_scores_gemma":[0.9950985,0.0017626337,0.0018522395,0.0005864815,0.00057628285,0.00012386465],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0038909675,0.00012700114,0.00081938226,0.00043869967,0.00003594096,0.000028778366,0.0007789103,0.0001563154,0.0061881086],"category_scores_gemma":[0.0038605616,0.00008567959,0.0003147892,0.00041451285,0.00023646279,0.0002226613,0.00007882804,0.0002000296,0.00018583135],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013197311,0.014416643,0.026327169,0.00021864436,0.0002740692,0.00029845544,0.004718121,0.000618967,0.03304773,0.010026531,0.0998071,0.8089268],"study_design_scores_gemma":[0.0017948983,0.0010581475,0.020160966,0.00012255322,0.00008113388,0.0005681755,0.0005937852,0.011758911,0.0010406559,0.9613454,0.0012950437,0.00018035594],"about_ca_topic_score_codex":0.000001038328,"about_ca_topic_score_gemma":0.0000010997395,"teacher_disagreement_score":0.95131886,"about_ca_system_score_codex":0.000017358065,"about_ca_system_score_gemma":0.000024976336,"threshold_uncertainty_score":0.9947204},"labels":[],"label_agreement":null},{"id":"W1987788491","doi":"10.1111/j.1542-4774.2012.01086.x","title":"RISK AVERSION AND EXPECTED UTILITY THEORY: AN EXPERIMENT WITH LARGE AND SMALL STAKES","year":2012,"lang":"en","type":"article","venue":"Journal of the European Economic Association","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":123,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Expected utility hypothesis; Risk aversion (psychology); Economics; Econometrics; Von Neumann–Morgenstern utility theorem; Subjective expected utility; Constant (computer programming); Set (abstract data type); Sample (material); Mathematical economics; Computer science","score_opus":0.062186598748908965,"score_gpt":0.312326934608013,"score_spread":0.250140335859104,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1987788491","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9971759,0.00014548199,0.00038331427,0.00013341199,0.0005517319,0.0000685077,0.000020893176,0.0000069744847,0.0015138172],"genre_scores_gemma":[0.99893856,0.000037837086,0.0005075094,0.000053640593,0.00019332631,2.4054668e-7,5.1771843e-7,0.000012178223,0.0002562071],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99745774,0.0014023399,0.0005653803,0.00016994207,0.00022090058,0.00018371164],"domain_scores_gemma":[0.9970815,0.00061854854,0.0017919713,0.00026607365,0.00010406575,0.00013779354],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0134019535,0.00010809763,0.00023522793,0.000089630994,0.00024459654,0.0002566269,0.00031685774,0.000039367427,0.00007305281],"category_scores_gemma":[0.00087592605,0.00006235103,0.000074898,0.000050934977,0.00003841031,0.0007182006,0.000133184,0.00018277175,0.000033581942],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015058806,0.000119822245,0.8878868,5.3805377e-7,0.000043975953,0.0000013094976,0.0041469447,0.000049488932,0.00008343301,0.00011971923,0.0011767179,0.10622067],"study_design_scores_gemma":[0.0009513014,0.00015808106,0.98096734,0.000015816053,0.00007031424,0.000026877158,0.005561532,0.00044118814,0.00018123325,0.0038747517,0.0076148426,0.00013670899],"about_ca_topic_score_codex":0.0000068506706,"about_ca_topic_score_gemma":0.00002455097,"teacher_disagreement_score":0.10608396,"about_ca_system_score_codex":0.00024477116,"about_ca_system_score_gemma":0.000030684245,"threshold_uncertainty_score":0.46448764},"labels":[],"label_agreement":null},{"id":"W1988958162","doi":"10.3758/s13423-012-0249-3","title":"Reasoning with base rates is routine, relatively effortless, and context dependent","year":2012,"lang":"en","type":"article","venue":"Psychonomic Bulletin & Review","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":67,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan; University of Waterloo","funders":"","keywords":"Psychology; Base (topology); Personality; Context (archaeology); Neglect; Social psychology; Cognitive psychology; Developmental psychology; Statistics; Mathematics; Psychiatry","score_opus":0.10304304513461295,"score_gpt":0.39120735380690946,"score_spread":0.28816430867229653,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1988958162","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.69738925,0.2817928,0.00089693966,0.00889471,0.00086391205,0.0009382251,0.000048007885,0.0000698694,0.00910631],"genre_scores_gemma":[0.96014905,0.027123889,0.004622052,0.0057026115,0.0001583767,0.000060998216,0.000004897299,0.00004533746,0.0021328104],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99704003,0.00023428626,0.0010657683,0.00076974265,0.00043553833,0.00045465375],"domain_scores_gemma":[0.9971181,0.0008532756,0.00063293654,0.00092352036,0.00014666111,0.00032551185],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0048841187,0.00032714262,0.0008611904,0.00010902426,0.00019936395,0.00024198066,0.00054405385,0.00009262202,0.004449726],"category_scores_gemma":[0.0006960753,0.00021798453,0.00018935559,0.00023812796,0.00014341575,0.00025135762,0.00014467098,0.00027100227,0.0046643144],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005993445,0.00008988069,0.044170883,0.00005333772,0.00003318678,0.0000038447674,0.00020037977,0.0000021538242,0.0000030986334,0.00036388662,0.09786149,0.85715795],"study_design_scores_gemma":[0.0006144224,0.000073470896,0.010546733,0.0018564321,0.000112293725,0.000106203595,0.0002515714,0.000026910213,0.000024076902,0.0006672364,0.98532885,0.0003917683],"about_ca_topic_score_codex":0.00007497018,"about_ca_topic_score_gemma":0.000012603916,"teacher_disagreement_score":0.8874674,"about_ca_system_score_codex":0.00006504891,"about_ca_system_score_gemma":0.00004451277,"threshold_uncertainty_score":0.9964603},"labels":[],"label_agreement":null},{"id":"W1989108037","doi":"10.1016/j.jmp.2005.11.004","title":"Modelling intransitive preferences: A random-effects approach","year":2005,"lang":"en","type":"article","venue":"Journal of Mathematical Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":26,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"National Science Council","keywords":"Transitive relation; Pairwise comparison; Consistency (knowledge bases); Preference; Replication (statistics); Computer science; Econometrics; Invariant (physics); Mathematics; Cognitive psychology; Mathematical economics; Artificial intelligence; Psychology; Statistics","score_opus":0.22193040817320334,"score_gpt":0.44617215646203207,"score_spread":0.22424174828882873,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1989108037","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4151272,0.00009647408,0.57021296,0.0007044625,0.00024590516,0.000097127726,0.0000012186958,0.000007857067,0.013506821],"genre_scores_gemma":[0.878472,0.000025493864,0.12058943,0.00050729583,0.00027428972,0.0000035826345,2.0816607e-7,0.00001172428,0.000116005554],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9967293,0.00032255895,0.0016245223,0.00030947174,0.000747423,0.00026669397],"domain_scores_gemma":[0.9952516,0.003070167,0.0007233606,0.00040017423,0.0003524025,0.0002023181],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004710206,0.00016989616,0.000824027,0.0003598609,0.00006409714,0.00013502948,0.0008596214,0.0001818704,0.00043841917],"category_scores_gemma":[0.0014628592,0.00010240217,0.0003309519,0.00026972304,0.00016182484,0.0003634796,0.0000434516,0.00046278734,0.000512208],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001030244,0.0019431843,0.000059748992,0.000023524924,0.00009540482,0.00007030036,0.0033206218,0.035225227,0.00025489237,0.0063525415,0.009076109,0.9425482],"study_design_scores_gemma":[0.002357146,0.00036528066,0.000043840515,0.00007997231,0.000060648348,0.0007991445,0.00028925255,0.08170793,0.00007703901,0.9103122,0.003741342,0.00016621788],"about_ca_topic_score_codex":3.5190445e-7,"about_ca_topic_score_gemma":3.5221024e-7,"teacher_disagreement_score":0.942382,"about_ca_system_score_codex":0.000035641548,"about_ca_system_score_gemma":0.000047451987,"threshold_uncertainty_score":0.65835685},"labels":[],"label_agreement":null},{"id":"W1989305447","doi":"10.1016/j.actpsy.2008.10.008","title":"Probability assessment with response times and confidence in perception and knowledge","year":2008,"lang":"en","type":"article","venue":"Acta Psychologica","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada; Carleton University","funders":"","keywords":"Perception; Psychology; Cognitive psychology; Confidence interval; Statistics; Mathematics; Neuroscience","score_opus":0.26175330820840575,"score_gpt":0.45149192595311716,"score_spread":0.1897386177447114,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1989305447","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9947488,0.000044967623,0.00010032902,0.001056061,0.00007005966,0.00020378026,0.0000033946467,0.000024549348,0.0037480574],"genre_scores_gemma":[0.9949963,0.00007093516,0.004411456,0.00013242956,0.000010619467,0.000015321139,5.008179e-7,0.0000045145694,0.00035790913],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99818903,0.00037388277,0.00037095012,0.0006571068,0.0002413964,0.0001676201],"domain_scores_gemma":[0.9981812,0.0010644955,0.0001192039,0.00045030907,0.00009652287,0.00008826768],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029818292,0.00012515408,0.00024405195,0.00015220918,0.0001438201,0.00011461473,0.00025692992,0.000096368676,0.0003094041],"category_scores_gemma":[0.00068296085,0.00007663467,0.000023281405,0.00027410468,0.00040519153,0.00026703384,0.00009791037,0.00016772734,0.00005414695],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011031908,0.00055000506,0.7758814,0.000002117504,0.0000036843223,0.000060484825,0.0022889373,0.00000478484,0.0019595658,0.00017750113,0.0037066077,0.21426168],"study_design_scores_gemma":[0.00043742094,0.00046931917,0.97817314,0.0000152306375,0.0000024953188,0.00015206123,0.0005011698,0.00013438037,0.0000043355058,0.016798988,0.0031910941,0.00012038042],"about_ca_topic_score_codex":0.000017105673,"about_ca_topic_score_gemma":0.00004578534,"teacher_disagreement_score":0.21414131,"about_ca_system_score_codex":0.000041369633,"about_ca_system_score_gemma":0.00006331281,"threshold_uncertainty_score":0.33877578},"labels":[],"label_agreement":null},{"id":"W1989563657","doi":"10.1007/s13209-011-0044-9","title":"Revealed preference and choice under uncertainty","year":2011,"lang":"en","type":"article","venue":"SERIEs","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Social Sciences and Humanities Research Council of Canada; Ministry of Education, Culture, Sports, Science and Technology","keywords":"Rationalizability; Transitive relation; Preference; Mathematical economics; Dominance (genetics); Preference theory; Property (philosophy); Class (philosophy); Economics; Revealed preference; Stochastic dominance; Econometrics; Mathematics; Mathematical optimization; Microeconomics; Computer science; Artificial intelligence; Combinatorics","score_opus":0.40996987268490964,"score_gpt":0.38680057717732247,"score_spread":0.023169295507587173,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1989563657","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9879384,0.00006917658,0.00017998173,0.00023280225,0.00031029107,0.00006681539,0.0000106325715,0.00003917162,0.01115273],"genre_scores_gemma":[0.99399096,0.000024072788,0.0017719006,0.0001908176,0.00003302211,0.0000049584924,9.05507e-7,0.000006519879,0.00397683],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9988237,0.00005852981,0.00032904887,0.0003618863,0.00026136596,0.00016547968],"domain_scores_gemma":[0.99886614,0.00034607004,0.00012101233,0.00044936113,0.0001261654,0.00009123358],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006612125,0.00010573619,0.00019584918,0.00008333668,0.00013188734,0.00017661163,0.0003883456,0.0000643703,0.00082910183],"category_scores_gemma":[0.0007064926,0.0000734871,0.000039580103,0.00018754827,0.00018347605,0.0005001513,0.00015875198,0.00008505602,0.00029624515],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024032072,0.00011813767,0.11241575,0.000006227101,0.000018279554,0.000022657274,0.0040920246,0.000071265815,0.0004802665,0.012061858,0.008648008,0.8618252],"study_design_scores_gemma":[0.00022878693,0.00015935618,0.32422635,0.000020849062,0.000012245847,0.000024061848,0.0024051736,0.00008628239,0.00023703263,0.63684016,0.035516944,0.0002427757],"about_ca_topic_score_codex":0.0001590601,"about_ca_topic_score_gemma":0.0005173358,"teacher_disagreement_score":0.8615824,"about_ca_system_score_codex":0.000015039843,"about_ca_system_score_gemma":0.000038911017,"threshold_uncertainty_score":0.90780836},"labels":[],"label_agreement":null},{"id":"W1989779703","doi":"10.3758/s13420-011-0015-9","title":"The criterion-calibration model of cue interaction in contingency judgments","year":2011,"lang":"en","type":"article","venue":"Learning & Behavior","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Psychology; Reciprocal; Contingency; Calibration; Social psychology; Class (philosophy); Cognitive psychology; Artificial intelligence; Statistics; Computer science; Mathematics; Epistemology","score_opus":0.27009798046754313,"score_gpt":0.40913906244095133,"score_spread":0.1390410819734082,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1989779703","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9961045,0.000022294944,0.0019855888,0.000042647498,0.0005657278,0.0001587762,0.0000029185649,0.00002674014,0.0010908135],"genre_scores_gemma":[0.9978895,0.000013057667,0.00117929,0.000021590049,0.000019073455,0.00003190773,0.00000248929,0.000013867968,0.00082918856],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9979399,0.00018250589,0.0008935438,0.00033487883,0.00044416692,0.00020504705],"domain_scores_gemma":[0.9985993,0.00034139148,0.00047879812,0.0003845414,0.00014483205,0.000051121104],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016977317,0.00012050503,0.00022216268,0.00021768642,0.00019147171,0.00017376133,0.00050684594,0.00008026766,0.00024076944],"category_scores_gemma":[0.0008089789,0.00008511049,0.000107886204,0.00027542212,0.00007698482,0.0005686885,0.0001247293,0.0003009037,0.00009026354],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008376574,0.00021529349,0.28877622,8.5540927e-7,0.0000023025038,0.000005006251,0.0027286864,0.0017195214,0.010621016,0.00020299661,0.00011176575,0.69553256],"study_design_scores_gemma":[0.0016500594,0.0006169603,0.63720685,0.00023375286,0.00012382626,0.000025087913,0.009378294,0.3141337,0.013130163,0.018839378,0.0037554405,0.0009064964],"about_ca_topic_score_codex":0.00016648855,"about_ca_topic_score_gemma":0.00013124874,"teacher_disagreement_score":0.69462603,"about_ca_system_score_codex":0.000047084082,"about_ca_system_score_gemma":0.000034988367,"threshold_uncertainty_score":0.34707052},"labels":[],"label_agreement":null},{"id":"W1991011913","doi":"10.1002/bdm.414","title":"A domain‐specific risk‐attitude scale: measuring risk perceptions and risk behaviors","year":2002,"lang":"en","type":"article","venue":"Journal of Behavioral Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1865,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Center for Interuniversity Research and Analysis on Organizations; Defence Research and Development Canada","funders":"","keywords":"Risk perception; Scale (ratio); Psychology; Consistency (knowledge bases); Social psychology; Sample (material); Perception; Actuarial science; Risk aversion (psychology); Construct (python library); Expected utility hypothesis; Business; Economics; Computer science; Financial economics","score_opus":0.11703020244390432,"score_gpt":0.38294582481598927,"score_spread":0.26591562237208494,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1991011913","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96964645,0.001469503,0.026080042,0.00004948712,0.0020329,0.00027435413,0.00015872522,0.00005677701,0.00023178669],"genre_scores_gemma":[0.903582,0.0030639274,0.09276636,0.000026754871,0.00038317378,0.000006863917,6.6896575e-7,0.000073253235,0.00009704755],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9897375,0.00094366714,0.0038543423,0.0011269706,0.003560494,0.0007770251],"domain_scores_gemma":[0.98926723,0.00280027,0.004568108,0.0014161895,0.0012781167,0.0006701068],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.009656786,0.0006340348,0.0013695385,0.0020064884,0.0015246639,0.0018369744,0.0018661877,0.00043032155,0.002872855],"category_scores_gemma":[0.0011803235,0.00048804583,0.0010329889,0.001363686,0.00040302935,0.0017636892,0.00057304517,0.0020580164,0.0006126005],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000115528346,0.00037946994,0.3669881,8.068766e-7,0.000014499855,0.00013486756,0.0012001669,0.00045383244,0.00023348826,0.000007660229,0.0025699225,0.6279017],"study_design_scores_gemma":[0.0030276747,0.0011205416,0.90600944,0.00061803655,0.00091280363,0.0018187107,0.006753746,0.00094248255,0.000053321026,0.048026122,0.029479042,0.001238064],"about_ca_topic_score_codex":0.000077919474,"about_ca_topic_score_gemma":0.0002684172,"teacher_disagreement_score":0.6266636,"about_ca_system_score_codex":0.00036959996,"about_ca_system_score_gemma":0.00006203675,"threshold_uncertainty_score":0.99977523},"labels":[],"label_agreement":null},{"id":"W1991737179","doi":"10.1509/jmkr.39.3.336.19105","title":"Understanding the Role of Preference Revision and Concession in Group Decisions","year":2002,"lang":"en","type":"article","venue":"Journal of Marketing Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":72,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Preference; Product (mathematics); Group decision-making; Affect (linguistics); Group (periodic table); Marketing; Economics; Microeconomics; Business; Psychology; Social psychology; Mathematics","score_opus":0.6854442531007234,"score_gpt":0.4879130225551921,"score_spread":0.19753123054553134,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1991737179","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9932521,0.001852275,0.000480197,0.0006559247,0.000120000994,0.00010751761,0.0000017524942,0.0000020403095,0.003528214],"genre_scores_gemma":[0.9976557,0.0015893101,0.0005901337,0.00001187367,0.00005027229,6.573704e-7,6.557973e-8,0.0000069502084,0.00009505413],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99337924,0.002521638,0.0012893924,0.00025911062,0.002229143,0.00032150975],"domain_scores_gemma":[0.96026546,0.038008448,0.00063011475,0.00037943598,0.00059413747,0.00012239796],"candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.0742226,0.00008855451,0.0003349526,0.0008069026,0.00027689003,0.00030217844,0.0010061469,0.00008749375,0.00036604845],"category_scores_gemma":[0.0472804,0.000047757334,0.00009299824,0.001055026,0.00028287637,0.00037394185,0.00040178053,0.00080927333,0.000012951043],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040091726,0.00009115348,0.059417192,0.0000035762255,0.00000402227,0.000016900729,0.0009098942,0.000058605194,0.0008496328,0.00033138174,0.0024536576,0.9354631],"study_design_scores_gemma":[0.0022185994,0.0011193551,0.17813388,0.0052689165,0.0000237979,0.00030532753,0.064763814,0.03383131,0.0002537887,0.6758421,0.03785822,0.0003808672],"about_ca_topic_score_codex":0.000010381207,"about_ca_topic_score_gemma":0.000020770145,"teacher_disagreement_score":0.9350822,"about_ca_system_score_codex":0.00014347715,"about_ca_system_score_gemma":0.000055906723,"threshold_uncertainty_score":0.96074474},"labels":[],"label_agreement":null},{"id":"W1991848957","doi":"10.1080/13546783.2015.1016450","title":"Better but still biased: Analytic cognitive style and belief bias","year":2015,"lang":"en","type":"article","venue":"Thinking & Reasoning","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":58,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Psychology; Cognitive bias; Cognition; Analytic reasoning; Cognitive style; Cognitive psychology; Heuristic; Confirmation bias; Style (visual arts); Debiasing; Response bias; Deductive reasoning; Social psychology; Artificial intelligence; Computer science","score_opus":0.21927638075755815,"score_gpt":0.3909617875035358,"score_spread":0.17168540674597763,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1991848957","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99262094,0.00031220188,0.0016775021,0.0003598164,0.0004726425,0.00013698365,0.000027426382,0.000118617696,0.004273877],"genre_scores_gemma":[0.992154,0.000008390857,0.0058320295,0.00096023944,0.00018997057,0.000005302617,0.000008936955,0.000030870153,0.00081024267],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9966119,0.00022877379,0.0007001753,0.000799039,0.001217759,0.00044235456],"domain_scores_gemma":[0.99574,0.0024810894,0.00043078844,0.0005392513,0.00045622993,0.0003526615],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0055139405,0.00026805393,0.000514338,0.00041983818,0.00028331025,0.0011705257,0.00061377103,0.00014882612,0.0001507562],"category_scores_gemma":[0.008271814,0.000209039,0.00012466557,0.0005707782,0.00018657958,0.00061090715,0.00040465058,0.00035209948,0.00064399117],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011334405,0.00009399557,0.1270364,0.0000030629349,0.00004393996,0.00016655837,0.0077422005,0.00017066016,0.00005520687,0.00046122246,0.0033020414,0.86081135],"study_design_scores_gemma":[0.008433911,0.0016493669,0.16045092,0.0028410614,0.0008108875,0.00087988726,0.04493348,0.06788896,0.001588789,0.66158664,0.04514079,0.0037952967],"about_ca_topic_score_codex":0.00027219753,"about_ca_topic_score_gemma":0.000060968192,"teacher_disagreement_score":0.8570161,"about_ca_system_score_codex":0.00008951496,"about_ca_system_score_gemma":0.000118741016,"threshold_uncertainty_score":0.99986637},"labels":[],"label_agreement":null},{"id":"W1992360739","doi":"10.1080/13546805.2012.663901","title":"Reasoning heuristics across the psychosis continuum: The contribution of hypersalient evidence–hypothesis matches","year":2012,"lang":"en","type":"article","venue":"Cognitive Neuropsychiatry","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Representativeness heuristic; Heuristics; Psychology; Cognition; Cognitive psychology; Delusion; Conceptualization; Task (project management); Social psychology; Artificial intelligence; Computer science; Psychiatry","score_opus":0.14748387289283332,"score_gpt":0.409925240830831,"score_spread":0.26244136793799766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1992360739","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98988163,0.0014139011,0.0014118018,0.0020442046,0.0037438415,0.00039802102,0.000103424245,0.00003611444,0.0009670755],"genre_scores_gemma":[0.99748755,0.00013604868,0.00024085182,0.0014235963,0.00048042028,0.000031721644,0.0000022164543,0.000028250437,0.00016933268],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9962312,0.00074994814,0.0009776233,0.0005047748,0.00095523463,0.0005812341],"domain_scores_gemma":[0.98630506,0.010938755,0.0008573459,0.0008559505,0.0008914881,0.0001513985],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0049510957,0.00026551267,0.00042982935,0.00008218995,0.0006757344,0.00034810093,0.0011005175,0.00011264708,0.0001353947],"category_scores_gemma":[0.015170817,0.00013976962,0.00034669973,0.0007161662,0.00062158605,0.00041753834,0.0002671848,0.00037677083,0.0004642709],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004927046,0.00044421494,0.62763333,0.0000056822537,0.000066050474,0.0000033570645,0.0031003559,0.000010078195,0.000627036,0.0007505096,0.017863568,0.34900308],"study_design_scores_gemma":[0.0008974917,0.00028354579,0.948307,0.00045064473,0.00033864082,0.00008844701,0.017378869,0.0001803107,0.0021322344,0.014711638,0.014732885,0.0004983234],"about_ca_topic_score_codex":0.000026931604,"about_ca_topic_score_gemma":0.000051559346,"teacher_disagreement_score":0.34850475,"about_ca_system_score_codex":0.000029647203,"about_ca_system_score_gemma":0.000056762638,"threshold_uncertainty_score":0.99312484},"labels":[],"label_agreement":null},{"id":"W1993972343","doi":"10.1214/105051604000000756","title":"Generalized stochastic differential utility and preference for information","year":2004,"lang":"en","type":"article","venue":"The Annals of Applied Probability","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Mitacs","keywords":"Preference; Differential (mechanical device); Mathematical economics; Mathematics; Computer science; Econometrics; Statistics; Physics","score_opus":0.34637374225379663,"score_gpt":0.40514627505927175,"score_spread":0.05877253280547512,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1993972343","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9656207,0.0000113384285,0.032125928,0.0006791398,0.00009653886,0.0008534393,0.00008629221,0.000021717762,0.00050489686],"genre_scores_gemma":[0.99772173,0.000003309172,0.0020126912,0.0001573436,0.00002178051,0.00006708476,0.000007175881,0.000003532578,0.000005326951],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9982596,0.00004346971,0.0007887964,0.00029521412,0.0004165627,0.00019638121],"domain_scores_gemma":[0.9977973,0.0006689974,0.00037383562,0.0007164901,0.0003705179,0.00007284415],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028921873,0.00013116532,0.00032094118,0.00006656347,0.00016686242,0.00015523362,0.0005569078,0.00007615969,0.00004949445],"category_scores_gemma":[0.00096027483,0.000077251956,0.000106023654,0.00017519291,0.0003000526,0.00028230913,0.00018019292,0.00009224815,0.00002064806],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016377184,0.0002209738,0.00014848131,0.000030073332,0.000017168555,2.9662413e-8,0.0017320975,0.005017217,0.00034710875,0.06944162,0.00034804776,0.9210595],"study_design_scores_gemma":[0.00055038073,0.00007326746,0.009616827,0.000006406852,0.000011748748,5.293469e-7,0.000097821074,0.0011134829,0.0016908728,0.98619705,0.0005485005,0.00009312532],"about_ca_topic_score_codex":0.00003212068,"about_ca_topic_score_gemma":0.000022443808,"teacher_disagreement_score":0.9209663,"about_ca_system_score_codex":0.000013079373,"about_ca_system_score_gemma":0.000078130906,"threshold_uncertainty_score":0.31502435},"labels":[],"label_agreement":null},{"id":"W1994476934","doi":"10.1080/01973530802659844","title":"I Knew It All Along, Unless I Had to Work to Learn What I Know","year":2009,"lang":"en","type":"article","venue":"Basic and Applied Social Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Trinity College","funders":"","keywords":"Psychology; Social psychology; Cognition; Knowledge level; Work (physics); Mathematics education","score_opus":0.15620093106182265,"score_gpt":0.45600478288758556,"score_spread":0.2998038518257629,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1994476934","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9330279,0.00011288562,0.0019251626,0.044413388,0.00097313913,0.0003296479,0.0000052444852,0.00005785804,0.019154748],"genre_scores_gemma":[0.9460964,0.000039502236,0.0010786762,0.050581675,0.00041943774,0.000019647281,0.0000027337835,0.000017200457,0.0017446995],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99745035,0.000081731065,0.0006209114,0.00095163466,0.00039782753,0.00049756153],"domain_scores_gemma":[0.9987321,0.00023398812,0.00014832776,0.0004778748,0.00007931458,0.0003283825],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0012418942,0.00023407355,0.00052913156,0.00023676301,0.0002857432,0.0005265652,0.0007065879,0.00028150593,0.0002863714],"category_scores_gemma":[0.00011326379,0.00020384806,0.000113885486,0.00068002095,0.00011612492,0.0001631771,0.00013250207,0.00024236675,0.003034277],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014811542,0.00009475779,0.00022496203,2.981395e-7,0.0000048299135,0.000006244854,0.0014994948,0.000012442765,0.00017301575,0.002390008,0.12500887,0.87043697],"study_design_scores_gemma":[0.00073159614,0.0002631374,0.048170395,0.0000247456,0.000019841493,0.000008588798,0.003171449,0.0000018071406,0.000032460917,0.12643796,0.82068115,0.00045686297],"about_ca_topic_score_codex":0.000008578964,"about_ca_topic_score_gemma":0.00005532068,"teacher_disagreement_score":0.8699801,"about_ca_system_score_codex":0.000035597044,"about_ca_system_score_gemma":0.00003251153,"threshold_uncertainty_score":0.997742},"labels":[],"label_agreement":null},{"id":"W1994622582","doi":"10.1016/s0304-4068(01)00060-x","title":"Rank-dependent preferences without ranking axioms","year":2001,"lang":"en","type":"article","venue":"Journal of Mathematical Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Axiom; Ranking (information retrieval); Mathematical economics; Weighting; Rank (graph theory); Dual (grammatical number); Function (biology); Set (abstract data type); Outcome (game theory); Expected utility hypothesis; Mathematics; Axiomatic system; Property (philosophy); Computer science; Decision theory; Combinatorics; Artificial intelligence; Statistics; Epistemology","score_opus":0.16462797547617009,"score_gpt":0.3913393237749928,"score_spread":0.22671134829882272,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1994622582","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9655909,0.00007839949,0.022254918,0.0007737049,0.0008228963,0.00010769802,0.000004943168,0.000014892978,0.010351683],"genre_scores_gemma":[0.9920705,0.00014968465,0.0066571375,0.0002072272,0.000305475,0.000001934809,3.018283e-7,0.000021828862,0.0005859171],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99604005,0.0001042121,0.0025674684,0.00032966497,0.00063264294,0.00032597137],"domain_scores_gemma":[0.9952081,0.0019461235,0.0016463081,0.0005577355,0.00035215294,0.00028959673],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0060951975,0.00022774232,0.00096707616,0.00041720748,0.00012254293,0.0006837117,0.0013970189,0.00015378284,0.0021656642],"category_scores_gemma":[0.0024032579,0.0001533251,0.00042157885,0.00018850838,0.00013475138,0.0008171327,0.0001658547,0.00036650102,0.0009818341],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000510342,0.00066206726,0.008892913,0.000013298181,0.00012286333,0.00011491011,0.0011962132,0.0034664539,0.00015418942,0.012208439,0.0013226917,0.9713356],"study_design_scores_gemma":[0.0010429232,0.00021226563,0.00072602916,0.000091150934,0.000060517497,0.0011368145,0.0010457793,0.006195404,0.00016854987,0.98238766,0.0066699795,0.00026294065],"about_ca_topic_score_codex":0.000002687975,"about_ca_topic_score_gemma":0.00001143677,"teacher_disagreement_score":0.9710727,"about_ca_system_score_codex":0.00012587599,"about_ca_system_score_gemma":0.00016301643,"threshold_uncertainty_score":0.99979603},"labels":[],"label_agreement":null},{"id":"W1994669758","doi":"10.1080/13546783.2013.875942","title":"Belief bias is stronger when reasoning is more difficult","year":2014,"lang":"en","type":"article","venue":"Thinking & Reasoning","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Psychology; Cognitive psychology; Task (project management); Dual process theory (moral psychology); Debiasing; Belief structure; Dual (grammatical number); Social psychology; Artificial intelligence; Computer science","score_opus":0.09637316939967731,"score_gpt":0.363925256305812,"score_spread":0.2675520869061347,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1994669758","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97585577,0.00022215162,0.006886201,0.0018657036,0.0010094172,0.00018209963,0.000025536989,0.00031353597,0.013639586],"genre_scores_gemma":[0.9650732,0.0000136613035,0.027086968,0.0028779404,0.0005052855,0.000012009409,0.000012575779,0.000079831865,0.0043385164],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99402374,0.00028078895,0.0012396396,0.0014141516,0.0021682212,0.00087345345],"domain_scores_gemma":[0.9946961,0.0018012864,0.0008569034,0.0017748603,0.0005311078,0.0003397611],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.005976779,0.0005031597,0.00083203055,0.0004263926,0.0009942725,0.0018910193,0.0020547244,0.00031657037,0.0015823654],"category_scores_gemma":[0.005535945,0.0003936612,0.00038308292,0.0007470809,0.00018455806,0.00080597674,0.000659403,0.0006725558,0.0017547535],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000036065558,0.000107643755,0.046368264,0.000005264611,0.00004352524,0.00002448696,0.019503705,0.00044363702,0.0001553379,0.0039461805,0.044856776,0.8845091],"study_design_scores_gemma":[0.0030973803,0.0006183753,0.06980607,0.002619689,0.0003557873,0.00029475935,0.010658631,0.120289974,0.0026311292,0.30260465,0.483317,0.0037065523],"about_ca_topic_score_codex":0.0003167379,"about_ca_topic_score_gemma":0.000032139946,"teacher_disagreement_score":0.8808026,"about_ca_system_score_codex":0.00017485544,"about_ca_system_score_gemma":0.000104960716,"threshold_uncertainty_score":0.9998515},"labels":[],"label_agreement":null},{"id":"W1995081088","doi":"10.1080/13546783.2013.844729","title":"Assessing miserly information processing: An expansion of the Cognitive Reflection Test","year":2013,"lang":"en","type":"article","venue":"Thinking & Reasoning","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":878,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; York University","funders":"","keywords":"Psychology; Test (biology); Dual process theory (moral psychology); Cognition; Cognitive psychology; Measure (data warehouse); Reliability (semiconductor); Variance (accounting); Information processing; Reflection (computer programming); Dual (grammatical number); Prime (order theory); Social psychology; Computer science; Mathematics; Data mining","score_opus":0.0971559523513711,"score_gpt":0.39984466099706467,"score_spread":0.3026887086456936,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1995081088","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9892233,0.000025644245,0.005010036,0.00012960256,0.00036730434,0.00023490196,0.0000025672232,0.00008315415,0.0049234782],"genre_scores_gemma":[0.9935919,0.0000014491833,0.0060223658,0.0002120545,0.00006449072,0.000012461084,0.0000061542587,0.000013188683,0.00007594798],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9974502,0.00016660079,0.00081717526,0.00030536405,0.0010228558,0.00023782981],"domain_scores_gemma":[0.9965795,0.00090175477,0.0010207361,0.00044937208,0.0009683575,0.00008025792],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0024553242,0.00015878584,0.00025336628,0.00023343615,0.00071664,0.0021412778,0.0006783258,0.00012830894,0.00010339458],"category_scores_gemma":[0.0050126123,0.000103810606,0.000100968566,0.0007718413,0.00010970132,0.0069129844,0.0001514248,0.00027960693,0.0001335076],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009325528,0.00003975572,0.01889487,0.000004429999,0.0000022379584,3.7525575e-7,0.004516492,0.00012510455,0.0027951223,0.00006517062,0.000100112265,0.973447],"study_design_scores_gemma":[0.0013740659,0.0005364796,0.59446704,0.003495363,0.00013126672,0.00012453173,0.05112343,0.11154598,0.018237276,0.2169483,0.0010420149,0.00097424985],"about_ca_topic_score_codex":0.0002134436,"about_ca_topic_score_gemma":0.000014872697,"teacher_disagreement_score":0.9724727,"about_ca_system_score_codex":0.00007647,"about_ca_system_score_gemma":0.00016547694,"threshold_uncertainty_score":0.9988946},"labels":[],"label_agreement":null},{"id":"W1996324419","doi":"10.1007/s00355-015-0876-5","title":"Expected utility without full transitivity","year":2015,"lang":"en","type":"article","venue":"Social Choice and Welfare","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Transitive relation; Axiom; Mathematical economics; Expected utility hypothesis; Class (philosophy); Consistency (knowledge bases); Preference; Completeness (order theory); Subjective expected utility; Mathematics; Economics; Econometrics; Discrete mathematics; Computer science; Statistics; Artificial intelligence; Combinatorics","score_opus":0.2373221207991091,"score_gpt":0.42417190135042226,"score_spread":0.18684978055131315,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1996324419","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9881526,0.00007439725,0.00029220944,0.0035116894,0.00039274446,0.00009881424,0.000059542883,0.00006841038,0.007349575],"genre_scores_gemma":[0.99922293,0.0000016617952,0.00010617032,0.00017117572,0.0002677824,0.000005312439,0.0000060232,0.000009748395,0.00020920235],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99815446,0.00017563236,0.00037311466,0.0004668545,0.00059425994,0.00023567361],"domain_scores_gemma":[0.998877,0.0002188408,0.00012771436,0.00026773656,0.00029799095,0.00021070513],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013630391,0.0001460011,0.0003412133,0.00008255142,0.00041608466,0.00028925666,0.0003003082,0.0001511679,0.00025192296],"category_scores_gemma":[0.00092110154,0.00011564814,0.00011445605,0.0003155466,0.00015752275,0.00036368117,0.000084293075,0.00017050165,0.00010585506],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011450277,0.00012709876,0.10883057,0.000002805562,0.000010944792,0.000009177872,0.00430924,0.0000018267893,0.000058819634,0.000449506,0.007818465,0.87826705],"study_design_scores_gemma":[0.0017882668,0.00019160341,0.5563156,0.0000114588365,0.000051980038,0.000016103588,0.015929524,0.00034038327,0.00004888118,0.07884764,0.34587651,0.0005820766],"about_ca_topic_score_codex":0.0002543391,"about_ca_topic_score_gemma":0.0006594844,"teacher_disagreement_score":0.87768495,"about_ca_system_score_codex":0.00003748319,"about_ca_system_score_gemma":0.00006504317,"threshold_uncertainty_score":0.47159943},"labels":[],"label_agreement":null},{"id":"W1996408424","doi":"10.2139/ssrn.2423352","title":"Evidence on Individual Preferences for Longevity Risk","year":2013,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bureau de Coopération Interuniversitaire; Université du Québec à Montréal","funders":"","keywords":"Longevity; Longevity risk; Biology; Genetics","score_opus":0.2020312407840326,"score_gpt":0.4011080707502904,"score_spread":0.19907682996625783,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1996408424","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98853594,0.0010436265,0.00832899,0.0007706536,0.0006101262,0.00031753664,0.000017252529,0.000025411391,0.0003504348],"genre_scores_gemma":[0.9966511,0.001466977,0.00053069927,0.00015026028,0.00031191375,0.000029291166,0.0000011554915,0.000015582978,0.000842997],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9956054,0.00027897078,0.0007896885,0.00052207446,0.0010638637,0.0017399647],"domain_scores_gemma":[0.99499345,0.00317466,0.0007118857,0.0005078401,0.0004354849,0.00017670456],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.012033267,0.00020899702,0.0003445405,0.00029539852,0.00050608465,0.001074283,0.0016655033,0.00012589675,0.000461908],"category_scores_gemma":[0.0059906235,0.00013630571,0.00027795113,0.00030169004,0.00008713049,0.0010407981,0.000109438144,0.0015368274,0.0013231107],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005523199,0.00006421874,0.015218931,4.8539766e-7,0.000028049326,4.6047236e-7,0.000092514856,0.000072797775,0.00001989039,0.002003892,0.0027239325,0.9797196],"study_design_scores_gemma":[0.00031414774,0.0010489206,0.020147221,0.00004222971,0.000036997553,0.000058891834,0.001119882,0.00019579918,0.000066568995,0.9751152,0.0016591252,0.00019506438],"about_ca_topic_score_codex":0.000110362824,"about_ca_topic_score_gemma":0.0006921283,"teacher_disagreement_score":0.97952455,"about_ca_system_score_codex":0.0003826558,"about_ca_system_score_gemma":0.0012523625,"threshold_uncertainty_score":0.9999627},"labels":[],"label_agreement":null},{"id":"W1997098523","doi":"10.1177/0146167207303014","title":"Motivated Prediction of Future Feelings: Effects of Negative Mood and Mood Orientation on Affective Forecasts","year":2007,"lang":"en","type":"review","venue":"Personality and Social Psychology Bulletin","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; Wilfrid Laurier University","funders":"","keywords":"Psychology; Feeling; Mood; Negative mood; Orientation (vector space); Affect (linguistics); Social psychology","score_opus":0.13290798073529012,"score_gpt":0.4459819949172987,"score_spread":0.31307401418200853,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1997098523","genre_codex":"empirical","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6366314,0.35416532,0.0005153655,0.00093407475,0.0026354773,0.001976749,0.0009375323,0.00005078692,0.0021532697],"genre_scores_gemma":[0.24439506,0.75315416,0.00060373166,0.00035506109,0.0010371641,0.00007778651,0.00013288119,0.00006783957,0.00017630398],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.996583,0.000826001,0.0010299828,0.0008325166,0.00050264935,0.00022584545],"domain_scores_gemma":[0.99500227,0.0031276885,0.0012612089,0.00023379344,0.00029828915,0.00007676591],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0024021706,0.0003425776,0.0016579016,0.00035512817,0.00020782942,0.00004215194,0.0002454315,0.0008334059,0.00009712402],"category_scores_gemma":[0.0009808149,0.00026762162,0.0003619282,0.0004191081,0.000536215,0.000057767877,0.000070965136,0.00051403494,0.00001729669],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018577675,0.00021895856,0.00019279422,0.00064990966,0.00009759543,0.0000022243119,0.0030807378,2.506528e-7,0.0000019716329,0.00028838383,0.0008817712,0.9943996],"study_design_scores_gemma":[0.007575829,0.005042206,0.07484667,0.0077046813,0.0023313228,0.00012743963,0.008728081,0.000028909042,0.000051395054,0.043982983,0.847979,0.0016014932],"about_ca_topic_score_codex":0.000035038844,"about_ca_topic_score_gemma":0.00001548676,"teacher_disagreement_score":0.99279815,"about_ca_system_score_codex":0.00005826707,"about_ca_system_score_gemma":0.0000497755,"threshold_uncertainty_score":0.9999776},"labels":[],"label_agreement":null},{"id":"W1997697391","doi":"10.1016/j.paid.2009.01.007","title":"The Maximization Paradox: The costs of seeking alternatives","year":2009,"lang":"en","type":"article","venue":"Personality and Individual Differences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":191,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Sacrifice; Psychology; Maximization; Social psychology; Microeconomics; Economics","score_opus":0.19789693230308184,"score_gpt":0.3878109505490901,"score_spread":0.18991401824600826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1997697391","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9938972,0.0005340146,0.00048409848,0.0033420927,0.00018287344,0.00009906908,0.00004294191,0.00001017319,0.0014075165],"genre_scores_gemma":[0.9992823,0.00016954131,0.00009471518,0.00026521596,0.00005477332,0.0000029566281,0.0000026128155,0.0000022112304,0.00012564333],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9979909,0.00027646663,0.00046115892,0.0002798762,0.0008201835,0.00017138262],"domain_scores_gemma":[0.9968409,0.0023832235,0.00032706448,0.0002726982,0.00012411797,0.000051992167],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025138704,0.00011714209,0.00021357443,0.00005500063,0.0006241108,0.0006680635,0.00084497116,0.000049542792,0.000064241445],"category_scores_gemma":[0.0009482938,0.00005196446,0.000080741156,0.00022385485,0.00041548332,0.00024047396,0.00009414198,0.00013335812,0.000008874773],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002766719,0.00004643859,0.07995969,6.8533797e-7,0.000013609559,4.29977e-7,0.0034158237,0.000008655989,0.000025585063,0.010384325,0.00029470614,0.9058224],"study_design_scores_gemma":[0.00012114987,0.00010461953,0.783108,0.000020281897,0.00001636542,0.0000042571,0.0034895376,0.0012131925,0.000045717275,0.21083805,0.00095219584,0.00008662615],"about_ca_topic_score_codex":0.00007745568,"about_ca_topic_score_gemma":0.00008424006,"teacher_disagreement_score":0.90573573,"about_ca_system_score_codex":0.000012161353,"about_ca_system_score_gemma":0.000030439383,"threshold_uncertainty_score":0.64421517},"labels":[],"label_agreement":null},{"id":"W2000166164","doi":"10.1016/j.strusafe.2007.09.007","title":"Application of cumulative prospect theory: Implied seismic design preference","year":2007,"lang":"en","type":"article","venue":"Structural Safety","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":49,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cumulative prospect theory; Weighting; Prospect theory; Preference; Bounded rationality; Rationality; Expected utility hypothesis; Seismic analysis; Econometrics; Seismic risk; Sensitivity (control systems); Computer science; Economics; Engineering; Mathematical economics; Microeconomics; Structural engineering","score_opus":0.1310299700131957,"score_gpt":0.39955937454729396,"score_spread":0.26852940453409824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2000166164","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6796781,0.000018264402,0.31770894,0.00004394908,0.00018486072,0.00035138716,0.000029073319,0.00003256786,0.001952874],"genre_scores_gemma":[0.991112,0.0000019463591,0.008578004,0.000048001904,0.000051821866,0.0000044614135,0.000006844577,0.000010940582,0.00018598647],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.997562,0.00013230673,0.0009274871,0.0005113147,0.00058845564,0.00027843495],"domain_scores_gemma":[0.9967398,0.0016741012,0.00056063384,0.0006414263,0.00028714127,0.000096872944],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035993357,0.00017423369,0.00034722805,0.00015672282,0.00016462682,0.000064854634,0.000714685,0.000106735555,0.00023108833],"category_scores_gemma":[0.00065141317,0.00011685302,0.00011165092,0.0005275447,0.00017323202,0.0002570758,0.00013129751,0.00015209915,0.000107942935],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005748095,0.000010162086,0.005029422,0.0000014726954,0.000008617421,0.0000010825387,0.00044448473,0.0036495917,0.0023647675,0.015509293,0.00005891831,0.9723474],"study_design_scores_gemma":[0.00030512412,0.00008369168,0.20774738,0.0000072296457,0.00001232461,0.000009262091,0.00026255375,0.008853047,0.0055757705,0.77620816,0.000760617,0.0001748249],"about_ca_topic_score_codex":0.000040564293,"about_ca_topic_score_gemma":0.000019304294,"teacher_disagreement_score":0.97217256,"about_ca_system_score_codex":0.00010326497,"about_ca_system_score_gemma":0.00005991637,"threshold_uncertainty_score":0.4765128},"labels":[],"label_agreement":null},{"id":"W2000481529","doi":"10.4236/jss.2014.23006","title":"The Role of Gender in Individual and Group Decision Making: A Research Model","year":2014,"lang":"en","type":"article","venue":"Open Journal of Social Sciences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Lottery; Group decision-making; Affect (linguistics); Preference; Diversity (politics); Context (archaeology); Psychology; Social psychology; Actuarial science; Economics; Microeconomics; Sociology; Geography","score_opus":0.46614455899107005,"score_gpt":0.5492682646874876,"score_spread":0.08312370569641753,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2000481529","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9865766,0.00017789545,0.00046115095,0.00057440315,0.00015307972,0.000093559225,0.000003054169,8.590861e-7,0.011959364],"genre_scores_gemma":[0.9949235,0.00002403362,0.0048962417,0.000048613267,0.00007741588,0.0000012961724,3.6149984e-8,0.0000034883587,0.00002538616],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9958249,0.0004992582,0.0009235132,0.00025498692,0.0022138706,0.00028352326],"domain_scores_gemma":[0.9947525,0.0039672647,0.00063117576,0.00015893945,0.00042156363,0.00006854425],"candidate_categories":["metaresearch","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.050842777,0.00007840635,0.0003151029,0.00039168366,0.0009731967,0.0016523928,0.0033307306,0.00007010091,0.00003485262],"category_scores_gemma":[0.003740777,0.000041235537,0.00007745784,0.0010390548,0.0009768204,0.0008865682,0.0008895521,0.00028764043,0.0000067310716],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000081865954,0.00004889237,0.011163899,2.947152e-7,0.0000027093458,0.0000013606178,0.002750032,0.0003330902,0.0000991481,0.014728858,0.0010427028,0.9697471],"study_design_scores_gemma":[0.00024759394,0.0001885555,0.025658496,0.000032214924,0.0000037194404,0.00001112901,0.008584833,0.006424724,0.000021327884,0.9534418,0.005323137,0.00006245791],"about_ca_topic_score_codex":0.000035131383,"about_ca_topic_score_gemma":0.00016165663,"teacher_disagreement_score":0.96968466,"about_ca_system_score_codex":0.00003530383,"about_ca_system_score_gemma":0.00025093113,"threshold_uncertainty_score":0.999384},"labels":[],"label_agreement":null},{"id":"W2001117071","doi":"10.1093/geronb/60.4.p215","title":"Framing Effects in Younger and Older Adults","year":2005,"lang":"en","type":"article","venue":"The Journals of Gerontology Series B","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":161,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"National Institute on Aging","keywords":"Framing (construction); Psychology; History","score_opus":0.07751531858098035,"score_gpt":0.3957720358829111,"score_spread":0.3182567173019307,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2001117071","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9894125,0.0038142612,0.00016582476,0.005679961,0.00032815713,0.00011160395,0.0000018776288,0.000007771511,0.00047804476],"genre_scores_gemma":[0.99780685,0.0001963189,0.0011940671,0.0005137779,0.00007824554,0.0000036185752,1.3019427e-7,0.000007087417,0.00019988835],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9982569,0.00023380204,0.0007351644,0.00023231399,0.00030173032,0.00024005174],"domain_scores_gemma":[0.99755305,0.0014924041,0.00038846277,0.00038553413,0.00011673216,0.000063845575],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025468413,0.00012059773,0.0004231231,0.00020124677,0.000113878305,0.00008946098,0.00052960095,0.00011973019,0.00020042254],"category_scores_gemma":[0.0010706199,0.00007059234,0.00006931151,0.0001716318,0.00027923097,0.0006697273,0.00013679253,0.00024380516,0.000040027033],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028491137,0.000075358585,0.03064564,0.0000051432553,0.000012287994,0.00001981926,0.0033867306,0.00008800781,0.0003947486,0.00031351444,0.0013302426,0.9634436],"study_design_scores_gemma":[0.0014669626,0.0002960753,0.9170001,0.00027714146,0.000032075113,0.0006213539,0.004657799,0.0005307988,0.0012093177,0.064400636,0.009238446,0.00026930237],"about_ca_topic_score_codex":0.00005332139,"about_ca_topic_score_gemma":0.00095255993,"teacher_disagreement_score":0.9631743,"about_ca_system_score_codex":0.00002389879,"about_ca_system_score_gemma":0.000022838378,"threshold_uncertainty_score":0.2878672},"labels":[],"label_agreement":null},{"id":"W2001136280","doi":"10.1108/10610420710834940","title":"Bundles = discount? Revisiting complex theories of bundle effects","year":2007,"lang":"en","type":"article","venue":"Journal of Product & Brand Management","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":50,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Bundle; Test (biology); Economics; Marketing; Business","score_opus":0.06909435262192272,"score_gpt":0.39120127922761805,"score_spread":0.32210692660569534,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2001136280","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96896285,0.0007898533,0.016936509,0.0009278351,0.0013213217,0.00027082022,0.0000035418686,0.000010505041,0.010776767],"genre_scores_gemma":[0.9904421,0.00009702559,0.007920556,0.000114600465,0.00048689087,8.1768036e-7,6.710267e-7,0.0000122962665,0.00092502084],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99659175,0.00011917256,0.0015694998,0.00030937837,0.0011438754,0.00026632505],"domain_scores_gemma":[0.99663705,0.00087191054,0.001401891,0.00053964724,0.0004479955,0.00010150876],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011080511,0.00016554404,0.0005850923,0.00052127364,0.00013841709,0.00024774307,0.0008168989,0.000030705363,0.00013448457],"category_scores_gemma":[0.0011106302,0.000107673564,0.0002530108,0.00048237696,0.000139268,0.0004901165,0.00022234062,0.00015508776,0.000033570595],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026378187,0.00023833581,0.0023696255,0.000075131524,0.00007435199,0.00006831327,0.00037964067,0.00017597614,0.0013195031,0.007973528,0.0037562337,0.9833056],"study_design_scores_gemma":[0.0037782246,0.0013421109,0.1484065,0.0012364424,0.00051810197,0.0002773379,0.0070130546,0.0000789586,0.014394405,0.52652264,0.29563773,0.0007945022],"about_ca_topic_score_codex":0.0000077273435,"about_ca_topic_score_gemma":0.000009639527,"teacher_disagreement_score":0.9825111,"about_ca_system_score_codex":0.000056856363,"about_ca_system_score_gemma":0.000027270942,"threshold_uncertainty_score":0.43908006},"labels":[],"label_agreement":null},{"id":"W2001362003","doi":"10.1080/02699930701739849","title":"Causal uncertainty and metacognitive inferences about goal attainment","year":2008,"lang":"en","type":"article","venue":"Cognition & Emotion","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Psychology; Feeling; Task (project management); Cognitive psychology; Metacognition; Social psychology; Cognition; Causal inference; Metamemory; Developmental psychology; Econometrics","score_opus":0.17357594901221282,"score_gpt":0.3853860977493752,"score_spread":0.2118101487371624,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2001362003","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98717475,0.00008881193,0.006095357,0.00031058275,0.0005064817,0.0002242069,0.00007467043,0.00006579279,0.0054593403],"genre_scores_gemma":[0.998399,0.00015534827,0.00047097058,0.0003417452,0.00013364933,0.000020237032,0.000059588598,0.00001063277,0.0004088316],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99750906,0.0002186027,0.0006477483,0.0006031623,0.0007702531,0.00025117965],"domain_scores_gemma":[0.9979684,0.00072203315,0.00030074298,0.00024049518,0.0006022963,0.00016607785],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0011750286,0.0001968359,0.0003172544,0.0002912687,0.00046308726,0.0002459801,0.00020506831,0.0001242735,0.00083080586],"category_scores_gemma":[0.0013036411,0.00015754034,0.000108773485,0.00036546227,0.00030993938,0.00062815467,0.00011002096,0.00017002365,0.00084025075],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000092283786,0.00019612622,0.010945521,0.0000032794974,0.000025009733,0.000041765154,0.0011524888,0.000116802956,0.0004484493,0.00040412773,0.0023865765,0.98418754],"study_design_scores_gemma":[0.0029219587,0.0008474237,0.6034935,0.0001968526,0.00022614062,0.00043042543,0.0060420665,0.0067413263,0.0018053985,0.3633468,0.012863847,0.001084259],"about_ca_topic_score_codex":0.000037685335,"about_ca_topic_score_gemma":0.000043104894,"teacher_disagreement_score":0.98310333,"about_ca_system_score_codex":0.00006074324,"about_ca_system_score_gemma":0.00008412994,"threshold_uncertainty_score":0.9999377},"labels":[],"label_agreement":null},{"id":"W2001678613","doi":"10.1167/14.10.1061","title":"Familiarity wins over novelty: A persistent attentional bias toward regularities","year":2014,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Novelty; Random forest; Computer science; Artificial intelligence; Pattern recognition (psychology); Psychology; Social psychology","score_opus":0.19506664713326635,"score_gpt":0.40634928934643605,"score_spread":0.2112826422131697,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2001678613","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9914106,0.00012188769,0.0033354075,0.0020270005,0.0017208665,0.000053162086,0.000012791078,0.000010573166,0.0013077181],"genre_scores_gemma":[0.99526197,0.000028436089,0.0031337508,0.00041429597,0.00037910088,4.530674e-7,0.0000013799648,0.000012017128,0.0007685978],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99596405,0.00022378823,0.0013431957,0.00031384634,0.0019304471,0.00022468939],"domain_scores_gemma":[0.99662066,0.0009417295,0.0009902074,0.00043507782,0.0008030386,0.00020928148],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0060257236,0.00016688506,0.0004956457,0.00047436688,0.00018119514,0.0005180626,0.0008144316,0.00019057331,0.00052641827],"category_scores_gemma":[0.0025657627,0.00011227341,0.00080311205,0.00032610618,0.00012187447,0.0007596573,0.000206439,0.00045324524,0.00017199175],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00049808034,0.0009057578,0.072351895,0.000011714506,0.00007805341,0.00006876276,0.000925579,0.0012501165,0.0031842806,0.0022547436,0.08048715,0.83798385],"study_design_scores_gemma":[0.002282174,0.0021548432,0.6353842,0.00035178094,0.000116892996,0.00063593057,0.0019634056,0.013306254,0.00013715771,0.13218804,0.21100186,0.00047744453],"about_ca_topic_score_codex":0.000017885146,"about_ca_topic_score_gemma":0.000012443699,"teacher_disagreement_score":0.8375064,"about_ca_system_score_codex":0.00014155403,"about_ca_system_score_gemma":0.00010984008,"threshold_uncertainty_score":0.57639104},"labels":[],"label_agreement":null},{"id":"W2003371167","doi":"10.1142/s021759081350001x","title":"VALUATIONS OF CHANGES IN RISKS: THE REFERENCE STATE AND EVIDENCE OF DIFFERENCES BETWEEN THE MEASURES","year":2013,"lang":"en","type":"article","venue":"The Singapore Economic Review","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"National Science Foundation","keywords":"Harm; Valuation (finance); Value (mathematics); Actuarial science; Economics; Willingness to pay; Econometrics; Psychology; Statistics; Microeconomics; Social psychology; Mathematics; Finance","score_opus":0.5790716842212912,"score_gpt":0.47581489895102164,"score_spread":0.10325678527026955,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2003371167","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9449432,0.045261186,0.00002176791,0.00866076,0.000096131305,0.0006654261,0.000017471957,0.0000037069103,0.0003303865],"genre_scores_gemma":[0.9581983,0.041383807,0.000047338246,0.00020660243,0.000026636772,0.00004673066,4.876178e-7,0.0000057649872,0.00008431269],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99726385,0.00077314914,0.0011763073,0.0003074505,0.00031303518,0.00016622806],"domain_scores_gemma":[0.9895973,0.0080234315,0.0011366961,0.0010391491,0.00016468375,0.00003871489],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010167574,0.0001470352,0.0006204109,0.00007953267,0.00015506534,0.0001469477,0.0014943508,0.000035395035,0.00037743666],"category_scores_gemma":[0.0025309976,0.000057539684,0.000093670664,0.00023273336,0.0005385474,0.00025840916,0.00024176124,0.00018145204,0.00015292397],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000040092777,0.000009695442,0.052540835,0.00006001959,0.000014138028,9.431226e-8,0.00053179485,0.00004394423,0.000022107004,0.00020316403,0.001059914,0.94551027],"study_design_scores_gemma":[0.00016727652,0.00015753566,0.7671609,0.0050871526,0.00016055093,0.0000067478027,0.0009890704,0.0005860631,0.00014844895,0.22139385,0.0038984295,0.00024397043],"about_ca_topic_score_codex":0.0008155667,"about_ca_topic_score_gemma":0.0011260272,"teacher_disagreement_score":0.9452663,"about_ca_system_score_codex":0.00003093845,"about_ca_system_score_gemma":0.00012055108,"threshold_uncertainty_score":0.4132667},"labels":[],"label_agreement":null},{"id":"W2004621686","doi":"10.1016/j.joep.2010.12.005","title":"Debiasing or rebiasing? Moderating the illusion of delayed incentives","year":2010,"lang":"en","type":"article","venue":"Journal of Economic Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Debiasing; Illusion; Incentive; Illusion of control; Cognitive psychology; Discounting; Psychology; Economics; Cognitive bias; Social psychology; Microeconomics; Cognition; Finance","score_opus":0.17832780228749712,"score_gpt":0.48335023824217876,"score_spread":0.30502243595468165,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2004621686","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9891421,0.00005547927,0.0020645082,0.0014630493,0.004862514,0.00006821441,0.0000065113923,0.0000047293997,0.002332868],"genre_scores_gemma":[0.9927054,0.00003360612,0.006298303,0.00048785392,0.0003501846,5.9183105e-7,2.4240381e-7,0.000012816823,0.00011097554],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9971996,0.0001595068,0.0019184496,0.00028399742,0.00022228397,0.00021617582],"domain_scores_gemma":[0.99471134,0.0020397322,0.0023054804,0.00059089396,0.0002564894,0.00009606198],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00520913,0.00013824468,0.0005272762,0.00034277723,0.00019150102,0.00014929894,0.0012049475,0.000160479,0.00076448586],"category_scores_gemma":[0.0018177229,0.00007600843,0.00025557526,0.000142351,0.00028800318,0.00043622384,0.00013763725,0.00054323097,0.00007203758],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012612108,0.00020732224,0.008571054,0.0000014707683,0.00006690778,0.000037794947,0.0015687306,0.0015131045,0.029352996,0.00094217446,0.00834267,0.94813454],"study_design_scores_gemma":[0.006568636,0.002733958,0.07013836,0.00020971493,0.00019703452,0.007893434,0.005787994,0.029095631,0.0048040412,0.7938182,0.07772306,0.0010299605],"about_ca_topic_score_codex":0.0000141366845,"about_ca_topic_score_gemma":0.00019525873,"teacher_disagreement_score":0.94710463,"about_ca_system_score_codex":0.000044256518,"about_ca_system_score_gemma":0.00018968194,"threshold_uncertainty_score":0.8370584},"labels":[],"label_agreement":null},{"id":"W2005019135","doi":"10.1037/a0019466","title":"Positive mood effects on delay discounting.","year":2010,"lang":"en","type":"article","venue":"Emotion","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":95,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health; University of Toronto","funders":"","keywords":"Psychology; Extraversion and introversion; Delay discounting; Mood; Affect (linguistics); Delay of gratification; Discounting; Personality; Developmental psychology; Temporal discounting; Situational ethics; Social psychology; Impulsivity; Big Five personality traits","score_opus":0.038430467147049154,"score_gpt":0.36229430862883577,"score_spread":0.3238638414817866,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2005019135","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9845437,0.0000027203967,0.0013968037,0.0007365463,0.0025802697,0.0001595394,0.000008477078,0.00004270382,0.010529279],"genre_scores_gemma":[0.9980146,5.6333477e-7,0.0006888014,0.00026381426,0.00030325065,0.0000054422326,0.0000054372445,0.000010556179,0.0007075279],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9985341,0.00007124072,0.000304336,0.00040162329,0.00051488844,0.00017384114],"domain_scores_gemma":[0.99817675,0.0009952608,0.0001622271,0.00046351654,0.00012373056,0.00007851827],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0012091772,0.000114451774,0.00016332387,0.00017841462,0.00016685127,0.00032744318,0.00034570153,0.00010430602,0.00027609954],"category_scores_gemma":[0.001496442,0.00008197716,0.000102352125,0.000237855,0.00004149455,0.00031067163,0.00006323742,0.0002585473,0.0034638932],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018941966,0.000072211405,0.0026734276,5.700247e-7,0.0000022875117,0.000007877567,0.00015395798,0.00003395109,0.0037258219,0.00087749364,0.0021601801,0.9902733],"study_design_scores_gemma":[0.0012522051,0.0008237642,0.65346736,0.00011610005,0.00004101574,0.000078585195,0.00027649122,0.0048369975,0.029663766,0.28375083,0.024996324,0.00069656374],"about_ca_topic_score_codex":0.000016766317,"about_ca_topic_score_gemma":0.00005687452,"teacher_disagreement_score":0.9895767,"about_ca_system_score_codex":0.000026437407,"about_ca_system_score_gemma":0.000017249859,"threshold_uncertainty_score":0.997312},"labels":[],"label_agreement":null},{"id":"W2005081301","doi":"10.1037/a0034207","title":"Do framing effects reveal irrational choice?","year":2013,"lang":"en","type":"article","venue":"Journal of Experimental Psychology General","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Framing effect; Framing (construction); Irrational number; Irrationality; Logical equivalence; Mathematical economics; Regret; Bounded function; Mathematics; Epistemology; Social psychology; Econometrics; Psychology; Positive economics; Economics; Discrete mathematics; Statistics; Philosophy; Rationality; Equivalence (formal languages); Mathematical analysis","score_opus":0.11481998722434929,"score_gpt":0.47479841124140215,"score_spread":0.3599784240170529,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2005081301","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99010044,0.0007478227,0.00045658456,0.0008125626,0.0044647763,0.0001241883,0.0000020556502,0.000009110435,0.0032824492],"genre_scores_gemma":[0.9862114,0.0000059700465,0.010005908,0.00201361,0.0010595006,0.0000083658,0.000001127505,0.00001592295,0.00067818793],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9970948,0.00028124204,0.0012179776,0.0003712655,0.0007478729,0.00028681924],"domain_scores_gemma":[0.99762344,0.0006625994,0.0007768536,0.00040801245,0.000300031,0.00022908708],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0014116666,0.00018788353,0.00044610348,0.00037475844,0.000171754,0.00032788623,0.0008452638,0.00017029903,0.0022043972],"category_scores_gemma":[0.00058066065,0.0001349297,0.00028956294,0.00023006508,0.00014105075,0.0007356952,0.00010239158,0.00040405398,0.00086814363],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000113639835,0.0007127687,0.032513205,0.0000011075491,0.0000524557,0.00008212764,0.0006062742,0.00010852809,0.48637402,0.0003014043,0.28315124,0.19598323],"study_design_scores_gemma":[0.008878486,0.0048267012,0.6632065,0.00012846164,0.00006333112,0.0033587634,0.001744384,0.00079421984,0.07084238,0.1809151,0.06392016,0.0013215287],"about_ca_topic_score_codex":0.000014494477,"about_ca_topic_score_gemma":0.0000014178548,"teacher_disagreement_score":0.63069326,"about_ca_system_score_codex":0.000081504404,"about_ca_system_score_gemma":0.000052734453,"threshold_uncertainty_score":0.9999098},"labels":[],"label_agreement":null},{"id":"W2005262305","doi":"10.1007/s10339-012-0526-0","title":"Negative valence can evoke a liberal response bias in syllogistic reasoning","year":2012,"lang":"en","type":"article","venue":"Cognitive Processing","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Syllogism; Cognitive psychology; Psychology; Valence (chemistry); Response bias; Analytic reasoning; Behavioural sciences; Social psychology; Epistemology; Artificial intelligence; Computer science; Deductive reasoning; Philosophy; Physics; Psychotherapist","score_opus":0.2911309358567643,"score_gpt":0.4497954750749713,"score_spread":0.158664539218207,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2005262305","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9934883,0.00047383396,0.002970161,0.00019458683,0.0003192261,0.00019796297,0.000039393708,0.0000585651,0.0022579657],"genre_scores_gemma":[0.9964311,0.0000044364515,0.002398635,0.0003853911,0.00012165496,0.000033202796,0.000003374706,0.00002517592,0.0005970297],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9965793,0.0006688012,0.0007654297,0.00063807564,0.000695596,0.0006528168],"domain_scores_gemma":[0.992949,0.0054525323,0.00047991448,0.00026405498,0.0006038036,0.0002506799],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.006350531,0.00025133294,0.00042763955,0.0005516408,0.0003082212,0.000550077,0.00047981972,0.00012509493,0.00014984631],"category_scores_gemma":[0.042591676,0.00020554774,0.000094735406,0.0012410327,0.00030871184,0.0011595258,0.0002203157,0.00038551103,0.00028467918],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005173819,0.00011954089,0.16238667,0.0000053598674,0.0000034416796,0.000036604353,0.0074461997,0.000017507487,0.00011837305,0.000024081894,0.000072700226,0.8292521],"study_design_scores_gemma":[0.0020196398,0.00035706063,0.87993383,0.0026079852,0.00008610762,0.00015813104,0.02279239,0.0067410846,0.0024186904,0.08082761,0.0008760081,0.0011814786],"about_ca_topic_score_codex":0.00004799515,"about_ca_topic_score_gemma":0.00009286547,"teacher_disagreement_score":0.82807064,"about_ca_system_score_codex":0.00018096689,"about_ca_system_score_gemma":0.00034427675,"threshold_uncertainty_score":0.965473},"labels":[],"label_agreement":null},{"id":"W2005512101","doi":"10.1287/mksc.1040.0109","title":"Overchoice and Assortment Type: When and Why Variety Backfires","year":2005,"lang":"en","type":"article","venue":"Marketing Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":450,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Regret; Variety (cybernetics); Set (abstract data type); Marketing; Product (mathematics); Product category; Business; Dimension (graph theory); Product type; Advertising; Computer science; Mathematics","score_opus":0.08857236628370567,"score_gpt":0.38417165942157194,"score_spread":0.29559929313786626,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2005512101","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9881569,0.00021372063,0.00017021711,0.0016467876,0.00038734358,0.00008472095,0.000004070303,0.00003128163,0.009304964],"genre_scores_gemma":[0.98522794,0.000038506492,0.0128519265,0.0008859466,0.00008877938,0.000001925157,2.5052154e-7,0.000006372811,0.0008983711],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9974266,0.00013350735,0.00040385238,0.0007669132,0.0009358419,0.00033324308],"domain_scores_gemma":[0.9968907,0.0020507285,0.00016843624,0.00046515424,0.00022016896,0.00020477048],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0135918725,0.00012925894,0.00018900176,0.00019399823,0.0005131556,0.0012302413,0.00067015213,0.000050370207,0.00029815515],"category_scores_gemma":[0.008056256,0.000096525946,0.000028844257,0.0005673089,0.0005810252,0.00082753296,0.0005290282,0.00012486184,0.000086638276],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000037346264,0.000031087562,0.055987425,0.0000016462736,0.000001926652,0.000002696038,0.0003697858,0.00003262695,0.00085190346,0.00019952188,0.010204555,0.93227947],"study_design_scores_gemma":[0.00038791017,0.00010463335,0.54519075,0.000061314066,0.000018079414,0.000063584725,0.0004304774,0.016073806,0.00028517758,0.019975392,0.41698244,0.00042640456],"about_ca_topic_score_codex":0.000050697814,"about_ca_topic_score_gemma":0.000060381586,"teacher_disagreement_score":0.93185306,"about_ca_system_score_codex":0.000074362855,"about_ca_system_score_gemma":0.000104793246,"threshold_uncertainty_score":0.9998066},"labels":[],"label_agreement":null},{"id":"W2005516635","doi":"10.1002/bdm.540","title":"Classifying simulated air threats with fast and frugal heuristics","year":2006,"lang":"en","type":"article","venue":"Journal of Behavioral Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Heuristics; Heuristic; Contrast (vision); Probabilistic logic; Constraint (computer-aided design); Task (project management); Psychology; Computer science; Cognitive psychology; Artificial intelligence; Machine learning; Mathematics; Economics","score_opus":0.09805858381858683,"score_gpt":0.4133919434235256,"score_spread":0.31533335960493875,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2005516635","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9715783,0.0003603477,0.026563434,0.000107209766,0.0008150662,0.00013427317,0.00001663844,0.00003226503,0.00039246472],"genre_scores_gemma":[0.9678869,0.000018663912,0.031527825,0.00007763676,0.0002723938,7.396703e-7,0.0000010903046,0.00004624948,0.00016849836],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9940724,0.0001471667,0.0024013496,0.00060159614,0.0023080364,0.00046946725],"domain_scores_gemma":[0.9940532,0.0018908696,0.0019231141,0.00062825816,0.0012621469,0.00024242289],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0025930663,0.00039287913,0.000947479,0.0010152505,0.00038246388,0.00090795505,0.0009096403,0.0002428072,0.00017910382],"category_scores_gemma":[0.0004804822,0.0002572459,0.0002975931,0.0008792951,0.00021696731,0.0010142243,0.00027278758,0.00064588705,0.000055842145],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005791248,0.0002847104,0.120254815,0.0000019873391,0.000009607036,0.0008585823,0.00013433486,0.01551845,0.0003150014,0.00009308269,0.0014984849,0.8604518],"study_design_scores_gemma":[0.008405733,0.0041694976,0.4777646,0.0024595847,0.00081024104,0.0073385555,0.0039243186,0.030967463,0.00048846967,0.44866797,0.012627012,0.0023765466],"about_ca_topic_score_codex":0.000026095737,"about_ca_topic_score_gemma":0.00009331981,"teacher_disagreement_score":0.85807526,"about_ca_system_score_codex":0.00016158598,"about_ca_system_score_gemma":0.00015667352,"threshold_uncertainty_score":0.99998796},"labels":[],"label_agreement":null},{"id":"W2005521174","doi":"10.1207/s15327663jcp1504_7","title":"Buyers Versus Sellers: How They Differ in Their Responses to Framed Outcomes","year":2005,"lang":"en","type":"article","venue":"Journal of Consumer Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Database transaction; Promotion (chess); Transaction cost; Economics; Microeconomics; Marketing; Business; Advertising; Computer science","score_opus":0.23289350444889675,"score_gpt":0.4811013462976919,"score_spread":0.24820784184879516,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2005521174","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.962902,0.00024198402,0.00033272483,0.032859694,0.0028086172,0.000101213715,0.000012320549,0.000010083325,0.0007313229],"genre_scores_gemma":[0.9937385,0.00009013578,0.0026892326,0.0028599962,0.00012414262,0.0000028345955,2.1231054e-7,0.000016595957,0.00047840294],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9970498,0.00046863875,0.0011539017,0.0003754463,0.00055574864,0.0003964594],"domain_scores_gemma":[0.99367607,0.0044545727,0.0006379433,0.00065742614,0.0003100276,0.00026394025],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035339496,0.00021562536,0.00074210524,0.0011815235,0.00006265301,0.00019994396,0.0011836719,0.00020061429,0.00055706874],"category_scores_gemma":[0.0042482875,0.0001350679,0.0002955638,0.00037316803,0.00013279551,0.00034912667,0.000090617126,0.00048902136,0.0005186994],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0033189019,0.0002998544,0.20750955,4.49591e-7,0.00006684385,0.00009129845,0.0015148654,0.00009712187,0.0005833068,0.000034145196,0.039067045,0.7474166],"study_design_scores_gemma":[0.005003882,0.0007099616,0.5266544,0.000036446898,0.000033039603,0.00021650172,0.0017464444,0.00004049279,0.00014706743,0.012300243,0.45275912,0.00035242064],"about_ca_topic_score_codex":0.0000051937504,"about_ca_topic_score_gemma":0.00019172927,"teacher_disagreement_score":0.7470642,"about_ca_system_score_codex":0.00009628262,"about_ca_system_score_gemma":0.00011397454,"threshold_uncertainty_score":0.6667005},"labels":[],"label_agreement":null},{"id":"W2005772722","doi":"10.1007/pl00004201","title":"Stochastically independent randomization and uncertainty aversion","year":2001,"lang":"en","type":"article","venue":"Economic Theory","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":42,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Ambiguity aversion; Preference; Knightian uncertainty; Ambiguity; Expected utility hypothesis; Econometrics; Independence (probability theory); Mathematical economics; Economics; Risk aversion (psychology); Prior probability; Subjective expected utility; Mathematics; Computer science; Microeconomics; Bayesian probability; Statistics","score_opus":0.0504129661313184,"score_gpt":0.3471142026273193,"score_spread":0.2967012364960009,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2005772722","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96394295,0.000056974397,0.0268547,0.00026616518,0.0007593033,0.00015737269,0.000013088932,0.00003699957,0.00791246],"genre_scores_gemma":[0.9977086,0.000039287872,0.0002571431,0.00022291826,0.000114546376,0.000005253256,0.0000040996024,0.00001196255,0.0016361517],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99832296,0.00019757893,0.00058746815,0.0005070333,0.00018216873,0.00020277346],"domain_scores_gemma":[0.99718565,0.0019772185,0.00021596492,0.00042635738,0.000050924613,0.00014386895],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0041403733,0.00014054695,0.00031444064,0.00021446409,0.00016678043,0.00028361435,0.0003888083,0.00010329857,0.0028656325],"category_scores_gemma":[0.00089550443,0.000111223504,0.00009503673,0.000076924436,0.00013105101,0.00033624197,0.00017526571,0.00011564488,0.0017477839],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016460607,0.000050334264,0.0033626102,7.993205e-7,0.00001660281,0.000014325767,0.00038199752,0.014651131,0.00008479097,0.037324388,0.0019156707,0.9405513],"study_design_scores_gemma":[0.0034199243,0.000086172135,0.0033510693,0.00001329267,0.000024082852,0.00007376814,0.0009703288,0.020543683,0.000031522297,0.9501463,0.021049226,0.0002905904],"about_ca_topic_score_codex":0.00001767308,"about_ca_topic_score_gemma":0.000038944756,"teacher_disagreement_score":0.9402607,"about_ca_system_score_codex":0.00012790096,"about_ca_system_score_gemma":0.0000634696,"threshold_uncertainty_score":0.99902946},"labels":[],"label_agreement":null},{"id":"W2006330681","doi":"10.1016/j.joep.2011.07.009","title":"Risky discounts: Do people prefer them on a per-item or per-purchase basis and why?","year":2011,"lang":"en","type":"article","venue":"Journal of Economic Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Mindset; Preference; Value (mathematics); Perception; Economics; Mental accounting; Prospect theory; Distribution (mathematics); Differential (mechanical device); Advertising; Actuarial science; Psychology; Microeconomics; Business; Statistics","score_opus":0.2985034151578828,"score_gpt":0.43902127049129536,"score_spread":0.14051785533341254,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2006330681","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98198575,0.000104914536,0.00032107646,0.0012026252,0.0022178781,0.00010155786,0.00003839523,0.000008329185,0.014019491],"genre_scores_gemma":[0.99580467,0.00026185173,0.0015261935,0.0013861766,0.00028202828,0.0000045015304,4.7824267e-7,0.00002481416,0.00070930994],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99719256,0.00018779507,0.001479372,0.0005790505,0.00023169458,0.00032954753],"domain_scores_gemma":[0.9966777,0.00099586,0.0011819026,0.0007366488,0.00013703939,0.00027084257],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002729068,0.00024655985,0.00075782154,0.00049095036,0.00012920726,0.000232125,0.001030889,0.00019505223,0.012017657],"category_scores_gemma":[0.0005334456,0.00015580255,0.00026249417,0.00010176331,0.00018037396,0.0006059409,0.0001238969,0.00039087515,0.0018115904],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003949249,0.00084356824,0.12856139,0.00000375189,0.00012638432,0.00011798068,0.005070325,0.000037696736,0.000104840234,0.00094466616,0.07232249,0.7879177],"study_design_scores_gemma":[0.007951458,0.005768092,0.35996363,0.00014891739,0.00021474817,0.0067565497,0.007283636,0.00045950155,0.00013511284,0.29221064,0.31785533,0.0012523927],"about_ca_topic_score_codex":0.000026449361,"about_ca_topic_score_gemma":0.0001462887,"teacher_disagreement_score":0.78666526,"about_ca_system_score_codex":0.000110870475,"about_ca_system_score_gemma":0.00011080056,"threshold_uncertainty_score":0.9989656},"labels":[],"label_agreement":null},{"id":"W2007402403","doi":"10.1016/j.econlet.2012.08.011","title":"Utility of a quarter-million","year":2012,"lang":"en","type":"article","venue":"Economics Letters","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Bernoulli's principle; Range (aeronautics); Taylor series; Function (biology); Econometrics; Economics; Computer science; Mathematical economics; Taylor rule; Monetary policy; Mathematics; Keynesian economics; Engineering; Geography","score_opus":0.12999314181060748,"score_gpt":0.3608629765096567,"score_spread":0.23086983469904923,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2007402403","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9922726,0.00003674237,0.0011564486,0.0014099649,0.0014159852,0.00008463402,0.000029081253,0.00001858534,0.0035759495],"genre_scores_gemma":[0.9975058,0.000006279088,0.0012378546,0.0010095001,0.00016739043,0.0000028219247,0.0000028245288,0.000010969059,0.000056598445],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9982473,0.000077902696,0.00086725893,0.0003276551,0.00016155056,0.0003183168],"domain_scores_gemma":[0.99805653,0.00056475255,0.0004148773,0.00076702866,0.00004626706,0.0001505334],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002114653,0.00013574363,0.0003564304,0.00023607112,0.00006381589,0.000099056655,0.00058882823,0.000072650364,0.0007231172],"category_scores_gemma":[0.00024750363,0.000117975906,0.00020930592,0.00015098063,0.00011666992,0.00061816676,0.00010730391,0.000105268475,0.00083448074],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000069230286,0.00021642231,0.36964086,0.0000032636337,0.000022428316,0.0000013988495,0.0010889707,0.0002049793,0.0018557322,0.0012488746,0.055014253,0.5706336],"study_design_scores_gemma":[0.0016186045,0.00015857666,0.6313407,0.000033386903,0.00006449372,0.000053742555,0.003247987,0.0069669923,0.009205683,0.05630468,0.28974184,0.0012632933],"about_ca_topic_score_codex":0.000027382699,"about_ca_topic_score_gemma":0.000015891486,"teacher_disagreement_score":0.56937027,"about_ca_system_score_codex":0.000036039182,"about_ca_system_score_gemma":0.00002425909,"threshold_uncertainty_score":0.9999435},"labels":[],"label_agreement":null},{"id":"W2007991621","doi":"10.1001/archneur.57.12.1791","title":"Comment on Berry and Hachinski","year":2000,"lang":"en","type":"article","venue":"Archives of Neurology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Berry; Botany; Biology","score_opus":0.08023214505637993,"score_gpt":0.3630877879362251,"score_spread":0.28285564287984516,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2007991621","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9636923,0.000025095183,0.000038189934,0.014820276,0.00012409991,0.00005318502,0.000011420286,0.000010979454,0.021224422],"genre_scores_gemma":[0.9907817,0.000040158353,0.00048733453,0.0084208315,0.000021517748,0.0000017687663,8.939181e-7,0.0000058533674,0.0002399255],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988359,0.0001677053,0.00034989585,0.00033679118,0.00016763277,0.00014206045],"domain_scores_gemma":[0.9969706,0.0024623645,0.000089602305,0.0004019068,0.000007803779,0.00006773084],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002831226,0.0000837624,0.00022128514,0.00016138413,0.00006529745,0.000027163784,0.00038025374,0.00003442548,0.00042784153],"category_scores_gemma":[0.00017297178,0.0000621761,0.00006368342,0.00006364299,0.0002499465,0.00004823751,0.00009495677,0.00013902814,0.00017173613],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021551701,0.000082395854,0.0050895913,3.3634856e-7,0.0000019012691,0.000011768274,0.00020295693,0.00012649695,0.0000883652,0.0010587074,0.0020352092,0.9910868],"study_design_scores_gemma":[0.00054259266,0.0014341733,0.16902363,0.000005677247,0.0000067762116,0.000054229997,0.000022968443,0.002417078,0.000112135785,0.3784405,0.44782025,0.00012000541],"about_ca_topic_score_codex":0.000017664957,"about_ca_topic_score_gemma":0.000009756778,"teacher_disagreement_score":0.99096674,"about_ca_system_score_codex":9.460057e-7,"about_ca_system_score_gemma":0.000008425161,"threshold_uncertainty_score":0.46845645},"labels":[],"label_agreement":null},{"id":"W2008579124","doi":"10.1017/s0140525x03240115","title":"The rationality debate as a progressive research program","year":2003,"lang":"en","type":"article","venue":"Behavioral and Brain Sciences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Rationality; Irrational number; Heuristics; Ecological rationality; Epistemology; Theme (computing); Irrationality; Point (geometry); Mathematical economics; Computer science; Psychology; Positive economics; Economics; Philosophy; Mathematics","score_opus":0.47192109140994104,"score_gpt":0.5840468023299901,"score_spread":0.11212571092004903,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008579124","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9885729,0.0004358473,0.00001107677,0.0048355768,0.0003570308,0.000510659,0.0000073167503,0.000043525197,0.005226054],"genre_scores_gemma":[0.99577034,0.000015400252,0.0015852208,0.00017788477,0.000046318557,0.00012526821,0.0000010565286,0.0000058878773,0.002272609],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9950168,0.0008349163,0.00059221865,0.0008124547,0.0021496874,0.00059388526],"domain_scores_gemma":[0.9954304,0.0031084593,0.00019807868,0.00046695847,0.0005807034,0.00021537006],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":["sts"],"category_scores_codex":[0.019311648,0.00015509738,0.00020635461,0.00020071202,0.0031315114,0.00318268,0.001132605,0.00008662943,0.00023289307],"category_scores_gemma":[0.0045812693,0.00007837374,0.00009286132,0.0015752255,0.0030040957,0.00058462186,0.00022666187,0.00026223643,0.00024005651],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016096767,0.00021005019,0.01703688,4.928707e-7,0.000001369109,0.000019824256,0.00030289797,0.0000029802404,0.00012616327,0.019705521,0.005975077,0.95660263],"study_design_scores_gemma":[0.00030517805,0.0011482829,0.017810075,0.00002231331,0.000008277866,0.000153607,0.005639287,0.00020768806,0.0005814157,0.64597154,0.32784912,0.00030318912],"about_ca_topic_score_codex":0.000110209556,"about_ca_topic_score_gemma":0.00018152731,"teacher_disagreement_score":0.9562995,"about_ca_system_score_codex":0.00003392804,"about_ca_system_score_gemma":0.0003979897,"threshold_uncertainty_score":0.9997091},"labels":[],"label_agreement":null},{"id":"W2009241456","doi":"10.1086/599045","title":"The Influence of Categorical Attributes on Choice Context Effects","year":2009,"lang":"en","type":"article","venue":"Journal of Consumer Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Categorical variable; Context (archaeology); Library science; Psychology; Sociology; Advertising; Computer science; History; Business","score_opus":0.26603361681559656,"score_gpt":0.5172143874819393,"score_spread":0.2511807706663427,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2009241456","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9946285,0.0011396338,0.000034027915,0.0034003137,0.00024561153,0.00013011177,0.0000024035608,0.0000032213281,0.0004161794],"genre_scores_gemma":[0.9992567,0.00018872299,0.00004923447,0.00014950306,0.000077596706,0.0000012445548,8.2720234e-8,0.0000051775773,0.0002717542],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99487734,0.00076303445,0.0011248735,0.0002068773,0.002655317,0.00037254908],"domain_scores_gemma":[0.9674513,0.028501209,0.00056836713,0.0005643236,0.0026976513,0.00021716389],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01298992,0.00010729168,0.00042060993,0.00048886694,0.00031511154,0.0003760795,0.0016828598,0.00008842546,0.000034591696],"category_scores_gemma":[0.031299163,0.000054874763,0.00019675838,0.0008402487,0.0004008889,0.0002936988,0.000103793514,0.0008637626,0.00026169818],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035299166,0.00019164401,0.013478482,0.0000020396337,0.000018583556,0.000072399605,0.000108506996,0.00019469085,0.001941313,0.001459675,0.023296982,0.9588827],"study_design_scores_gemma":[0.001842921,0.0038704034,0.49087164,0.0002537523,0.00002987523,0.00019492483,0.00052485534,0.00015082161,0.008578557,0.22145446,0.27198195,0.0002458353],"about_ca_topic_score_codex":0.000031694817,"about_ca_topic_score_gemma":0.000017452074,"teacher_disagreement_score":0.9586369,"about_ca_system_score_codex":0.00008910001,"about_ca_system_score_gemma":0.00033274546,"threshold_uncertainty_score":0.97686064},"labels":[],"label_agreement":null},{"id":"W2009706815","doi":"10.1016/j.jcps.2010.06.019","title":"The influence of involvement on the endowment effect: The moveable value function","year":2010,"lang":"en","type":"article","venue":"Journal of Consumer Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; University of Manitoba","funders":"","keywords":"Endowment effect; Loss aversion; Moderation; Psychology; Value (mathematics); Context (archaeology); Endowment; Function (biology); Economics; Negativity effect; Prospect theory; Arousal; Risk-seeking; Microeconomics; Social psychology","score_opus":0.06578126432249025,"score_gpt":0.40464076763814,"score_spread":0.33885950331564973,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2009706815","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9876438,0.00020060297,0.00011363024,0.0068755923,0.0034706153,0.00019254706,0.0000023089624,0.0000031408742,0.0014978104],"genre_scores_gemma":[0.99729383,0.00009052947,0.000053931388,0.0023010995,0.000098836244,0.000008235372,7.580311e-8,0.0000065351664,0.00014689934],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99727476,0.00050515763,0.0010535525,0.00019270788,0.00077202916,0.00020179572],"domain_scores_gemma":[0.9902343,0.0071373945,0.0012207526,0.00092088134,0.00042300948,0.000063668194],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010144999,0.0001269427,0.00028031997,0.00012723537,0.00031996606,0.00015307916,0.0014202177,0.000091241534,0.00019896994],"category_scores_gemma":[0.0022052168,0.00004479765,0.00021089285,0.00025656805,0.00047099573,0.00012613198,0.00008358674,0.0007025999,0.00018770272],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012965329,0.0003417081,0.039513502,0.0000018474119,0.0001636606,0.000013190794,0.0004604239,0.001422098,0.02626333,0.012545333,0.056478456,0.8614999],"study_design_scores_gemma":[0.0013960835,0.0019535252,0.2764664,0.000044932767,0.000117831914,0.00017104943,0.00043231304,0.000105459694,0.002485755,0.22701545,0.48964867,0.0001625126],"about_ca_topic_score_codex":0.000017318804,"about_ca_topic_score_gemma":0.000041480074,"teacher_disagreement_score":0.8613374,"about_ca_system_score_codex":0.000019016114,"about_ca_system_score_gemma":0.00007404338,"threshold_uncertainty_score":0.35160744},"labels":[],"label_agreement":null},{"id":"W2010899313","doi":"10.1016/s0165-4896(99)00055-4","title":"Separable and additive representations of binary gambles of gains","year":2000,"lang":"en","type":"article","venue":"Mathematical Social Sciences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Separable space; Representation (politics); Differentiable function; Monotonic function; Mathematics; Binary number; Additive function; Rank (graph theory); Consistency (knowledge bases); Function (biology); Mathematical economics; Discrete mathematics; Pure mathematics; Combinatorics; Arithmetic","score_opus":0.2351220511006282,"score_gpt":0.4872952272806448,"score_spread":0.25217317618001656,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2010899313","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94734293,0.000026843167,0.0001228192,0.00039318626,0.000030197572,0.00008087639,0.00004277644,0.00000943169,0.051950924],"genre_scores_gemma":[0.9954395,0.000014485098,0.0037211757,0.000030628726,0.000021827656,0.000004241952,6.0015594e-7,0.0000026997827,0.0007648092],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99817455,0.00009181284,0.00059231644,0.00027532727,0.00070648955,0.00015948196],"domain_scores_gemma":[0.9977807,0.0017126091,0.00020941129,0.0001435465,0.00010221791,0.00005151217],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0017693602,0.00007459131,0.00031851575,0.0001085202,0.00028169644,0.00008629388,0.00041379587,0.00005251915,0.0037459624],"category_scores_gemma":[0.0009850292,0.000050605708,0.00009308315,0.0006976809,0.0013214435,0.00025897176,0.00007252752,0.000047457113,0.00009436172],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000047310365,0.0006596436,0.0063911127,0.000019380657,0.000018290017,0.0000053579365,0.008777833,0.00023938823,0.0017036677,0.078947805,0.010260388,0.8929298],"study_design_scores_gemma":[0.00013709432,0.00013356935,0.01600592,0.000034905894,0.00001584227,0.000004035885,0.0041578067,0.0024769937,0.00072464405,0.9749628,0.0012340173,0.00011241423],"about_ca_topic_score_codex":0.000046262758,"about_ca_topic_score_gemma":0.000010586512,"teacher_disagreement_score":0.8960149,"about_ca_system_score_codex":0.000009176621,"about_ca_system_score_gemma":0.00005535428,"threshold_uncertainty_score":0.9971647},"labels":[],"label_agreement":null},{"id":"W2011424025","doi":"10.1080/00036840500392391","title":"The prevalence of hyperbolic discounting: some European evidence","year":2006,"lang":"en","type":"article","venue":"Applied Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":39,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Banca d'Italia","keywords":"Hyperbolic discounting; Economics; Matching (statistics); Quarter (Canadian coin); Demographic economics; Household income; Econometrics; Discounting; Mathematics; Geography; Statistics","score_opus":0.0970031242518656,"score_gpt":0.3340430994324108,"score_spread":0.2370399751805452,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2011424025","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9777438,0.00038615245,0.00011818196,0.00035364827,0.0004269989,0.00016803945,0.000019308947,0.000029803103,0.02075409],"genre_scores_gemma":[0.9972984,0.00034463644,0.00040256645,0.00012473558,0.0002589673,0.00000905244,0.0000010276916,0.000024545743,0.0015360325],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99757737,0.00007052367,0.0012099835,0.00057328533,0.00024893007,0.00031989938],"domain_scores_gemma":[0.99585104,0.0020884096,0.00072455057,0.0011948682,0.00007778242,0.00006335995],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0038323656,0.0001782953,0.00030462642,0.00010334727,0.00029270473,0.00047530606,0.0018279733,0.000052972635,0.000078719706],"category_scores_gemma":[0.00038583513,0.00012227823,0.00014843588,0.00016928918,0.0003187138,0.00045784755,0.00036083785,0.00013671962,0.0011618285],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000097990574,0.0001309762,0.022623088,0.000020848238,0.000015320415,0.0000023872217,0.00020642388,0.007976578,0.0016055241,0.15356624,0.0067184824,0.80703616],"study_design_scores_gemma":[0.0004591442,0.00006659974,0.16677104,0.000056160272,0.000054666052,0.000014484138,0.00040376157,0.0016398169,0.0026073244,0.7353533,0.09197088,0.00060280197],"about_ca_topic_score_codex":0.00003809484,"about_ca_topic_score_gemma":0.00004223127,"teacher_disagreement_score":0.8064333,"about_ca_system_score_codex":0.00005915407,"about_ca_system_score_gemma":0.00006631004,"threshold_uncertainty_score":0.9996159},"labels":[],"label_agreement":null},{"id":"W2012021772","doi":"10.7771/1932-6246.1119","title":"Book Review of Rosenhouse, The Monty Hall Problem","year":2012,"lang":"en","type":"article","venue":"The Journal of Problem Solving","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"History","score_opus":0.09142991047685242,"score_gpt":0.37379934551963934,"score_spread":0.2823694350427869,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2012021772","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1358272,0.8266325,0.0041934787,0.017652547,0.0015031638,0.001089054,0.000012305372,0.000031575706,0.013058181],"genre_scores_gemma":[0.91541386,0.058264047,0.01094209,0.010439853,0.0007915126,0.000007838681,4.802648e-7,0.0000669481,0.004073384],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99581134,0.00055582996,0.0019723056,0.00012976599,0.0011738947,0.00035686474],"domain_scores_gemma":[0.9938507,0.0020709324,0.0025328023,0.00072160125,0.0006893475,0.00013460018],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.022147017,0.00016925906,0.00056705036,0.00012553405,0.00025259453,0.00012232512,0.0018484498,0.000061962935,0.0007684363],"category_scores_gemma":[0.0013659123,0.00007102157,0.00033530223,0.00040604887,0.00014898564,0.0009036515,0.00028429757,0.00046418144,0.0001231725],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007627557,0.0002473185,0.0017962957,0.00021754004,0.000065400454,0.000005779277,0.004568691,0.0005950672,0.0011422081,0.0003500425,0.7707152,0.2202202],"study_design_scores_gemma":[0.000821255,0.0005199628,0.004311547,0.010751625,0.00057267974,0.0013968777,0.0021887203,0.00033549385,0.001400106,0.07474223,0.90241766,0.00054182595],"about_ca_topic_score_codex":0.000021425034,"about_ca_topic_score_gemma":0.0000067481265,"teacher_disagreement_score":0.7795867,"about_ca_system_score_codex":0.00006147087,"about_ca_system_score_gemma":0.00013966417,"threshold_uncertainty_score":0.8413839},"labels":[],"label_agreement":null},{"id":"W2012493037","doi":"10.1037//0278-7393.26.1.28","title":"Probability judgment in three-category classification learning.","year":2000,"lang":"en","type":"article","venue":"Journal of Experimental Psychology Learning Memory and Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Subadditivity; Psychology; Cognitive psychology; Context (archaeology); Context effect; Set (abstract data type); Cognition; Counterintuitive; Social psychology; Mathematics; Computer science; Combinatorics","score_opus":0.20659909491471232,"score_gpt":0.4234373883273,"score_spread":0.21683829341258767,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2012493037","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98512477,0.00045315764,0.00018196121,0.00043017906,0.00027689233,0.00011934668,5.3049837e-7,0.000013864964,0.013399292],"genre_scores_gemma":[0.99900347,0.00007905067,0.000317412,0.00021183278,0.00007792514,0.0000075397297,0.0000028883535,0.0000095023315,0.00029036732],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9975349,0.0005176049,0.0009899879,0.00037796612,0.00039694432,0.0001826387],"domain_scores_gemma":[0.9987228,0.00032472427,0.0005565427,0.00016106784,0.00013381994,0.00010108284],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0031201965,0.00013978175,0.00032196668,0.00030411742,0.00017279031,0.000111911926,0.00022886993,0.00014661031,0.0019667235],"category_scores_gemma":[0.00035056783,0.00011496512,0.000109431334,0.00024106631,0.00018696858,0.00045621707,0.000027620015,0.0006729115,0.00018271596],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010385656,0.0007268106,0.022741217,0.000001908225,0.000012788774,0.000035541427,0.0010082688,0.00066423096,0.024031077,0.000049536062,0.00022974101,0.9494603],"study_design_scores_gemma":[0.010170317,0.007247192,0.67172664,0.00028279505,0.00010069261,0.0017167111,0.017890597,0.003532828,0.009974209,0.25473207,0.021574864,0.0010510769],"about_ca_topic_score_codex":0.000004025601,"about_ca_topic_score_gemma":0.000004929014,"teacher_disagreement_score":0.94840926,"about_ca_system_score_codex":0.000061819184,"about_ca_system_score_gemma":0.00003134494,"threshold_uncertainty_score":0.9989456},"labels":[],"label_agreement":null},{"id":"W2013222865","doi":"10.1111/1468-5876.00194","title":"Solutions For Some Dynamic Problems With Uncertainty Aversion","year":2001,"lang":"en","type":"article","venue":"Japanese Economic Review","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Economics; Operator (biology); Mathematical economics; Choquet integral; Investment (military); Risk aversion (psychology); Ambiguity aversion; Loss aversion; Expected utility hypothesis; Mathematical optimization; Econometrics; Mathematics; Microeconomics; Computer science","score_opus":0.12817197489065418,"score_gpt":0.3835525774052029,"score_spread":0.2553806025145487,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2013222865","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9586742,0.023096718,0.0007629673,0.008352272,0.0014633433,0.002971196,0.00016633651,0.00014845384,0.004364495],"genre_scores_gemma":[0.93845457,0.04555516,0.001313794,0.0030193732,0.0003025477,0.00053462456,0.00010809245,0.000088014654,0.010623817],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99712014,0.00010114288,0.0011682617,0.00083543104,0.0002536702,0.00052133534],"domain_scores_gemma":[0.9971801,0.0008230314,0.00058966945,0.001079389,0.00013826088,0.00018955123],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0035392176,0.00027260673,0.00082630164,0.00018972541,0.0003406693,0.00023469876,0.00090694736,0.00008077259,0.0010569379],"category_scores_gemma":[0.0004048021,0.00018378181,0.00035727647,0.00024940836,0.00011650227,0.0007285975,0.00015363072,0.00013401017,0.0032868313],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009258572,0.00014117402,0.00045516432,0.0002014826,0.00004119879,0.000011324568,0.0001649224,0.009416473,0.000022311055,0.00100928,0.04474869,0.94369537],"study_design_scores_gemma":[0.00090334984,0.000279959,0.0003040659,0.0012994551,0.00012156888,0.00022975262,0.00028251848,0.023857405,0.0000014324834,0.04150234,0.93062997,0.0005881584],"about_ca_topic_score_codex":0.0000721698,"about_ca_topic_score_gemma":0.00030406093,"teacher_disagreement_score":0.94310725,"about_ca_system_score_codex":0.00036808426,"about_ca_system_score_gemma":0.00017541027,"threshold_uncertainty_score":0.99985623},"labels":[],"label_agreement":null},{"id":"W2013660131","doi":"10.1002/bdm.683","title":"A choice prediction competition: Choices from experience and from description","year":2009,"lang":"en","type":"article","venue":"Journal of Behavioral Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":340,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Waterloo","funders":"Harvard Business School; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Stochastic game; Competition (biology); Robustness (evolution); Computer science; Set (abstract data type); Baseline (sea); Econometrics; Operations research; Artificial intelligence; Psychology; Economics; Mathematics; Mathematical economics; Political science","score_opus":0.1433559998342561,"score_gpt":0.42074730310549663,"score_spread":0.2773913032712405,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2013660131","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9759563,0.00051356916,0.020810323,0.00014700057,0.002203128,0.00011813662,0.00008815348,0.000034667144,0.0001287289],"genre_scores_gemma":[0.9707935,0.00007094371,0.02813558,0.0002727015,0.0006737429,0.0000019462718,0.0000048699944,0.000015703754,0.000031010706],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9946666,0.00018277344,0.0022254759,0.0006459431,0.0019871292,0.0002920855],"domain_scores_gemma":[0.9948398,0.0018866425,0.0016766319,0.0006055871,0.00072090625,0.00027043387],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0015139522,0.00029726076,0.0007176154,0.0006446995,0.0003299964,0.0014464705,0.0009719542,0.00023115698,0.00082352647],"category_scores_gemma":[0.001158228,0.00022983745,0.00029420241,0.0005556525,0.0001206301,0.002702948,0.00015130057,0.00048074286,0.00006832281],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026986096,0.00022026486,0.07419473,2.7595792e-7,0.000005588207,0.00007879453,0.0008399134,0.00016268613,0.0053521725,0.000028842573,0.0008376809,0.9180092],"study_design_scores_gemma":[0.0012630136,0.00069756183,0.8201799,0.00056537025,0.00011281692,0.00014744549,0.0015993519,0.0017521136,0.00027392004,0.16378197,0.009286573,0.0003399665],"about_ca_topic_score_codex":0.0001136052,"about_ca_topic_score_gemma":0.00007630166,"teacher_disagreement_score":0.91766924,"about_ca_system_score_codex":0.00016277489,"about_ca_system_score_gemma":0.00006606347,"threshold_uncertainty_score":0.9995901},"labels":[],"label_agreement":null},{"id":"W2014518776","doi":"10.3758/bf03194383","title":"Is probability matching smart? Associations between probabilistic choices and cognitive ability","year":2003,"lang":"en","type":"article","venue":"Memory & Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":140,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Heuristics; Probabilistic logic; Matching (statistics); Psychology; Task (project management); Cognition; Cognitive psychology; Interpretation (philosophy); Artificial intelligence; Statistics; Computer science; Mathematics","score_opus":0.17002629189211088,"score_gpt":0.39274179217563027,"score_spread":0.22271550028351939,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2014518776","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9870104,0.000043019507,0.000996761,0.0003104895,0.00024357012,0.00071997254,0.00046085537,0.00008287547,0.010132045],"genre_scores_gemma":[0.99849695,0.000003074464,0.00086815277,0.0002611011,0.00006558082,0.00005203713,0.00005354627,0.000016307426,0.00018324971],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99623686,0.0006660616,0.0010031089,0.0009788539,0.00077760516,0.00033749946],"domain_scores_gemma":[0.9934199,0.0046443515,0.0005050281,0.0004440843,0.0007967978,0.00018985063],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.005612296,0.00024367419,0.0004951595,0.00018898047,0.0005354757,0.00053754234,0.00024226171,0.000178955,0.0006181297],"category_scores_gemma":[0.011557452,0.00021130129,0.00015787169,0.00050702866,0.00027039016,0.0007339645,0.00009436981,0.00029092585,0.0003821779],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006167129,0.000657961,0.3396564,0.000039050206,0.00008274161,0.000006617368,0.0025878847,0.000024740792,0.00041099696,0.00033654098,0.00066869764,0.6554667],"study_design_scores_gemma":[0.0005364369,0.00008155807,0.41595572,0.000051982206,0.00017013261,0.000005513934,0.0006854446,0.00004290943,0.00059023144,0.58088225,0.0007102962,0.00028753784],"about_ca_topic_score_codex":0.00006566386,"about_ca_topic_score_gemma":0.00014462741,"teacher_disagreement_score":0.65517914,"about_ca_system_score_codex":0.00011648398,"about_ca_system_score_gemma":0.00012943434,"threshold_uncertainty_score":0.9967686},"labels":[],"label_agreement":null},{"id":"W2014960425","doi":"10.1002/bdm.583","title":"Subjective valuation and asymmetrical motivational systems: implications of scope insensitivity for decision making","year":2007,"lang":"en","type":"article","venue":"Journal of Behavioral Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Université Laval","funders":"Social Sciences and Humanities Research Council of Canada; McGill University; Canadian Institutes of Health Research; Université Laval","keywords":"Valuation (finance); Feeling; Psychology; Social psychology; Cognitive psychology; Scope (computer science); Computer science; Economics","score_opus":0.18786858322453592,"score_gpt":0.47161238862498295,"score_spread":0.283743805400447,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2014960425","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5704291,0.00022412078,0.4280619,0.000040854342,0.0007635148,0.0003653059,0.00004003363,0.000009135639,0.00006605328],"genre_scores_gemma":[0.8635279,0.00001733032,0.13615842,0.00005119238,0.00019725105,0.000007173794,0.0000017002571,0.0000302438,0.000008792352],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9925492,0.00022774085,0.0037713696,0.0006363498,0.00238699,0.00042837102],"domain_scores_gemma":[0.96714765,0.02353138,0.0034774507,0.00060295995,0.0050135404,0.0002270419],"candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0145827085,0.00031889108,0.0010223535,0.0026023989,0.00038149237,0.00057802605,0.0007700843,0.0003093254,0.00005382835],"category_scores_gemma":[0.013303233,0.0002512123,0.0004840639,0.0018056037,0.00017276384,0.0013145467,0.00028009998,0.00040870204,0.000013874802],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006801576,0.00030187436,0.061153423,0.000004979019,0.0000147756755,0.00001612848,0.00018184967,0.0011679513,0.0013130368,0.00068085256,0.0005847338,0.93390024],"study_design_scores_gemma":[0.0010921282,0.00074362906,0.73994815,0.0009456395,0.0001333978,0.00050451513,0.0011784569,0.0028272464,0.00025524764,0.25176048,0.00028918806,0.00032192364],"about_ca_topic_score_codex":0.000018968936,"about_ca_topic_score_gemma":0.000044552224,"teacher_disagreement_score":0.9335783,"about_ca_system_score_codex":0.00040047447,"about_ca_system_score_gemma":0.00026606963,"threshold_uncertainty_score":0.99999404},"labels":[],"label_agreement":null},{"id":"W2015104885","doi":"10.1037/a0030518","title":"Optimal weighting of costs and probabilities in a risky motor decision-making task requires experience.","year":2012,"lang":"en","type":"article","venue":"Journal of Experimental Psychology Human Perception & Performance","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Ontario Ministry of Research and Innovation; Natural Sciences and Engineering Research Council of Canada","keywords":"Weighting; Task (project management); Selection (genetic algorithm); Point (geometry); Stochastic game; Event (particle physics); Statistics; Clinical endpoint; Computer science; Psychology; Econometrics; Mathematics; Economics; Artificial intelligence; Randomized controlled trial","score_opus":0.09468109097173782,"score_gpt":0.45230257292173215,"score_spread":0.3576214819499943,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2015104885","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9973828,0.00066816685,0.00023360408,0.000046404246,0.00092453166,0.00017029302,0.0000044688836,0.000009375276,0.0005603563],"genre_scores_gemma":[0.9899668,0.00010705959,0.009496914,0.000118908974,0.00023960347,0.000012534966,6.005161e-7,0.00001785729,0.00003968468],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99622303,0.00017554444,0.0020631095,0.00038757778,0.00073818903,0.00041253425],"domain_scores_gemma":[0.9975556,0.00042106266,0.0012143713,0.0004231507,0.00022256657,0.0001632473],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002943054,0.00024287066,0.0006223271,0.00081094675,0.00023153787,0.00010968683,0.0006599294,0.00017493701,0.0008971953],"category_scores_gemma":[0.00031151652,0.00017302479,0.00017845447,0.00030731133,0.0005583444,0.0020508692,0.00018223345,0.0003619126,0.000037309364],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018129419,0.0012976709,0.4913732,0.00001025505,0.000019600346,0.000013892202,0.037461985,0.00020472094,0.21955183,0.000096036434,0.0010823722,0.24707548],"study_design_scores_gemma":[0.0022029683,0.0022657032,0.9492748,0.0006342353,0.000018649926,0.00078732433,0.037131477,0.00095558935,0.0028192652,0.001957149,0.0014444975,0.00050835527],"about_ca_topic_score_codex":0.000006853223,"about_ca_topic_score_gemma":0.000004762423,"teacher_disagreement_score":0.4579016,"about_ca_system_score_codex":0.00023509114,"about_ca_system_score_gemma":0.00003246546,"threshold_uncertainty_score":0.9823659},"labels":[],"label_agreement":null},{"id":"W2015135931","doi":"10.4236/ojpsych.2013.31005","title":"Variation in the &amp;lt;i&amp;gt;DRD2&amp;lt;/i&amp;gt; gene affects impulsivity in intertemporal choice","year":2013,"lang":"en","type":"article","venue":"Open Journal of Psychiatry","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"Japan Society for the Promotion of Science; Ministry of Education, Culture, Sports, Science and Technology","keywords":"Impulsivity; Single-nucleotide polymorphism; Dopaminergic; Intertemporal choice; Dopamine receptor D2; Delay discounting; Psychology; Neuroeconomics; Discounting; Internal medicine; Endocrinology; Dopamine; Genetics; Biology; Medicine; Gene; Economics; Developmental psychology; Econometrics; Genotype; Neuroscience","score_opus":0.11457674586613241,"score_gpt":0.4089607049941456,"score_spread":0.2943839591280132,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2015135931","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9806469,0.0004949925,0.0027874885,0.007702248,0.0049324385,0.00067229,0.000019725776,0.000010999007,0.0027329293],"genre_scores_gemma":[0.9648701,0.000042771695,0.032155413,0.0011646345,0.000697385,0.00002281505,0.000010430264,0.000039195602,0.0009972404],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9935707,0.0012353008,0.002408819,0.0007229383,0.0014577234,0.00060451083],"domain_scores_gemma":[0.9939756,0.0016293238,0.0021716077,0.0014614428,0.00046889271,0.00029315086],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0115993265,0.00042191724,0.0009771517,0.0009082257,0.00025197997,0.0023742435,0.0044041867,0.0002929488,0.0022851385],"category_scores_gemma":[0.0021473207,0.0002779207,0.00040858504,0.00141377,0.00011401299,0.0026288568,0.00053611293,0.0010176464,0.0018760572],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00064569304,0.0029587117,0.35958776,0.000022753697,0.00011628074,0.000035308098,0.005685575,0.0015350373,0.011285389,0.0007057568,0.31796637,0.29945534],"study_design_scores_gemma":[0.0038050478,0.0003996348,0.69147265,0.0005403104,0.000094581555,0.0005671949,0.0005791446,0.00018375166,0.000022016731,0.1275262,0.17393643,0.00087304163],"about_ca_topic_score_codex":0.0006613849,"about_ca_topic_score_gemma":0.018879758,"teacher_disagreement_score":0.33188492,"about_ca_system_score_codex":0.00021163105,"about_ca_system_score_gemma":0.00048342062,"threshold_uncertainty_score":0.9999673},"labels":[],"label_agreement":null},{"id":"W2015261885","doi":"10.1177/0963721413480172","title":"The Common Currency of Psychological Distance","year":2013,"lang":"en","type":"article","venue":"Current Directions in Psychological Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":83,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Wonder; Distancing; Social distance; Construal level theory; Psychology; Construct (python library); Social psychology; Common currency; Cognitive psychology; Currency; Coronavirus disease 2019 (COVID-19); Computer science","score_opus":0.23367826120475063,"score_gpt":0.538267310469019,"score_spread":0.30458904926426833,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2015261885","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9778531,0.00077008066,0.0007349377,0.0006713069,0.0051506087,0.00031029072,0.000008624254,0.000048305432,0.014452735],"genre_scores_gemma":[0.9989329,0.00038816858,0.0003915844,0.000048138438,0.0000483674,0.000081553764,5.379229e-7,0.0000038692856,0.00010487779],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99588203,0.00024046781,0.0011870161,0.001019163,0.0011237249,0.00054757245],"domain_scores_gemma":[0.99608284,0.001753719,0.00037707682,0.0012165932,0.00037429784,0.00019549279],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0043904977,0.00017934402,0.00033505945,0.00031320544,0.00068401784,0.000500712,0.0029992869,0.000088631125,0.000546591],"category_scores_gemma":[0.0041889246,0.00009207978,0.00015801546,0.0040733414,0.002704093,0.00055310305,0.00028559996,0.0004872016,0.00067287707],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010085126,0.00057636324,0.047276255,3.5906353e-7,3.7659106e-7,6.4421926e-7,0.000038678932,0.000016288412,0.00013555691,0.0033512616,0.004059459,0.94453466],"study_design_scores_gemma":[0.00019378334,0.00015705373,0.6071618,0.000029939354,0.000002179582,0.000012707994,0.0001577363,0.0006354824,0.000035867564,0.34100783,0.050424393,0.00018119758],"about_ca_topic_score_codex":0.000024364394,"about_ca_topic_score_gemma":0.00004239166,"teacher_disagreement_score":0.94435346,"about_ca_system_score_codex":0.00009149741,"about_ca_system_score_gemma":0.000026323321,"threshold_uncertainty_score":0.9963344},"labels":[],"label_agreement":null},{"id":"W2015391868","doi":"10.1080/09297040600762701","title":"Developmental and Gender Differences in Future-Oriented Decision-Making During the Preschool Period","year":2006,"lang":"en","type":"article","venue":"Child Neuropsychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Psychology; Task (project management); Developmental psychology; Period (music); Deck","score_opus":0.040883355866788255,"score_gpt":0.33120695763893493,"score_spread":0.29032360177214667,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2015391868","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99228275,0.00025926187,0.00019979055,0.00073527585,0.0012425652,0.00021373619,0.000008843265,0.000038955302,0.00501885],"genre_scores_gemma":[0.9982912,0.00003288945,0.00072902563,0.0005312388,0.00027819144,0.00001424914,8.790405e-7,0.0000204164,0.00010194437],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.997039,0.00025045054,0.0008844125,0.0009402601,0.00047869197,0.0004071745],"domain_scores_gemma":[0.99834275,0.00082698296,0.00022999752,0.000466282,0.00006145025,0.0000725073],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00076018757,0.00024810413,0.00036924944,0.00038807912,0.00045178388,0.00030434638,0.00081886136,0.00012850674,0.00032136225],"category_scores_gemma":[0.00060159626,0.00015548726,0.00008542621,0.0006018618,0.00022794893,0.00022901077,0.00033153556,0.00043762045,0.00014656586],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027381376,0.00022673981,0.7108185,0.000002600337,0.000008141878,0.00025134516,0.0009948523,0.000049673017,0.00054034154,0.0008613807,0.0015455022,0.2844271],"study_design_scores_gemma":[0.0005576726,0.00003219558,0.97449684,0.00001788875,0.0000042969727,0.00069570064,0.0005066728,0.00007255512,0.000011703913,0.017819926,0.0055980776,0.00018644308],"about_ca_topic_score_codex":0.000008342662,"about_ca_topic_score_gemma":0.00010506136,"teacher_disagreement_score":0.28424066,"about_ca_system_score_codex":0.000040707284,"about_ca_system_score_gemma":0.00002790313,"threshold_uncertainty_score":0.63405865},"labels":[],"label_agreement":null},{"id":"W2015569424","doi":"10.1080/13669870802579798","title":"Pleasure in decision‐making situations: politics and gambling","year":2009,"lang":"en","type":"article","venue":"Journal of Risk Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Pleasure; Psychology; Politics; Set (abstract data type); Dimension (graph theory); Social psychology; Computer science; Political science","score_opus":0.39443930843170166,"score_gpt":0.5694844779745664,"score_spread":0.1750451695428647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2015569424","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9943749,0.00087453896,0.002886882,0.0010220134,0.00020366121,0.000075273645,0.000005727677,0.0000039341267,0.0005530917],"genre_scores_gemma":[0.98742133,0.00060466636,0.011689863,0.00006966003,0.0001641453,4.1857703e-7,1.1196943e-7,0.000007036662,0.000042763608],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99500126,0.0005460293,0.0012917302,0.00027124674,0.002490585,0.00039918165],"domain_scores_gemma":[0.98705643,0.010278484,0.0004722713,0.0003902991,0.0015927125,0.00020978015],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.024489697,0.000101619196,0.00037211608,0.002244962,0.00030506589,0.0007390559,0.00079462526,0.00011649968,0.000078393925],"category_scores_gemma":[0.03985271,0.00007189064,0.000117805816,0.0013614094,0.00011223417,0.0005937264,0.00012742449,0.0010891871,0.00005316524],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008594408,0.00009058597,0.033137616,5.7860206e-7,0.0000026620762,0.000088417124,0.0006436594,0.00085163466,0.00004755427,0.00044468563,0.0024583424,0.9621483],"study_design_scores_gemma":[0.00051418855,0.00024911293,0.19920123,0.00022896248,0.0000059280396,0.00013939905,0.0021725248,0.0023993773,0.000020656164,0.7906675,0.0043086726,0.00009246303],"about_ca_topic_score_codex":0.000019293135,"about_ca_topic_score_gemma":0.00008165867,"teacher_disagreement_score":0.96205586,"about_ca_system_score_codex":0.0001582268,"about_ca_system_score_gemma":0.00028954656,"threshold_uncertainty_score":0.968235},"labels":[],"label_agreement":null},{"id":"W2016146995","doi":"","title":"Risky social choice with approximate interpersonal comparisons of well-being","year":2010,"lang":"en","type":"article","venue":"Munich Personal RePEc Archive (Ludwig Maximilian University of Munich)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Trent University","funders":"","keywords":"Von Neumann–Morgenstern utility theorem; Preference; Interpersonal communication; Social planner; Social welfare function; Mathematical economics; Social choice theory; Order (exchange); Von Neumann architecture; Psychology; Mathematics; Social psychology; Expected utility hypothesis; Welfare; Economics; Microeconomics; Statistics","score_opus":0.044917903870073855,"score_gpt":0.3019552545627112,"score_spread":0.25703735069263733,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2016146995","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9500462,0.000019946952,0.001865869,0.0005795351,0.00021469634,0.00023192515,0.00023681512,0.000053611137,0.046751395],"genre_scores_gemma":[0.97939575,0.000022445305,0.018664908,0.00006100587,0.00007200305,6.3548316e-7,0.00003323464,0.000032935754,0.0017170788],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99619865,0.00033056102,0.0007323547,0.0008849726,0.0013152115,0.00053822575],"domain_scores_gemma":[0.99553907,0.0016278271,0.0009319587,0.0010875487,0.0005167173,0.00029684932],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0015093443,0.00038407676,0.0009568914,0.00062063953,0.0007611643,0.00008762746,0.002771729,0.00021179627,0.0013599232],"category_scores_gemma":[0.0004846153,0.0003607563,0.0005433786,0.00061013846,0.0019395811,0.00045897692,0.0010316689,0.001072707,0.00009783448],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00683169,0.0038897668,0.27278912,0.00019303375,0.0009532873,0.00042513112,0.13490884,0.0004792718,0.02413619,0.016281676,0.032520007,0.506592],"study_design_scores_gemma":[0.01053699,0.0021201684,0.3065742,0.000699251,0.00080358546,0.0003225208,0.15651882,0.079105824,0.0013868687,0.03691519,0.40185606,0.003160513],"about_ca_topic_score_codex":0.0019680192,"about_ca_topic_score_gemma":0.0075820433,"teacher_disagreement_score":0.50343144,"about_ca_system_score_codex":0.000075622425,"about_ca_system_score_gemma":0.00029479494,"threshold_uncertainty_score":0.9998844},"labels":[],"label_agreement":null},{"id":"W2016720004","doi":"10.1177/154193121005400415","title":"Decision Strategy Types and Situation-Contingent Selection Mechanisms: A Review and Some Field Data","year":2010,"lang":"en","type":"review","venue":"Proceedings of the Human Factors and Ergonomics Society Annual Meeting","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Decision analysis; Computer science; Decision engineering; Business decision mapping; Optimal decision; Management science; Decision field theory; Decision model; Decision support system; Decision problem; Selection (genetic algorithm); Situational ethics; Operations research; Artificial intelligence; Decision tree; Machine learning; Psychology; Engineering; Economics","score_opus":0.12500911088303296,"score_gpt":0.38746008594372755,"score_spread":0.2624509750606946,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2016720004","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20159528,0.7971198,0.000016502714,0.00007368461,0.00030148894,0.0006267762,0.00016445898,0.000025315336,0.00007672138],"genre_scores_gemma":[0.0054792333,0.9924065,0.0017449834,0.00011229252,0.00012885721,0.000009771233,0.000013708841,0.000035174617,0.00006946358],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99704295,0.000029733274,0.0013336046,0.0009764689,0.00035190344,0.00026530764],"domain_scores_gemma":[0.99634564,0.0011348189,0.0017344293,0.00036638856,0.00029296117,0.00012575787],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0035192058,0.00043107997,0.0014886416,0.00011049251,0.0006682729,0.0006165281,0.0011379065,0.00044901768,0.000015935608],"category_scores_gemma":[0.0018279977,0.00026820847,0.00031864355,0.00025894347,0.00015188236,0.0008515191,0.0015687313,0.0006685674,0.0000019298004],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000051478455,0.000025485382,0.00027401402,0.001980094,0.000059029615,4.785545e-8,0.00045901726,3.9365887e-7,0.000025333611,0.0006567543,0.0028578155,0.9936569],"study_design_scores_gemma":[0.0005993846,0.000453988,0.0006977067,0.036188763,0.0044767032,0.00008512458,0.0051082717,0.0006069001,0.0001064348,0.09414697,0.85543174,0.0020980353],"about_ca_topic_score_codex":0.00006148759,"about_ca_topic_score_gemma":0.00003735469,"teacher_disagreement_score":0.99155885,"about_ca_system_score_codex":0.000044309356,"about_ca_system_score_gemma":0.00008480446,"threshold_uncertainty_score":0.999977},"labels":[],"label_agreement":null},{"id":"W2017092729","doi":"10.3758/bf03196483","title":"Syllogistic reasoning time: Disconfirmation disconfirmed","year":2003,"lang":"en","type":"article","venue":"Psychonomic Bulletin & Review","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":64,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Syllogism; Premise; Psychology; Deductive reasoning; Psychology of reasoning; Cognitive psychology; Verbal reasoning; Cognition; Epistemology; Philosophy","score_opus":0.09815062896328869,"score_gpt":0.4042266667219603,"score_spread":0.3060760377586716,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2017092729","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2975965,0.15082832,0.0149681,0.035768487,0.00980808,0.004952082,0.0001549655,0.00062356435,0.4852999],"genre_scores_gemma":[0.90592366,0.032673076,0.01937648,0.012686691,0.00049430446,0.00036849052,0.00008073527,0.00018627508,0.028210266],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9957938,0.00058919354,0.0017231414,0.0009381333,0.0005195261,0.00043621537],"domain_scores_gemma":[0.9963118,0.0010658695,0.00080886413,0.0014376799,0.0001473563,0.00022847521],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.005636082,0.0003344458,0.00088903407,0.0001624605,0.00021553633,0.00041821718,0.0009914673,0.000105098254,0.023360813],"category_scores_gemma":[0.005002168,0.00025141175,0.00036832693,0.00042147958,0.00014682578,0.00016340434,0.00007654033,0.00025846725,0.04340939],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016237162,0.000115228184,0.0004663275,0.00006933739,0.000017165272,0.0000075607345,0.000044861823,0.00003035452,0.0000426978,0.0029694836,0.36730042,0.6289203],"study_design_scores_gemma":[0.00030022298,0.000037553316,0.00052540057,0.0011436326,0.000059299757,0.000062622865,0.00004639124,0.000080170685,0.00001208153,0.010678736,0.98670083,0.00035307242],"about_ca_topic_score_codex":0.000015255322,"about_ca_topic_score_gemma":0.0000032978753,"teacher_disagreement_score":0.6285672,"about_ca_system_score_codex":0.00010015466,"about_ca_system_score_gemma":0.0000866166,"threshold_uncertainty_score":0.9999938},"labels":[],"label_agreement":null},{"id":"W2017240459","doi":"10.3109/10826084.2012.705685","title":"Is Addiction a Failure of Rationality?","year":2012,"lang":"en","type":"article","venue":"Substance Use & Misuse","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Commodity; Addiction; Consumption (sociology); Rationality; Luck; Economics; Market failure; Microeconomics; Government (linguistics); Positive economics; Public economics; Psychology; Market economy; Sociology; Political science; Psychiatry; Law","score_opus":0.2272857588072667,"score_gpt":0.411040235686017,"score_spread":0.1837544768787503,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2017240459","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9969126,0.00032427334,0.0011489252,0.0003406565,0.0006155018,0.000110337554,0.000108506814,0.000033243923,0.00040597934],"genre_scores_gemma":[0.99566174,0.000023231873,0.0028441558,0.00023815644,0.00012640013,0.0000071498107,0.000008106781,0.000012962692,0.0010781238],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99777114,0.00009307528,0.0007231108,0.00032887855,0.0008075129,0.00027624995],"domain_scores_gemma":[0.9975398,0.0007689639,0.0003829783,0.00075281964,0.00040660147,0.00014882555],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0013875634,0.00013828301,0.0002758611,0.0001847391,0.000115540526,0.00015078818,0.00041652357,0.00010719596,0.0017842322],"category_scores_gemma":[0.000860119,0.0001108803,0.00016714567,0.0005682994,0.00009741548,0.001571307,0.00003973992,0.000119542674,0.00076432776],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002167058,0.0005811532,0.58626467,0.0000054776965,0.000042081447,0.000005777209,0.0061202296,0.000115587965,0.004865539,0.0047268635,0.21362165,0.1834343],"study_design_scores_gemma":[0.0013188947,0.00010126037,0.2409055,0.00012322262,0.00008549094,0.000027622451,0.0019859972,0.0004995745,0.01625219,0.054974865,0.6830006,0.0007247428],"about_ca_topic_score_codex":0.000031531774,"about_ca_topic_score_gemma":0.00018290954,"teacher_disagreement_score":0.469379,"about_ca_system_score_codex":0.000060367594,"about_ca_system_score_gemma":0.00005109717,"threshold_uncertainty_score":0.9991283},"labels":[],"label_agreement":null},{"id":"W2018329894","doi":"10.3758/bf03193584","title":"Confidence and accuracy in deductive reasoning","year":2006,"lang":"en","type":"article","venue":"Memory & Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":131,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Psychology; Syllogism; Deliberation; Heuristic; Cognitive psychology; Self-confidence; Function (biology); Metacognition; Contrast (vision); Cognition; Social psychology; Artificial intelligence; Computer science; Epistemology","score_opus":0.08557876263758146,"score_gpt":0.38471391691217405,"score_spread":0.2991351542745926,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2018329894","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9843531,0.000098239274,0.00090047444,0.00018471594,0.00019955884,0.00012473615,0.000008960394,0.000025219624,0.014104948],"genre_scores_gemma":[0.99875206,0.000009945667,0.0007391988,0.00012139608,0.00007478322,0.000010552652,0.0000070172473,0.000006672486,0.00027836408],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99854946,0.00010153323,0.0004341716,0.00041621816,0.00033318804,0.00016544416],"domain_scores_gemma":[0.9983081,0.0010848081,0.00018184427,0.0002090128,0.00017176983,0.000044424425],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012967277,0.00010012591,0.00018308124,0.00024253054,0.000105974694,0.0002633458,0.0001694451,0.000063051535,0.00022702877],"category_scores_gemma":[0.0020575575,0.000087405104,0.000037574628,0.0003192935,0.00010121252,0.00061022845,0.0000636692,0.00012438963,0.00027707889],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000089158755,0.000128976,0.0080278125,0.0000025465063,0.0000025598795,0.000067548164,0.00043483748,0.0001590061,0.0045352923,0.002090889,0.0016698508,0.98279154],"study_design_scores_gemma":[0.00076577795,0.00006305766,0.17305881,0.00012726686,0.000019396864,0.00008871321,0.002630135,0.0011602945,0.0047260216,0.8154034,0.0016589364,0.00029820544],"about_ca_topic_score_codex":0.00020879775,"about_ca_topic_score_gemma":0.00026501098,"teacher_disagreement_score":0.98249334,"about_ca_system_score_codex":0.0000366668,"about_ca_system_score_gemma":0.000038677776,"threshold_uncertainty_score":0.35642767},"labels":[],"label_agreement":null},{"id":"W2019406163","doi":"10.1016/j.jesp.2009.12.009","title":"You can’t always get what you want: The motivational effect of need on risk-sensitive decision-making","year":2009,"lang":"en","type":"article","venue":"Journal of Experimental Social Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":131,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Psychology; Risk-seeking; Social psychology; Irrational number; Risk aversion (psychology); Expected utility hypothesis; Economics","score_opus":0.05784026192484497,"score_gpt":0.44220946422586266,"score_spread":0.3843692023010177,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2019406163","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9919472,0.0002957081,0.00047465827,0.0031108696,0.0026336403,0.00017726747,0.000023364777,0.0000083137365,0.0013289872],"genre_scores_gemma":[0.9971697,0.000043645236,0.0004956446,0.0016534815,0.0006017443,0.0000018714384,0.0000013680461,0.000015584536,0.00001698548],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99586266,0.00070270436,0.0014609125,0.0004016054,0.0012548319,0.0003172944],"domain_scores_gemma":[0.99395734,0.003245907,0.001989302,0.00036312334,0.00033751316,0.00010679008],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035349955,0.00026688652,0.00076913583,0.0003965575,0.000449497,0.00024155594,0.0009276226,0.00022633898,0.00027129913],"category_scores_gemma":[0.0015583823,0.00016051889,0.00058792176,0.00045691687,0.0003165451,0.00048378826,0.000084178966,0.0005534456,0.000052000185],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0037136015,0.0006852419,0.0032837377,4.5936375e-7,0.000081228885,0.00008345473,0.0052370196,0.0002459976,0.0161052,0.00052176055,0.012142743,0.9578996],"study_design_scores_gemma":[0.014190784,0.02423671,0.43563655,0.0006793574,0.00029710366,0.0012096998,0.046148486,0.00045549305,0.060336616,0.4078516,0.0074727037,0.0014849112],"about_ca_topic_score_codex":0.000009167385,"about_ca_topic_score_gemma":0.000003523459,"teacher_disagreement_score":0.95641464,"about_ca_system_score_codex":0.00018770617,"about_ca_system_score_gemma":0.00006703654,"threshold_uncertainty_score":0.654577},"labels":[],"label_agreement":null},{"id":"W2019569350","doi":"10.1109/itsc.2006.1706823","title":"Modeling Driver Psychological Deliberation During Dynamic Route Selection Processes","year":2006,"lang":"en","type":"article","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Deliberation; Computer science; Process (computing); Representation (politics); Dissemination; Field (mathematics); Management science; Selection (genetic algorithm); Risk analysis (engineering); Operations research; Artificial intelligence; Engineering","score_opus":0.08425027100821553,"score_gpt":0.39873464016649096,"score_spread":0.31448436915827543,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2019569350","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89130235,0.00001954525,0.10519882,0.00014640717,0.00021373531,0.000093155366,0.0000026341893,0.0001392027,0.0028841689],"genre_scores_gemma":[0.9909214,0.000006854594,0.006265209,0.00006836626,0.00008430905,0.000008821802,0.0000063185344,0.0000107413625,0.0026279716],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99798965,0.000045458262,0.0006495453,0.00059359934,0.0004973603,0.00022435306],"domain_scores_gemma":[0.99908066,0.00012777813,0.00011303608,0.0002478871,0.0003799586,0.000050653754],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005613229,0.00013781684,0.00018773183,0.00021964705,0.00027436428,0.00053005334,0.00031953817,0.0001184499,0.00038154313],"category_scores_gemma":[0.00029744545,0.00009794257,0.00007586224,0.0006006554,0.000027110504,0.00068600907,0.000055484517,0.00012279315,0.00047307744],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000117268886,0.00042897384,0.016455768,0.000005476288,0.0000060107077,0.000012964864,0.00011240128,0.7081888,0.007927144,0.0005806068,0.0013126603,0.26485196],"study_design_scores_gemma":[0.00043242716,0.00007236447,0.020325206,0.000014395529,0.000011582114,0.0000649473,0.000117112206,0.853806,0.00070863473,0.12375868,0.0003690782,0.00031954405],"about_ca_topic_score_codex":0.00007374674,"about_ca_topic_score_gemma":0.00082869746,"teacher_disagreement_score":0.26453242,"about_ca_system_score_codex":0.000091797316,"about_ca_system_score_gemma":0.000032892065,"threshold_uncertainty_score":0.60806113},"labels":[],"label_agreement":null},{"id":"W2020045420","doi":"10.3390/jintelligence2010008","title":"Assessing Cognitive Abilities: Intelligence and More","year":2014,"lang":"en","type":"article","venue":"Journal of Intelligence","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"John Templeton Foundation","keywords":"Rationality; Construct (python library); Cognition; Psychology; Dual (grammatical number); Dual process theory (moral psychology); Cognitive psychology; Process (computing); Ecological rationality; Cognitive science; Rational analysis; Computer science; Epistemology","score_opus":0.2266708241467239,"score_gpt":0.4726964524896948,"score_spread":0.24602562834297087,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2020045420","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6875114,0.00021288385,0.3100456,0.00031934955,0.0005869194,0.000044332428,0.0000021481949,0.0000071515483,0.0012702314],"genre_scores_gemma":[0.9930636,0.00009937717,0.0061939848,0.00032928286,0.00018015332,8.439992e-7,1.6790788e-7,0.00001094767,0.00012158493],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9967715,0.00020263821,0.0015432879,0.00034469072,0.0009017161,0.00023616359],"domain_scores_gemma":[0.9905429,0.0065676286,0.0010400981,0.000317965,0.0013039947,0.0002274503],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.005910841,0.0001756555,0.0004835453,0.00040136694,0.00014746792,0.00092792226,0.0008213535,0.000095903626,0.00031843246],"category_scores_gemma":[0.015164981,0.00012060799,0.00017868612,0.00041454544,0.00040711535,0.0012743982,0.00016064703,0.00038122814,0.00012757836],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032869444,0.000050734172,0.0041215676,0.0000030522845,0.0000075379708,0.000015316471,0.0011666543,0.00042061735,0.000059989623,0.00059257325,0.00013876252,0.9933903],"study_design_scores_gemma":[0.00019158993,0.0011170753,0.011635919,0.0008964429,0.00008496404,0.0011825106,0.071758986,0.019251833,0.012483974,0.87201446,0.008725372,0.0006568709],"about_ca_topic_score_codex":0.000010865874,"about_ca_topic_score_gemma":0.0000057729058,"teacher_disagreement_score":0.9927335,"about_ca_system_score_codex":0.000053090025,"about_ca_system_score_gemma":0.00011740881,"threshold_uncertainty_score":0.9931307},"labels":[],"label_agreement":null},{"id":"W2021544558","doi":"10.1037/xge0000049","title":"Disfluent fonts don’t help people solve math problems.","year":2015,"lang":"en","type":"review","venue":"Journal of Experimental Psychology General","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":113,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan; University of Waterloo","funders":"","keywords":"Counterintuitive; Pooling; Font; CLARITY; Replicate; Computer science; Cognitive psychology; Psychology; Cognition; Artificial intelligence; Statistics; Mathematics","score_opus":0.33698835825116236,"score_gpt":0.5406556207180131,"score_spread":0.20366726246685074,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2021544558","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.032187916,0.95724636,0.00013348255,0.00011893486,0.008186315,0.0004310066,0.000057065987,0.000016868764,0.0016220732],"genre_scores_gemma":[0.0015936693,0.9899439,0.004605814,0.00048039897,0.0019239413,0.00004500619,0.000023281149,0.00011959738,0.0012643961],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99248797,0.0006149393,0.0038791972,0.00091278553,0.0015151107,0.00058997853],"domain_scores_gemma":[0.993709,0.00031496727,0.003828958,0.0011370156,0.00045717804,0.0005528601],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0047342805,0.0006991009,0.0035816384,0.0009050819,0.00016987533,0.0003973941,0.00258095,0.0006399301,0.0007236215],"category_scores_gemma":[0.00024928,0.00044627066,0.001704137,0.0005560153,0.00019117615,0.00047608634,0.0004303283,0.0010881367,0.000992972],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000666794,0.00076220615,0.000066236236,0.000044907618,0.00011940674,0.0001326993,0.00039724517,0.000013780717,0.00004413038,0.00007206397,0.101443574,0.89683706],"study_design_scores_gemma":[0.0009196365,0.0009083855,0.000028579869,0.00086220657,0.00019223453,0.0026966692,0.00033160506,0.000012628614,0.0000083915975,0.0038025451,0.98976374,0.00047337732],"about_ca_topic_score_codex":0.000010670194,"about_ca_topic_score_gemma":0.00001465675,"teacher_disagreement_score":0.8963637,"about_ca_system_score_codex":0.0004864536,"about_ca_system_score_gemma":0.00049321196,"threshold_uncertainty_score":0.9997989},"labels":[],"label_agreement":null},{"id":"W2023548979","doi":"10.1207/s15327663jcp1601_6","title":"Malleable Mental Accounting: The Effect of Flexibility on the Justification of Attractive Spending and Consumption Decisions","year":2006,"lang":"en","type":"article","venue":"Journal of Consumer Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":264,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"University of Colorado Boulder","keywords":"Mental accounting; Flexibility (engineering); Ambiguity; Consumption (sociology); Control (management); Construct (python library); Process (computing); Economics; Actuarial science; Microeconomics; Accounting; Psychology; Computer science","score_opus":0.19941157557364297,"score_gpt":0.4636348922484119,"score_spread":0.26422331667476895,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2023548979","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99630046,0.00033525037,0.0004321479,0.0010845712,0.0007769678,0.0001886333,0.000014358151,0.0000025326276,0.00086506346],"genre_scores_gemma":[0.9995623,0.00008938374,0.00019659352,0.00005899338,0.00004286712,0.000001924009,6.368019e-7,0.0000059308486,0.000041367937],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9973258,0.0005506898,0.0012227834,0.00023326003,0.0005331593,0.00013430037],"domain_scores_gemma":[0.987206,0.010233182,0.001768967,0.0004921893,0.00026418263,0.000035493507],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007379828,0.00011878469,0.00041136766,0.00024916357,0.0001790373,0.00006891587,0.00055150536,0.000095385156,0.0002513976],"category_scores_gemma":[0.0022357749,0.00005629499,0.0001698885,0.00021595914,0.00051326735,0.00019972592,0.00005510443,0.0002944544,0.00004020466],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020847507,0.00034863883,0.54850286,0.000005648411,0.00008068457,0.0000068609065,0.00031441025,0.00020971987,0.021637134,0.0012737943,0.013614104,0.4119214],"study_design_scores_gemma":[0.0014904465,0.000840412,0.9511925,0.00010988701,0.00015141601,0.0003171828,0.0004458798,0.00022528124,0.008474466,0.029095676,0.0075276485,0.00012918231],"about_ca_topic_score_codex":0.0000164623,"about_ca_topic_score_gemma":0.000015462509,"teacher_disagreement_score":0.41179222,"about_ca_system_score_codex":0.00003168665,"about_ca_system_score_gemma":0.00002834771,"threshold_uncertainty_score":0.27526274},"labels":[],"label_agreement":null},{"id":"W2024535950","doi":"10.1007/s40505-013-0009-1","title":"Eliciting beliefs by paying in chance","year":2013,"lang":"en","type":"article","venue":"Economic Theory Bulletin","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"National Science Foundation","keywords":"Public finance; Economics; Positive economics; Microeconomics; Neoclassical economics; Public economics; Macroeconomics","score_opus":0.037965172797364444,"score_gpt":0.32763378151263245,"score_spread":0.289668608715268,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2024535950","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9752809,0.00019837277,0.00033226903,0.0029213908,0.00060572097,0.00021924081,0.000020200367,0.000050717685,0.020371186],"genre_scores_gemma":[0.99390835,0.000020795182,0.00056697946,0.001397616,0.00014343302,0.0000501547,0.0000035985497,0.000028738486,0.0038803504],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99733114,0.0002546557,0.0010766037,0.0007379782,0.00014546105,0.0004541457],"domain_scores_gemma":[0.9966167,0.0021611666,0.00037865472,0.00066758605,0.00004313908,0.00013275187],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0044835196,0.0002152944,0.00042752537,0.00024685435,0.00014331208,0.00048824202,0.000982764,0.00011958868,0.026115306],"category_scores_gemma":[0.00088900246,0.00018814532,0.0001269704,0.000115943745,0.00010994533,0.00025377763,0.00023508427,0.00023846104,0.04616008],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021368627,0.000046200646,0.0034162852,0.0000011053197,0.0000047374433,0.0000044276408,0.000410844,0.00035408273,0.00047017264,0.0036374915,0.0774895,0.9141438],"study_design_scores_gemma":[0.0006664595,0.0000509198,0.0031675291,0.000043987842,0.0000038069,0.000014992078,0.0020688425,0.0010494022,0.00068571867,0.6991405,0.29256296,0.0005449097],"about_ca_topic_score_codex":0.00024097293,"about_ca_topic_score_gemma":0.000031685806,"teacher_disagreement_score":0.9135989,"about_ca_system_score_codex":0.00017457269,"about_ca_system_score_gemma":0.000036415997,"threshold_uncertainty_score":0.97477496},"labels":[],"label_agreement":null},{"id":"W2024781866","doi":"10.5539/ijef.v5n8p109","title":"Optimal Investment Behavior for Regret-Averse Competitive Firms under Price Uncertainty","year":2013,"lang":"en","type":"article","venue":"International Journal of Economics and Finance","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Shanghai University of Finance and Economics","keywords":"Regret; Economics; Microeconomics; Risk aversion (psychology); Investment (military); Capital (architecture); Perspective (graphical); Expected utility hypothesis; Financial economics; Computer science","score_opus":0.07926708993715913,"score_gpt":0.3512461151656826,"score_spread":0.27197902522852346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2024781866","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99439806,0.00010642762,0.0009948676,0.0017417606,0.0017392491,0.00017555115,0.00008013075,0.0000023681746,0.00076160615],"genre_scores_gemma":[0.9869318,0.00059390947,0.0107110245,0.000914564,0.00028018086,0.00001886349,0.000003945583,0.000010546089,0.0005351695],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.998512,0.000020136233,0.00087946386,0.00025760717,0.00018006291,0.00015069844],"domain_scores_gemma":[0.9975585,0.00044588422,0.00091550924,0.00016625274,0.00083400984,0.00007988073],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007374224,0.00012826943,0.00029656506,0.0001985478,0.000067802546,0.0003787174,0.00066907605,0.000067778594,0.00015153032],"category_scores_gemma":[0.0002459769,0.00010120112,0.00017317015,0.000047790036,0.00011546017,0.00064230297,0.0001159055,0.00012264396,0.000055952743],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003766282,0.00047628945,0.0030664979,0.0000019495296,0.00014411991,0.000027471617,0.0005537721,0.12369003,0.00009851574,0.15154143,0.011895692,0.7081276],"study_design_scores_gemma":[0.0036596311,0.00085241086,0.05950489,0.00010774334,0.00004790168,0.00045687793,0.002093596,0.07516493,0.00024526648,0.44343424,0.41382152,0.00061101024],"about_ca_topic_score_codex":0.000038551007,"about_ca_topic_score_gemma":0.00002035195,"teacher_disagreement_score":0.7075166,"about_ca_system_score_codex":0.00016232624,"about_ca_system_score_gemma":0.00011895545,"threshold_uncertainty_score":0.41268617},"labels":[],"label_agreement":null},{"id":"W2025443246","doi":"10.1086/513041","title":"On the Perceived Value of Money: The Reference Dependence of Currency Numerosity Effects","year":2007,"lang":"en","type":"article","venue":"Journal of Consumer Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":176,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Numerosity adaptation effect; Anchoring; Value (mathematics); Economics; Currency; Salient; Perception; Illusion; Value for money; Microeconomics; Econometrics; Monetary economics; Psychology; Cognitive psychology; Social psychology; Computer science; Statistics; Mathematics; Public economics; Artificial intelligence","score_opus":0.32434961425618797,"score_gpt":0.5109207354967847,"score_spread":0.18657112124059677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2025443246","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99620557,0.0005430698,0.00044055012,0.00059955113,0.00032893513,0.00020148793,0.000007140622,0.0000021195117,0.0016715949],"genre_scores_gemma":[0.99940586,0.00017587926,0.00021213952,0.000040776067,0.000034339555,0.000001348904,9.7347794e-8,0.000007102683,0.00012248063],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9933905,0.0012091794,0.001296715,0.00023314859,0.0035141709,0.00035630047],"domain_scores_gemma":[0.96732837,0.028337419,0.0009240356,0.00087699556,0.0023803045,0.00015289552],"candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.033267353,0.000120778815,0.00043420936,0.00049309485,0.0002771059,0.0001352258,0.0025265939,0.000098073884,0.00024082878],"category_scores_gemma":[0.016608639,0.000053927022,0.00022344282,0.00088167033,0.0007327031,0.00021763796,0.0002689001,0.0012046497,0.00012279968],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001454903,0.0008076293,0.07465843,0.000027160364,0.00009305593,0.00010174267,0.0022228404,0.0001551029,0.02988301,0.011653839,0.012617163,0.86632514],"study_design_scores_gemma":[0.0012718722,0.0019058057,0.6853236,0.0008881733,0.00007352955,0.00015634556,0.0033859685,0.0005292817,0.035086066,0.2657069,0.0053946045,0.00027782936],"about_ca_topic_score_codex":0.00011668012,"about_ca_topic_score_gemma":0.000043181342,"teacher_disagreement_score":0.8660473,"about_ca_system_score_codex":0.0000641089,"about_ca_system_score_gemma":0.00038194677,"threshold_uncertainty_score":0.99545467},"labels":[],"label_agreement":null},{"id":"W2025902133","doi":"10.1016/j.jmp.2006.10.004","title":"A behavioral condition for Prelec's weighting function on the positive line without assuming","year":2007,"lang":"en","type":"article","venue":"Journal of Mathematical Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":22,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Weighting; Axiom; Context (archaeology); Line (geometry); Function (biology); Mathematics; Expected utility hypothesis; Applied mathematics; Mathematical economics; Medicine; Biology","score_opus":0.23755183170948954,"score_gpt":0.5187104857905608,"score_spread":0.2811586540810712,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2025902133","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7470239,0.000013037121,0.24824212,0.001826302,0.00072271394,0.00017719061,0.000005494213,0.000007837119,0.001981416],"genre_scores_gemma":[0.9907545,0.0000014127539,0.0077672144,0.00091308396,0.00038093593,0.0000042198917,0.0000010388258,0.00001529123,0.00016233277],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99732757,0.00014312942,0.001414605,0.00024342278,0.000606016,0.00026525895],"domain_scores_gemma":[0.9925939,0.0053231283,0.0011190425,0.00031260645,0.000537755,0.00011358616],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009056961,0.00014113878,0.00042422873,0.00030380834,0.00017576429,0.00012574674,0.00045942908,0.00016064745,0.00038108008],"category_scores_gemma":[0.002645813,0.000076579825,0.00028042495,0.00021029357,0.00012845268,0.00020135027,0.000030929736,0.00039982825,0.00017070146],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0039838227,0.002478406,0.0012841257,0.0000099268345,0.0001063621,0.0000857539,0.0014627813,0.00009272573,0.00998208,0.036472883,0.02275108,0.92129004],"study_design_scores_gemma":[0.0013875832,0.0038661421,0.005010853,0.00016636115,0.00014802456,0.0006014525,0.0011001067,0.00091271946,0.0011915702,0.97970635,0.0057161674,0.00019270153],"about_ca_topic_score_codex":3.7722543e-7,"about_ca_topic_score_gemma":0.000002095182,"teacher_disagreement_score":0.94323343,"about_ca_system_score_codex":0.00005712605,"about_ca_system_score_gemma":0.000028944562,"threshold_uncertainty_score":0.417256},"labels":[],"label_agreement":null},{"id":"W2026133119","doi":"10.1024/1662-9647/a000051","title":"Multivariate Longitudinal Modeling of Cognitive Aging","year":2012,"lang":"en","type":"article","venue":"GeroPsych","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"National Institute on Aging","keywords":"Latent growth modeling; Multivariate statistics; Growth curve (statistics); Association (psychology); Cognition; Psychology; Longitudinal data; Structural equation modeling; Multivariate analysis; Random effects model; Longitudinal study; Statistics; Cognitive psychology; Econometrics; Developmental psychology; Mathematics; Computer science; Medicine; Data mining","score_opus":0.316591569796243,"score_gpt":0.4667040383921943,"score_spread":0.15011246859595134,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2026133119","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9446866,0.00014961245,0.04984864,0.00006449294,0.0009786573,0.00008100728,0.000017057004,0.000023642144,0.0041503157],"genre_scores_gemma":[0.99668634,0.000003831444,0.0028655156,0.000051778807,0.00016438769,0.0000039498364,0.000002235726,0.00001271605,0.00020925324],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998032,0.00008205381,0.000655867,0.00033346613,0.0005571998,0.0003394524],"domain_scores_gemma":[0.99810874,0.000814707,0.0002492342,0.00037725104,0.0003140489,0.0001360011],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021915953,0.00012962901,0.000298894,0.00022771925,0.000106775165,0.000089795605,0.00038543847,0.00007127277,0.0004504397],"category_scores_gemma":[0.0010870766,0.00009940162,0.00013721694,0.0003698453,0.000059439913,0.00047378955,0.00013314806,0.00013278746,0.00072409207],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011123419,0.00040376486,0.1707076,0.0000032970984,0.000030216816,0.0000052660903,0.0032715027,0.0022510283,0.0006773797,0.00058194937,0.000574877,0.82138187],"study_design_scores_gemma":[0.0053220326,0.00047565324,0.3820028,0.0009193847,0.00032056478,0.00019217559,0.018093359,0.40191618,0.0030246417,0.18141358,0.0039213668,0.0023982471],"about_ca_topic_score_codex":0.00007603265,"about_ca_topic_score_gemma":0.0000062427266,"teacher_disagreement_score":0.8189836,"about_ca_system_score_codex":0.000021496171,"about_ca_system_score_gemma":0.000027304935,"threshold_uncertainty_score":0.930698},"labels":[],"label_agreement":null},{"id":"W2026651188","doi":"10.1007/s00199-007-0260-5","title":"Utility of gambling I: entropy modified linear weighted utility","year":2007,"lang":"en","type":"article","venue":"Economic Theory","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":36,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria; University of Waterloo","funders":"","keywords":"Receipt; Axiom; Mathematical economics; Expected utility hypothesis; Von Neumann–Morgenstern utility theorem; Preference; Revealed preference; Public finance; Subjective expected utility; Term (time); Entropy (arrow of time); Economics; Mathematics; Econometrics; Microeconomics","score_opus":0.16259229680610154,"score_gpt":0.4074807756393446,"score_spread":0.24488847883324305,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2026651188","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9550647,0.000102225815,0.021500396,0.000052351035,0.0013284999,0.00016746484,0.00007695891,0.000058938174,0.021648435],"genre_scores_gemma":[0.9972509,0.000008210659,0.0017445917,0.000081085556,0.0001778505,0.0000015881756,0.000005428699,0.00001810229,0.0007122079],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9964996,0.00025735423,0.001754497,0.00076246273,0.0002976371,0.00042843763],"domain_scores_gemma":[0.9941826,0.003463334,0.0006721298,0.0013360063,0.00014254659,0.0002034167],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.014701215,0.00022403801,0.000623735,0.00035709972,0.00013574176,0.000092689384,0.0010763523,0.00018592288,0.0050322376],"category_scores_gemma":[0.0011283932,0.00018730716,0.0003406588,0.00019637596,0.00032864543,0.00034342642,0.00024292117,0.00023621207,0.0012139741],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001154781,0.00023367535,0.021507606,0.0000046717387,0.000036056434,0.000010266781,0.00050972175,0.00017988632,0.00047982603,0.042339753,0.0015007787,0.93204296],"study_design_scores_gemma":[0.00087461923,0.00006774705,0.034792263,0.000016601016,0.000026830656,0.000009820538,0.0009949339,0.029707605,0.009782294,0.9061273,0.017243564,0.00035641924],"about_ca_topic_score_codex":0.00005093403,"about_ca_topic_score_gemma":0.0000619532,"teacher_disagreement_score":0.9316866,"about_ca_system_score_codex":0.00007405698,"about_ca_system_score_gemma":0.00014604784,"threshold_uncertainty_score":0.9995637},"labels":[],"label_agreement":null},{"id":"W2027211078","doi":"10.1167/13.9.426","title":"Probability Cuing Improves Perceptual Judgments","year":2013,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Cued speech; Psychology; Perception; Task (project management); Tilt (camera); Orientation (vector space); Audiology; Cognitive psychology; Social psychology; Mathematics","score_opus":0.1396155848047455,"score_gpt":0.40066244794314937,"score_spread":0.26104686313840386,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2027211078","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99651784,0.000056141424,0.00052871753,0.00074645464,0.0011175995,0.00012991639,0.0000015188435,0.00000921359,0.0008925921],"genre_scores_gemma":[0.9927972,0.000011003212,0.0065023154,0.00015691393,0.0001805353,0.0000012483148,2.2800651e-7,0.000009171076,0.00034140985],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99681306,0.0001375265,0.0013932827,0.00027084668,0.0011713357,0.00021397445],"domain_scores_gemma":[0.99701303,0.000608372,0.00090337,0.0004289206,0.0008395145,0.0002067732],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.003425735,0.00013235262,0.0003820036,0.0002883765,0.00012916946,0.00060918916,0.0008064771,0.000095288924,0.0014500101],"category_scores_gemma":[0.0021683304,0.000079654346,0.00027580574,0.00025806317,0.00008266322,0.0014799519,0.00017955458,0.00027975705,0.00097465643],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032105658,0.00017728987,0.0047975364,0.0000013193153,0.0000050367526,0.0000060053458,0.00030919112,0.00006345371,0.017445615,0.000015813152,0.014949544,0.96219707],"study_design_scores_gemma":[0.0013233387,0.0019292749,0.59181255,0.00019179819,0.000038303268,0.00020340443,0.0025998305,0.003231941,0.0008791722,0.37447786,0.02289956,0.00041297308],"about_ca_topic_score_codex":0.000018243689,"about_ca_topic_score_gemma":0.0000031782465,"teacher_disagreement_score":0.9617841,"about_ca_system_score_codex":0.00010455503,"about_ca_system_score_gemma":0.0000802155,"threshold_uncertainty_score":0.9998032},"labels":[],"label_agreement":null},{"id":"W2027566178","doi":"10.2466/07.09.cp.2.3","title":"The existence bias: a systematic replication","year":2013,"lang":"en","type":"article","venue":"Comprehensive Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bishop's University","funders":"","keywords":"Status quo; Status quo bias; Replication (statistics); Preference; Psychology; Social psychology; Cognitive psychology; Statistics; Political science; Mathematics","score_opus":0.3984765751873719,"score_gpt":0.48357484355951325,"score_spread":0.08509826837214135,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2027566178","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9804714,0.0009374123,0.00227885,0.007339259,0.0018818149,0.0008652585,0.000002837899,0.000074717536,0.006148486],"genre_scores_gemma":[0.9945072,0.000051672614,0.0008852461,0.0029110701,0.0000700729,0.00021381903,0.0000013780146,0.000013169972,0.0013464036],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9968955,0.0005188962,0.0010821274,0.0007702716,0.00043637256,0.00029681937],"domain_scores_gemma":[0.99028194,0.0049499325,0.00059398275,0.0031125231,0.00095667836,0.00010493398],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0014811243,0.00015663457,0.00041394462,0.00014399372,0.00035091702,0.00049356517,0.0016269819,0.000104911815,0.000204785],"category_scores_gemma":[0.0037981619,0.00008615096,0.0001489313,0.00045095183,0.00029158196,0.00020320345,0.00017198661,0.00016858525,0.013320194],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000042797885,0.00014055413,0.0029487258,0.00007571129,0.000038345996,0.000010913154,0.00049957924,0.00003026958,0.0027844373,0.0065124566,0.1905737,0.7963425],"study_design_scores_gemma":[0.00049334305,0.00021969524,0.07404141,0.00026006944,0.00002784458,0.00028147936,0.0018750007,0.0021763423,0.00005998043,0.82276136,0.09742753,0.0003759291],"about_ca_topic_score_codex":0.00001838167,"about_ca_topic_score_gemma":0.00000868097,"teacher_disagreement_score":0.8162489,"about_ca_system_score_codex":0.00002950134,"about_ca_system_score_gemma":0.000021570146,"threshold_uncertainty_score":0.98744804},"labels":[],"label_agreement":null},{"id":"W2028228266","doi":"10.1002/mar.20274","title":"Leaving the store empty‐handed: Testing explanations for the too‐much‐choice effect using decision field theory","year":2009,"lang":"en","type":"article","venue":"Psychology and Marketing","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":51,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Trinity College","funders":"","keywords":"Variance (accounting); Townsend; Choice set; Quality (philosophy); Set (abstract data type); Psychology; Distribution (mathematics); Field (mathematics); Econometrics; Social psychology; Economics; Mathematics; Computer science","score_opus":0.1785591740851731,"score_gpt":0.4808777904796224,"score_spread":0.30231861639444935,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2028228266","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94186443,0.0008583343,0.050343208,0.003171678,0.0010658634,0.00037326152,0.000004990399,0.000039778344,0.002278444],"genre_scores_gemma":[0.9909036,0.00003728218,0.0057178545,0.0029363437,0.00025864944,0.000018496172,8.8740444e-7,0.000011388016,0.00011551013],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99763376,0.00065432285,0.00055854814,0.00054351916,0.0002786386,0.0003312235],"domain_scores_gemma":[0.90294987,0.0959869,0.0002888429,0.00057121157,0.00014660445,0.00005657145],"candidate_categories":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.017224375,0.00018034475,0.0002581093,0.00014988049,0.0015568519,0.00034450143,0.0007152488,0.0001538179,0.00007063859],"category_scores_gemma":[0.03949039,0.00009486523,0.00012446805,0.0003736802,0.00011401714,0.00021274731,0.00010944266,0.00031903852,0.000011288391],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002593622,0.000017823988,0.01439406,0.0000010944583,0.000008514083,0.0000021403669,0.00014873785,0.00007912899,0.000317209,0.00014957633,0.004345254,0.9802771],"study_design_scores_gemma":[0.002499674,0.0009168663,0.5762318,0.00035974206,0.00025716115,0.00041948823,0.0024220864,0.025725143,0.00017646546,0.29478422,0.095370896,0.0008364734],"about_ca_topic_score_codex":0.000009227444,"about_ca_topic_score_gemma":0.00001939481,"teacher_disagreement_score":0.9794406,"about_ca_system_score_codex":0.000018388442,"about_ca_system_score_gemma":0.000024624702,"threshold_uncertainty_score":0.999743},"labels":[],"label_agreement":null},{"id":"W2028816642","doi":"10.1509/jmkr.37.1.125.18724","title":"Are Consumer Survey Results Distorted? Systematic Impact of Behavioral Frequency and Duration on Survey Response Errors","year":2000,"lang":"en","type":"article","venue":"Journal of Marketing Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":79,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Duration (music); Econometrics; Telephone survey; Statistics; Homogeneous; Call duration; Scale (ratio); Non-sampling error; Survey data collection; Psychology; Audiology; Mathematics; Computer science; Marketing; Medicine; Telecommunications; Acoustics; Geography; Business","score_opus":0.37626530138169945,"score_gpt":0.5223666706228461,"score_spread":0.1461013692411467,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2028816642","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9988118,0.0001869894,0.0000035128755,0.00009863268,0.0001762166,0.0002634337,0.00029390858,0.00000538885,0.00016012118],"genre_scores_gemma":[0.9993041,0.00006760385,0.00008443136,0.0000057026145,0.00003100941,0.000002191716,0.000005070292,0.000018968505,0.00048092235],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9555638,0.036737457,0.0033655646,0.0004964835,0.0033107414,0.0005259697],"domain_scores_gemma":[0.91430116,0.07855232,0.0025679932,0.0008228772,0.0034316578,0.00032400546],"candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.32222953,0.00019368646,0.0008695352,0.001170373,0.00026447204,0.0004055282,0.00084161723,0.00016358665,0.00035551074],"category_scores_gemma":[0.19349428,0.00012591972,0.00024543083,0.001130155,0.0003050927,0.00039591448,0.00008707748,0.0007870072,0.000059909555],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.05778387,0.00042005343,0.9133237,0.00009060448,0.000046917237,0.0001553119,0.0004594211,0.00013309928,0.0004221487,5.252414e-7,0.007066681,0.02009767],"study_design_scores_gemma":[0.00071970955,0.0008824301,0.9958302,0.0014255478,0.000015139175,0.00008632624,0.0004899693,0.00015446868,0.00001828287,0.00022822412,0.000025713234,0.00012399488],"about_ca_topic_score_codex":0.00150475,"about_ca_topic_score_gemma":0.0010826106,"teacher_disagreement_score":0.12873524,"about_ca_system_score_codex":0.00037794877,"about_ca_system_score_gemma":0.00048054877,"threshold_uncertainty_score":0.81329924},"labels":[],"label_agreement":null},{"id":"W2030031047","doi":"10.1198/tast.2009.0001","title":"Splitting a Predictor at the Upper Quarter or Third and the Lower Quarter or Third","year":2009,"lang":"en","type":"article","venue":"The American Statistician","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":192,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Mathematics; Statistics; Voting; Linear regression; Econometrics; Simple (philosophy); Regression analysis; Simple linear regression; Regression; Geography; Political science; Philosophy; Politics","score_opus":0.050893470110711776,"score_gpt":0.3687126660059382,"score_spread":0.31781919589522645,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2030031047","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9698534,0.000076903576,0.0039311782,0.020643791,0.00050797523,0.00052006496,0.00018389836,0.000064202344,0.004218561],"genre_scores_gemma":[0.98255074,0.000024723124,0.0014328706,0.011260589,0.0002780979,0.000025459249,0.0000025943864,0.000020694351,0.0044042366],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99634135,0.00066804554,0.0009057528,0.0006270954,0.0009257186,0.00053203973],"domain_scores_gemma":[0.98820627,0.009394536,0.0007418272,0.0013658706,0.00014927029,0.00014224056],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034270543,0.00030700344,0.000622344,0.00009290566,0.00093489245,0.00079975557,0.0013471197,0.00004637711,0.00074777106],"category_scores_gemma":[0.0021160028,0.00010202258,0.0001555922,0.0006039458,0.0018233124,0.00018476177,0.00021803715,0.0003460881,0.00070803],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0038592117,0.00013087432,0.0014920649,0.0000015258228,0.000048645576,0.00026335355,0.009308543,0.00002803225,0.000027372242,0.0025234704,0.24565999,0.7366569],"study_design_scores_gemma":[0.006421682,0.0075679747,0.32436997,0.00022017975,0.00075044704,0.0024125895,0.0972733,0.022441518,0.000042582524,0.32626477,0.2101112,0.0021237973],"about_ca_topic_score_codex":0.00029254166,"about_ca_topic_score_gemma":0.0006352388,"teacher_disagreement_score":0.73453313,"about_ca_system_score_codex":0.00006375643,"about_ca_system_score_gemma":0.00010503977,"threshold_uncertainty_score":0.91005296},"labels":[],"label_agreement":null},{"id":"W2030299881","doi":"10.1006/obhd.2000.2881","title":"Information Processing at Successive Stages of Decision Making: Need for Cognition and Inclusion–Exclusion Effects","year":2000,"lang":"en","type":"article","venue":"Organizational Behavior and Human Decision Processes","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":212,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Psychology; Mindset; Cognition; Set (abstract data type); Information processing; Inclusion (mineral); Need for cognition; Purchasing; Quality (philosophy); Cognitive psychology; Decision quality; Social psychology; Marketing; Computer science; Knowledge management; Artificial intelligence","score_opus":0.0275843643319885,"score_gpt":0.3520217450133791,"score_spread":0.32443738068139055,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2030299881","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98562706,0.00046242957,0.012435133,0.000074787495,0.00013598005,0.00082050735,0.00016446477,0.000064265136,0.00021534995],"genre_scores_gemma":[0.99404365,0.00013506568,0.0051144715,0.00019459592,0.00006133089,0.000061894585,0.00016230061,0.000038288417,0.00018837958],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99598163,0.00005904738,0.001482262,0.00061725226,0.0015717278,0.00028806308],"domain_scores_gemma":[0.99226516,0.003983032,0.00077328115,0.00034167682,0.0024592355,0.00017758452],"candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0011774172,0.0003537826,0.0005735615,0.00071706844,0.0030324154,0.0006125786,0.00057678786,0.00025556094,0.0011859715],"category_scores_gemma":[0.004927799,0.00028326942,0.000077599274,0.0011017971,0.0002461159,0.0021362854,0.001573268,0.00012953379,0.00004052407],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045857226,0.00022715927,0.021081451,0.00012494551,0.000005971292,0.0000046503947,0.0019652867,0.000069568756,0.0017286636,0.00031168392,0.00053192786,0.9734901],"study_design_scores_gemma":[0.009525416,0.001801755,0.1805064,0.003349719,0.00072288205,0.0002971004,0.0017070539,0.0012416169,0.02087309,0.7619207,0.01582758,0.0022267045],"about_ca_topic_score_codex":0.0000053553113,"about_ca_topic_score_gemma":0.000035021494,"teacher_disagreement_score":0.9712634,"about_ca_system_score_codex":0.000080830294,"about_ca_system_score_gemma":0.00017735074,"threshold_uncertainty_score":0.999962},"labels":[],"label_agreement":null},{"id":"W2031010434","doi":"10.3758/s13421-014-0488-9","title":"Metacognition and abstract reasoning","year":2014,"lang":"en","type":"article","venue":"Memory & Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":42,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan; Université du Québec à Montréal","funders":"","keywords":"Metacognition; Psychology; Inference; Task (project management); Normative; Cognitive psychology; Representation (politics); Logical reasoning; Cognition; Social psychology; Artificial intelligence; Epistemology; Mathematics education; Computer science","score_opus":0.11633257991673143,"score_gpt":0.3807593215937227,"score_spread":0.2644267416769913,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031010434","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9436774,0.00003771723,0.0023946892,0.0001911393,0.00032963406,0.000103588696,0.000012779444,0.00006733689,0.053185664],"genre_scores_gemma":[0.9978031,0.00001117248,0.0012813217,0.00040017028,0.00014877015,0.00001010596,0.000021240176,0.000012982809,0.00031116937],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9982369,0.000115254305,0.00047991256,0.0004778539,0.0005028499,0.00018722369],"domain_scores_gemma":[0.9982219,0.00087990717,0.00023954232,0.00029137242,0.000251042,0.00011626932],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002822473,0.0001355898,0.00023672475,0.00023563534,0.00022368626,0.0004110488,0.00017975183,0.00009115801,0.0007494558],"category_scores_gemma":[0.0024238662,0.000112359536,0.000083386534,0.00021533857,0.00008256986,0.0005653458,0.00006404232,0.00014251031,0.0013115279],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002419424,0.00003468984,0.00025092554,0.0000019001282,0.000004234769,0.000003919916,0.00007220371,0.000010846684,0.0021817437,0.0001404865,0.00074685615,0.99652797],"study_design_scores_gemma":[0.002083912,0.00034403394,0.14593506,0.00022826366,0.0002452399,0.0001787386,0.0018163786,0.006213804,0.011609201,0.7951045,0.035297208,0.00094366627],"about_ca_topic_score_codex":0.000011716383,"about_ca_topic_score_gemma":0.000019650834,"teacher_disagreement_score":0.9955843,"about_ca_system_score_codex":0.000017096821,"about_ca_system_score_gemma":0.00001681525,"threshold_uncertainty_score":0.99946606},"labels":[],"label_agreement":null},{"id":"W2031320758","doi":"10.2202/1534-598x.1250","title":"Likely Events and Possible States","year":2006,"lang":"en","type":"article","venue":"The B E Journal of Theoretical Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Recipe; Monotonic function; Preference; Computer science; Mathematical economics; Economics; Mathematics; Microeconomics","score_opus":0.03492388371377373,"score_gpt":0.3302847674715733,"score_spread":0.29536088375779956,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031320758","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99297154,0.00018255739,0.0010231532,0.0031481467,0.0004512248,0.000053833523,0.000015797585,0.000005270528,0.0021485058],"genre_scores_gemma":[0.99814403,0.00020804552,0.00093092624,0.0002909397,0.00019327356,3.359672e-7,5.7092933e-7,0.00001269138,0.00021921216],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9980699,0.00017805603,0.0011402381,0.00016165325,0.00023588346,0.00021428391],"domain_scores_gemma":[0.99620616,0.00245601,0.0006631962,0.0003707497,0.00017715979,0.00012669276],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005387159,0.00013230326,0.00037158126,0.00015620474,0.00013947731,0.00025543768,0.00092646515,0.00007097149,0.000368558],"category_scores_gemma":[0.00056816515,0.0000722311,0.00015548154,0.00010732166,0.00051271473,0.00029747727,0.00018076782,0.00022892367,0.00011903861],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008641544,0.00030073183,0.014865807,0.0000030709573,0.000054736818,0.00001688262,0.00047020707,0.0076163663,0.0001380269,0.6732868,0.0106830755,0.29170012],"study_design_scores_gemma":[0.0003157952,0.00014466906,0.0049324203,0.00001088841,0.000033330267,0.00020252942,0.0002439278,0.002435944,0.00016039489,0.9866437,0.0047779973,0.00009841524],"about_ca_topic_score_codex":0.000010954722,"about_ca_topic_score_gemma":0.000008662335,"teacher_disagreement_score":0.31335688,"about_ca_system_score_codex":0.00005266321,"about_ca_system_score_gemma":0.00006855844,"threshold_uncertainty_score":0.40354514},"labels":[],"label_agreement":null},{"id":"W2031386401","doi":"10.1093/scan/nsu097","title":"Randomness increases self-reported anxiety and neurophysiological correlates of performance monitoring","year":2014,"lang":"en","type":"article","venue":"Social Cognitive and Affective Neuroscience","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":54,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Randomness; Psychology; Anxiety; Negativity effect; Social anxiety; Order (exchange); Event (particle physics); Cognitive psychology; Social psychology; Developmental psychology; Statistics","score_opus":0.0759486822671648,"score_gpt":0.35921231858403485,"score_spread":0.28326363631687007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031386401","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99856955,0.000033541528,0.00035123847,0.00001541748,0.00033954676,0.00018744891,0.000011961259,0.00003617955,0.00045509657],"genre_scores_gemma":[0.999639,0.00015112846,0.000024076535,0.0000712725,0.000084350024,0.000009956806,4.6722496e-7,0.0000072465787,0.000012499642],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99790794,0.00039654764,0.00035953303,0.00067058846,0.00043932753,0.00022606253],"domain_scores_gemma":[0.9966595,0.002463788,0.00032238045,0.000112394744,0.00033954644,0.00010236695],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012921,0.00017037206,0.00040177736,0.00011462597,0.00057197036,0.00012141277,0.00021271537,0.00007453853,0.000004559402],"category_scores_gemma":[0.004951067,0.00012431074,0.00007841797,0.00049096916,0.00077053835,0.00041526085,0.0002454769,0.00018504678,0.0000045651072],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016987504,0.00013881801,0.59055865,0.0000065242098,0.0000050128033,0.000003968358,0.00041168314,0.0000054896313,0.015881896,0.00007454466,0.0000057146026,0.39273784],"study_design_scores_gemma":[0.0007939547,0.00042865996,0.99035436,0.000031145766,0.0000403713,0.000023634555,0.0003937179,0.0013872663,0.0028648297,0.003451267,0.00006566827,0.00016513931],"about_ca_topic_score_codex":0.000012925847,"about_ca_topic_score_gemma":0.0000010156006,"teacher_disagreement_score":0.3997957,"about_ca_system_score_codex":0.000009346498,"about_ca_system_score_gemma":0.00003010363,"threshold_uncertainty_score":0.5927247},"labels":[],"label_agreement":null},{"id":"W2031737940","doi":"10.1007/s11031-014-9436-z","title":"Bending perception to desire: Effects of task demands, motivation, and cognitive resources","year":2014,"lang":"en","type":"article","venue":"Motivation and Emotion","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Psychology; Perception; Task (project management); Biasing; Cognitive psychology; Response bias; Cognition; Contrast (vision); Cognitive bias; Attentional bias; Social psychology; Computer science","score_opus":0.06474831282725908,"score_gpt":0.33008772399618636,"score_spread":0.2653394111689273,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031737940","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93626076,0.00002038537,0.06270353,0.00027256063,0.00017999111,0.00023810305,0.000003896625,0.000028015158,0.00029275447],"genre_scores_gemma":[0.99882686,0.000015007266,0.00073776534,0.00016569451,0.00008502011,0.000006867726,0.0000117467835,0.000010006938,0.0001410415],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9984084,0.00016391452,0.00048406995,0.00042032317,0.00038697588,0.00013635156],"domain_scores_gemma":[0.99760973,0.0015879974,0.0002582111,0.00016208897,0.0002739801,0.00010801514],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013405001,0.00013126426,0.00024498583,0.0004159793,0.00021950863,0.00018626128,0.000102742735,0.000095299445,0.000034712342],"category_scores_gemma":[0.0056990525,0.00010938747,0.000039693554,0.00039787663,0.00006964892,0.00041910744,0.00007043441,0.00007311925,0.00002733469],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000037761867,0.00003496608,0.08910333,0.000017324126,0.000004823313,2.41525e-7,0.0019386017,0.0000629515,0.0037911246,0.00031915493,0.0001864072,0.9045033],"study_design_scores_gemma":[0.0005050562,0.00021607945,0.97562146,0.00024438975,0.00002749874,0.00000323316,0.0009947941,0.0021676098,0.0010964416,0.018519389,0.00046865965,0.00013539456],"about_ca_topic_score_codex":0.000017849492,"about_ca_topic_score_gemma":0.0000040114264,"teacher_disagreement_score":0.9043679,"about_ca_system_score_codex":0.000023949853,"about_ca_system_score_gemma":0.0000071942745,"threshold_uncertainty_score":0.68227094},"labels":[],"label_agreement":null},{"id":"W2035007309","doi":"10.1037/h0087327","title":"Strategy selection in causal reasoning: When beliefs and covariation collide.","year":2000,"lang":"en","type":"article","venue":"Canadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":69,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Psychology; Causality (physics); Selection (genetic algorithm); Social psychology; Causal reasoning; Attribution; Cognitive psychology; Metacognition; Causal inference; Cognition; Developmental psychology; Artificial intelligence","score_opus":0.10551642984328458,"score_gpt":0.3890571869603014,"score_spread":0.2835407571170168,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2035007309","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9899218,0.0013221679,0.000078659985,0.000942171,0.0011320864,0.00024893158,0.000041900126,0.000013567172,0.006298681],"genre_scores_gemma":[0.99560183,0.000040159666,0.0022242987,0.0011960636,0.00023433319,0.000016272506,0.000007186227,0.000034166253,0.0006457048],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9963004,0.00033363287,0.0013881308,0.0008011849,0.00018907852,0.0009875934],"domain_scores_gemma":[0.9974102,0.00020381274,0.00052678084,0.0004388009,0.00014852558,0.0012719162],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002723758,0.00032521537,0.0005996562,0.0010765289,0.0002620825,0.00030095712,0.00091626757,0.00033157005,0.0036808539],"category_scores_gemma":[0.00034701976,0.0003274261,0.00014745438,0.0006511285,0.00032763951,0.0006076608,0.000023850649,0.00054059026,0.000107746],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014040003,0.0010578335,0.3974515,0.000007279261,0.00015380525,0.0028330302,0.023950208,0.0016668444,0.046919048,0.0016506031,0.087444074,0.4354618],"study_design_scores_gemma":[0.013051547,0.0068003614,0.7501034,0.0003881367,0.00007920759,0.014857262,0.025720552,0.0010531215,0.005365421,0.104303606,0.07600364,0.0022737544],"about_ca_topic_score_codex":0.009555665,"about_ca_topic_score_gemma":0.11842611,"teacher_disagreement_score":0.43318802,"about_ca_system_score_codex":0.0013178051,"about_ca_system_score_gemma":0.00055422157,"threshold_uncertainty_score":0.9999178},"labels":[],"label_agreement":null},{"id":"W2035549323","doi":"10.3758/s13423-013-0394-3","title":"Belief bias during reasoning among religious believers and skeptics","year":2013,"lang":"en","type":"article","venue":"Psychonomic Bulletin & Review","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":115,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Psychology; Skepticism; Syllogism; Religiosity; Cognition; Cognitive psychology; Cognitive style; Association (psychology); Style (visual arts); Logical reasoning; Social psychology; Epistemology; Psychotherapist","score_opus":0.06870550286111418,"score_gpt":0.34729412377814173,"score_spread":0.2785886209170275,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2035549323","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9528191,0.035547655,0.00004286173,0.004945632,0.0007642049,0.0006966016,0.0000072068865,0.00008678696,0.005089967],"genre_scores_gemma":[0.8348744,0.14800525,0.008276303,0.0043326076,0.0003055852,0.00016272273,0.000006687172,0.00009906158,0.0039374167],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9961758,0.00020621574,0.0015882091,0.00105658,0.0004751635,0.00049801555],"domain_scores_gemma":[0.9966607,0.00074790465,0.0007520194,0.0012871731,0.00020177824,0.00035043506],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0026184875,0.00036168162,0.0008744717,0.00020185574,0.00026774456,0.0006012505,0.00094002526,0.00014344582,0.0035759935],"category_scores_gemma":[0.0017639375,0.00028879163,0.00028050278,0.00034462672,0.00020654888,0.00022816879,0.00029823146,0.00034503147,0.012094572],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011165762,0.00006167914,0.015586549,0.00011571979,0.000020684047,0.000010037072,0.00012882343,0.000015753381,0.00003689214,0.000059098107,0.3383215,0.6456321],"study_design_scores_gemma":[0.0006874773,0.00008063756,0.04837886,0.003383756,0.000088075416,0.00012746375,0.00021193443,0.00011523356,0.000018045781,0.0065525854,0.9395986,0.0007573276],"about_ca_topic_score_codex":0.00020463066,"about_ca_topic_score_gemma":0.000013127214,"teacher_disagreement_score":0.64487475,"about_ca_system_score_codex":0.00008866008,"about_ca_system_score_gemma":0.000035421657,"threshold_uncertainty_score":0.9999564},"labels":[],"label_agreement":null},{"id":"W2036753089","doi":"10.3758/s13421-012-0186-4","title":"More evidence for a dual-process model of conditional reasoning","year":2012,"lang":"en","type":"article","venue":"Memory & Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":47,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Counterexample; Probabilistic logic; Psychology; Deductive reasoning; Cognitive psychology; Inference; Competence (human resources); Logical reasoning; Causal reasoning; Artificial intelligence; Natural language processing; Cognition; Social psychology; Computer science; Mathematics; Discrete mathematics","score_opus":0.43200280190254614,"score_gpt":0.49774711247939607,"score_spread":0.06574431057684993,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2036753089","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96237534,0.000108714725,0.035490658,0.0001603654,0.00024975612,0.00022895102,0.00018516288,0.000028494953,0.0011725479],"genre_scores_gemma":[0.99511266,0.0000047281114,0.004136421,0.00023176575,0.00015000554,0.00006345928,0.000044999342,0.000012794361,0.00024319306],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99813664,0.000048044403,0.0005828868,0.00031516506,0.0006728263,0.00024445186],"domain_scores_gemma":[0.9970785,0.0014301591,0.00038065697,0.00027360543,0.00072478905,0.000112291855],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022463275,0.00012194845,0.0002525315,0.00019456811,0.00015519517,0.00007664858,0.00023934603,0.00008654326,0.0002762214],"category_scores_gemma":[0.003896382,0.00010394502,0.00014713148,0.0002308601,0.000114736446,0.0011850403,0.00005003932,0.000083334526,0.00012921907],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016685872,0.0014771662,0.010633026,0.00016112781,0.00008389589,0.0000082896095,0.007950784,0.037513994,0.06440042,0.00496886,0.01882561,0.8523082],"study_design_scores_gemma":[0.0019645747,0.0002772682,0.011484839,0.0007571009,0.00030529004,0.00007157875,0.0061615943,0.21861129,0.05347203,0.7055415,0.00051036885,0.0008426009],"about_ca_topic_score_codex":0.0000029801256,"about_ca_topic_score_gemma":0.0000023452867,"teacher_disagreement_score":0.85146564,"about_ca_system_score_codex":0.00003316048,"about_ca_system_score_gemma":0.000095500254,"threshold_uncertainty_score":0.46646145},"labels":[],"label_agreement":null},{"id":"W2037625086","doi":"10.1257/aer.98.3.1145","title":"Strotz Meets Allais: Diminishing Impatience and the Certainty Effect","year":2008,"lang":"en","type":"article","venue":"American Economic Review","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":243,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Economics; Certainty; Representation (politics); Simple (philosophy); Mathematical economics; Expected utility hypothesis; Microeconomics; Econometrics; Mathematics","score_opus":0.07887972630349924,"score_gpt":0.3963949627792216,"score_spread":0.31751523647572233,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2037625086","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9780034,0.013710373,0.00004448881,0.0038579684,0.00031306077,0.00059234345,0.000011230398,0.000031285617,0.0034358772],"genre_scores_gemma":[0.95874226,0.038047142,0.00032441414,0.0026418455,0.00006292275,0.00005935552,0.000001502926,0.000015614942,0.00010491649],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9970382,0.0005951118,0.0011066397,0.0006793102,0.00026774916,0.00031301734],"domain_scores_gemma":[0.9938612,0.003989254,0.00091626967,0.0010201962,0.000048927275,0.00016413616],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004591714,0.00024421135,0.0011942876,0.00007799737,0.00031871782,0.00020656687,0.0010734019,0.00002875886,0.0002261515],"category_scores_gemma":[0.0020245416,0.00013401477,0.00029234384,0.00023142349,0.0012963769,0.00037550405,0.00027285065,0.00017546957,0.0008207211],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030207746,0.000007978086,0.006717433,0.000011080384,0.000011629224,0.0000060352045,0.00015451443,0.000029085066,0.0000010234158,0.00017440478,0.0071355966,0.985721],"study_design_scores_gemma":[0.0033582847,0.0013155718,0.046168603,0.0014759918,0.00032193234,0.0011643362,0.0009051889,0.0053538163,0.000044211658,0.0116505325,0.9266121,0.0016294332],"about_ca_topic_score_codex":0.00043891885,"about_ca_topic_score_gemma":0.00005769074,"teacher_disagreement_score":0.9840916,"about_ca_system_score_codex":0.00008912448,"about_ca_system_score_gemma":0.00009875907,"threshold_uncertainty_score":0.99995726},"labels":[],"label_agreement":null},{"id":"W2037983318","doi":"10.1509/jppm.08.155","title":"Policy and Research Related to Consumer Rebates: A Comprehensive Review","year":2012,"lang":"en","type":"review","venue":"Journal of Public Policy & Marketing","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Payment; Multidisciplinary approach; Consumer research; Consumer protection; State (computer science); Marketing; Public economics; Consumer behaviour; Public relations; Economics; Business; Political science; Law and economics; Law; Finance","score_opus":0.5204980449335583,"score_gpt":0.5773516793151534,"score_spread":0.056853634381595075,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2037983318","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0009482209,0.98593396,0.00000404553,0.007569258,0.00055418315,0.0007202713,0.00005062453,0.000020082301,0.0041993833],"genre_scores_gemma":[0.00024901232,0.9956634,0.00061931903,0.0010412054,0.0012437312,0.000012282479,0.0000040298114,0.00008706957,0.0010799675],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.97980887,0.009141359,0.0058061653,0.0008284669,0.002955331,0.0014597814],"domain_scores_gemma":[0.95390505,0.03158045,0.0055848234,0.0016525008,0.005277511,0.0019996485],"candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication","research_integrity"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.087744065,0.00063606806,0.0042536845,0.0076196357,0.0004494055,0.0014623665,0.0027625053,0.000535394,0.0004720388],"category_scores_gemma":[0.17971103,0.00042348827,0.001145547,0.0070734103,0.0003942209,0.000934785,0.0016193403,0.0024156582,0.00069685216],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011587838,0.000049890536,0.000041330142,0.0021157488,0.00009501929,0.000034103257,0.00008465676,1.027799e-7,3.649709e-7,0.00028650876,0.028041458,0.96923923],"study_design_scores_gemma":[0.00017487712,0.00008128218,0.00008536303,0.03609351,0.0002493422,0.0021429658,0.00012474152,0.000001494481,2.999005e-8,0.0037175706,0.95696735,0.00036145368],"about_ca_topic_score_codex":0.000114376046,"about_ca_topic_score_gemma":0.0000052560604,"teacher_disagreement_score":0.9688778,"about_ca_system_score_codex":0.0008996759,"about_ca_system_score_gemma":0.005182481,"threshold_uncertainty_score":0.9998858},"labels":[],"label_agreement":null},{"id":"W2038387744","doi":"10.1080/02724990244000278","title":"The Relative Effect of Cue Interaction","year":2003,"lang":"en","type":"article","venue":"The Quarterly Journal of Experimental Psychology Section B","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Outcome (game theory); Psychology; Asymptote; Contingency; Cognitive psychology; Judgement; Econometrics; Mathematics; Mathematical economics","score_opus":0.08141772623723703,"score_gpt":0.4693003845810417,"score_spread":0.38788265834380464,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2038387744","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98539376,0.00045785678,0.0014360845,0.00037255482,0.006848981,0.00010835329,8.532306e-7,0.0000049430523,0.0053765913],"genre_scores_gemma":[0.9994964,0.0000104585715,0.00008453442,0.0000831044,0.00013734073,0.0000034917064,1.1569059e-7,0.000007816229,0.00017670845],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9970189,0.0012499108,0.0010037447,0.00017601269,0.0004100908,0.00014138549],"domain_scores_gemma":[0.99592394,0.002257007,0.0011873812,0.000398586,0.00018041149,0.00005267711],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004876018,0.0001233701,0.00028253425,0.00017557488,0.00028510275,0.00009987894,0.00051605946,0.00008548019,0.0002241455],"category_scores_gemma":[0.00037201092,0.000056699115,0.00028076133,0.00027018267,0.00025858486,0.00044291615,0.0000109878765,0.00038845904,0.000086198255],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0058833044,0.00084588944,0.00492711,0.0000016486013,0.00031034404,0.000030660914,0.014923597,0.00015683273,0.21377268,0.0043338337,0.030204345,0.72460973],"study_design_scores_gemma":[0.011635662,0.0749584,0.014638403,0.00018209995,0.0002793657,0.011530157,0.07684521,0.0002920277,0.31065366,0.3105705,0.18750668,0.000907855],"about_ca_topic_score_codex":0.0000051760535,"about_ca_topic_score_gemma":0.0000045294732,"teacher_disagreement_score":0.7237019,"about_ca_system_score_codex":0.00006415646,"about_ca_system_score_gemma":0.00001972833,"threshold_uncertainty_score":0.24542359},"labels":[],"label_agreement":null},{"id":"W2038878409","doi":"10.1037/h0087366","title":"Testing architectures of the decision–confidence relation.","year":2001,"lang":"en","type":"article","venue":"Canadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":45,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Carleton University","funders":"","keywords":"Psychology; Low Confidence; Confidence interval; Perception; Cognitive psychology; Social psychology; Statistics; Mathematics","score_opus":0.16137066060177452,"score_gpt":0.40004944956288097,"score_spread":0.23867878896110645,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2038878409","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9853605,0.0013839537,0.000508601,0.0013298672,0.0044078934,0.00024229182,0.000039352773,0.000011236553,0.0067162975],"genre_scores_gemma":[0.9925551,0.0000065294043,0.005454065,0.0015306227,0.00022624923,0.000008460065,0.0000011635289,0.000033639677,0.00018421056],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.995886,0.00031057908,0.0018190616,0.00069278805,0.00034372482,0.00094781833],"domain_scores_gemma":[0.9945865,0.0011072647,0.0013641957,0.0014083165,0.00041686418,0.0011168536],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0029964189,0.0003298597,0.00061294565,0.0009013034,0.0004084895,0.00014904766,0.0031811239,0.00025802615,0.0010641841],"category_scores_gemma":[0.0036668016,0.0002486876,0.0004235872,0.0013263767,0.00081821624,0.00025586807,0.00010505187,0.0006282476,0.00006873969],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005456851,0.00055156415,0.5202515,0.000004595735,0.00013108873,0.0020009978,0.008809353,0.0022379726,0.13228022,0.0013351595,0.044366967,0.28748488],"study_design_scores_gemma":[0.0033148618,0.0017774146,0.7013719,0.00051268074,0.000074246374,0.0191425,0.010738775,0.00017066798,0.013861458,0.21704908,0.031014608,0.000971776],"about_ca_topic_score_codex":0.0034420693,"about_ca_topic_score_gemma":0.021643676,"teacher_disagreement_score":0.28651312,"about_ca_system_score_codex":0.00067923986,"about_ca_system_score_gemma":0.0006835842,"threshold_uncertainty_score":0.99999654},"labels":[],"label_agreement":null},{"id":"W2039335428","doi":"10.1348/014466607x258696","title":"Illusion of control by proxy: Placing one's fate in the hands of another","year":2008,"lang":"en","type":"article","venue":"British Journal of Social Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta; Carleton University","funders":"Research Centre for the Humanities; Ontario Problem Gambling Research Centre","keywords":"Illusion of control; Lottery; Luck; Psychology; Ticket; Social psychology; Illusion; Perception; Advertising; Roulette; Control (management); Cognitive psychology; Computer security; Computer science","score_opus":0.10838281614715406,"score_gpt":0.4001128352617986,"score_spread":0.2917300191146445,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2039335428","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99596214,0.00032745762,0.00083682867,0.0007746849,0.00029871636,0.000091006674,0.00002716603,0.000002028911,0.001679989],"genre_scores_gemma":[0.9989014,0.000121938,0.00016875667,0.0006091495,0.00011386774,0.0000010523395,4.5016242e-7,0.000008153642,0.00007521691],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99742246,0.0003711968,0.001273756,0.00016717071,0.00059490796,0.00017049807],"domain_scores_gemma":[0.9978256,0.0004943305,0.001182856,0.00013722644,0.00032977498,0.000030214953],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032392382,0.00007826834,0.00054903433,0.00018891298,0.00012316582,0.000037582096,0.0006961385,0.00014851887,0.00019743666],"category_scores_gemma":[0.0005569408,0.00006310694,0.0002025981,0.00032475105,0.00035687262,0.00016938984,0.00002849764,0.00029675217,0.00000785349],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00073995924,0.0012242846,0.040843014,0.0000042961224,0.000043449672,0.0003682311,0.0054497067,0.000037692862,0.010730002,0.000072058894,0.069638364,0.87084895],"study_design_scores_gemma":[0.018105993,0.002419036,0.8849676,0.00038277768,0.00007803162,0.0064629572,0.0034372462,0.00006284193,0.0006845966,0.059823543,0.023108512,0.0004668595],"about_ca_topic_score_codex":0.00006325495,"about_ca_topic_score_gemma":0.000036092533,"teacher_disagreement_score":0.8703821,"about_ca_system_score_codex":0.000019700095,"about_ca_system_score_gemma":0.00005806677,"threshold_uncertainty_score":0.25734264},"labels":[],"label_agreement":null},{"id":"W2039855396","doi":"10.1037/a0013403","title":"Just tell me what to do: Bringing back experimenter control in active contingency tasks with the command-performance procedure and finding cue density effects along the way.","year":2009,"lang":"en","type":"article","venue":"Canadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Contingency; Task (project management); Outcome (game theory); Control (management); Psychology; Contingency theory; Contingency management; Social psychology; Contingency table; Cognitive psychology; Computer science; Artificial intelligence; Mathematics; Engineering; Machine learning","score_opus":0.05915164180727435,"score_gpt":0.3560247499129494,"score_spread":0.2968731081056751,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2039855396","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.989058,0.0025884234,0.00011566579,0.0050416393,0.0013469361,0.0008257459,0.000012338347,0.000008729623,0.0010024981],"genre_scores_gemma":[0.9904055,0.00003568456,0.0003388146,0.008900206,0.00016225953,0.0000331684,0.0000017218936,0.00003109512,0.00009155111],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99649864,0.00032051417,0.00093025446,0.00081902294,0.00023644991,0.001195095],"domain_scores_gemma":[0.9969253,0.0005244955,0.0005950073,0.00082632503,0.00015422987,0.00097467465],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0024107073,0.00043926187,0.00067762134,0.00061318494,0.0005730769,0.00064542756,0.0016378823,0.00019095888,0.00014508271],"category_scores_gemma":[0.00022493415,0.00028556742,0.00015398582,0.000616324,0.00045750075,0.0008685993,0.000062434796,0.0007441287,0.000040648072],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0036671718,0.0009911162,0.3930582,0.000024628584,0.000337561,0.003768893,0.1349788,0.00067002524,0.109520085,0.0002676265,0.05533555,0.29738033],"study_design_scores_gemma":[0.010453042,0.0061975033,0.78138936,0.0015208764,0.0001156687,0.009225351,0.14365114,0.0003240033,0.03802413,0.0013015579,0.0061739213,0.0016234632],"about_ca_topic_score_codex":0.0010630436,"about_ca_topic_score_gemma":0.023106432,"teacher_disagreement_score":0.38833112,"about_ca_system_score_codex":0.00082368916,"about_ca_system_score_gemma":0.00019885402,"threshold_uncertainty_score":0.99995965},"labels":[],"label_agreement":null},{"id":"W2041362059","doi":"10.1080/02724980443000160","title":"The Attraction Effect in Decision Making: Superior Performance by Older Adults","year":2004,"lang":"en","type":"article","venue":"The Quarterly Journal of Experimental Psychology Section A","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":108,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"National Institute on Aging","keywords":"Attraction; Psychology; Young adult; Domain (mathematical analysis); Developmental psychology; Heuristic; Social psychology; Cognitive psychology; Computer science; Artificial intelligence; Mathematics","score_opus":0.03219983119930698,"score_gpt":0.41138005434671165,"score_spread":0.3791802231474047,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2041362059","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99119663,0.00077131856,0.0008863772,0.0008914261,0.005740306,0.00022866992,0.0000012478512,0.000011872577,0.0002721462],"genre_scores_gemma":[0.9991911,0.000036016423,0.00013403822,0.0003506283,0.00021664573,0.000012509094,3.7594793e-7,0.000015500338,0.00004318484],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99708897,0.0003605203,0.0012475003,0.00033603897,0.0006787148,0.00028823712],"domain_scores_gemma":[0.9975497,0.0010204652,0.0007245349,0.0004960661,0.000133568,0.00007566927],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0037821003,0.00019948109,0.0003264156,0.00028038383,0.00044386234,0.00028630282,0.0008789744,0.00014952576,0.00013530818],"category_scores_gemma":[0.00014336429,0.0001025386,0.00022051312,0.00044528316,0.00021542539,0.0006664296,0.00002586607,0.0005786619,0.00016367153],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0042188787,0.00049943285,0.0037501913,8.2524946e-7,0.000018426363,0.00002221031,0.0042999773,0.00019022656,0.013365109,0.000014385057,0.006251311,0.967369],"study_design_scores_gemma":[0.05353422,0.0715645,0.6161372,0.0021706908,0.00014967461,0.016996829,0.08457908,0.001757148,0.04535531,0.056808356,0.04850676,0.0024402183],"about_ca_topic_score_codex":0.00001324071,"about_ca_topic_score_gemma":0.000033166725,"teacher_disagreement_score":0.9649288,"about_ca_system_score_codex":0.00021928636,"about_ca_system_score_gemma":0.000034840898,"threshold_uncertainty_score":0.41814026},"labels":[],"label_agreement":null},{"id":"W2041413148","doi":"10.1111/j.1539-6924.2008.01037.x","title":"Implied Preference for Seismic Design Level and Earthquake Insurance","year":2008,"lang":"en","type":"article","venue":"Risk Analysis","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Actuarial science; Preference; Seismic risk; Risk management; Insurance policy; Seismic analysis; Happiness; Business; Economics; Engineering; Finance; Microeconomics; Psychology","score_opus":0.4257793941713929,"score_gpt":0.38949549103244174,"score_spread":0.036283903138951135,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2041413148","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.70645714,0.00009510327,0.29296696,0.00006574203,0.00005105125,0.00011359311,0.00016177111,0.0000206086,0.0000680228],"genre_scores_gemma":[0.98107654,0.00024259376,0.017730499,0.00010187668,0.000028576176,0.000019664023,0.0000054072148,0.000009366478,0.0007854532],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9979006,0.00014350314,0.00062349986,0.0006545341,0.00042868403,0.00024919008],"domain_scores_gemma":[0.9967759,0.0018367184,0.0003581035,0.0006517982,0.0002453607,0.00013208245],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017626076,0.00016107138,0.00053612306,0.000521476,0.00042968907,0.0001751022,0.00046707928,0.00009075008,0.00009365308],"category_scores_gemma":[0.0011069748,0.00012081073,0.0002997473,0.0012551255,0.00011755398,0.0003061007,0.00007640318,0.00010769779,0.000157927],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009241764,0.000059656784,0.28979164,9.5193855e-7,0.0001744508,0.000005339389,0.0003963147,0.038959775,0.000061823506,0.000045019926,0.0020545297,0.6683581],"study_design_scores_gemma":[0.00052298355,0.000089248,0.8535232,0.0000042107254,0.00043896324,0.000011768195,0.00014316336,0.10291021,0.00023929952,0.037135467,0.004668626,0.00031286135],"about_ca_topic_score_codex":0.00015831964,"about_ca_topic_score_gemma":0.0001234508,"teacher_disagreement_score":0.6680452,"about_ca_system_score_codex":0.000022203598,"about_ca_system_score_gemma":0.00006337859,"threshold_uncertainty_score":0.49265185},"labels":[],"label_agreement":null},{"id":"W2041686768","doi":"10.1016/j.beproc.2014.07.021","title":"Discounting of delayed rewards: (A)theoretical interpretation of the Kirby questionnaire","year":2014,"lang":"en","type":"article","venue":"Behavioural Processes","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":133,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"National Institute of Mental Health; National Institutes of Health","keywords":"Psychology; Interpretation (philosophy); Delay discounting; Social psychology; Discounting; Developmental psychology; Cognitive psychology; Computer science; Impulsivity; Economics","score_opus":0.048147320755506824,"score_gpt":0.3573796646016789,"score_spread":0.3092323438461721,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2041686768","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9901339,0.00006375189,0.008399825,0.00034193255,0.0003607419,0.00012115383,0.000018341383,0.000022369744,0.0005380139],"genre_scores_gemma":[0.999376,0.0000031282711,0.00045473746,0.000048742786,0.000030003468,0.0000068565732,0.0000022665984,0.00001196472,0.00006629168],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9976432,0.00012252724,0.0009768509,0.00032184177,0.00077105453,0.00016457423],"domain_scores_gemma":[0.9971692,0.00070067996,0.000721579,0.00051741156,0.0008389605,0.000052169697],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0016548315,0.00013838545,0.00032935455,0.000117313284,0.000118396965,0.000102347956,0.0008981965,0.00009079534,0.00010096196],"category_scores_gemma":[0.008360868,0.00007984856,0.00014839736,0.00056044,0.0005204971,0.00035373305,0.00018151461,0.00014987268,0.0000197467],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026704467,0.00038346223,0.32254204,0.00009043528,0.000015795755,0.0000014562115,0.0025037592,0.000676768,0.0021623285,0.029328272,0.00060996553,0.64141864],"study_design_scores_gemma":[0.0009046764,0.0006310634,0.18111238,0.0014059026,0.00027056268,0.000049136317,0.0024598066,0.016459832,0.04299359,0.7527726,0.00026027043,0.00068014645],"about_ca_topic_score_codex":0.00008460261,"about_ca_topic_score_gemma":0.00010564744,"teacher_disagreement_score":0.72344434,"about_ca_system_score_codex":0.000024294402,"about_ca_system_score_gemma":0.00013179975,"threshold_uncertainty_score":0.99999213},"labels":[],"label_agreement":null},{"id":"W2041745738","doi":"10.1016/j.cognition.2012.09.012","title":"The role of answer fluency and perceptual fluency as metacognitive cues for initiating analytic thinking","year":2012,"lang":"en","type":"article","venue":"Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":213,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; University of Saskatchewan","funders":"","keywords":"Fluency; Psychology; Metacognition; Cognitive psychology; Perception; Processing fluency; Verbal fluency test; Feeling; Cognition; Metamemory; Social psychology; Neuropsychology; Mathematics education","score_opus":0.09725029981884653,"score_gpt":0.403945180666073,"score_spread":0.30669488084722646,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2041745738","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.985388,0.0008012408,0.0006329238,0.000064706175,0.00027167363,0.000263125,0.000051792566,0.000022625154,0.01250392],"genre_scores_gemma":[0.9983963,0.000045487377,0.0011475482,0.00016704298,0.00013662134,0.000029014633,0.000013452391,0.000013380408,0.000051177867],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9982064,0.00011342096,0.0006156212,0.0002928172,0.00048474045,0.00028701543],"domain_scores_gemma":[0.9954948,0.0031782247,0.00036387562,0.00021998491,0.00064863166,0.000094521056],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028155255,0.00013870899,0.0002554256,0.00016988422,0.00051987125,0.00026158334,0.00026464934,0.00008686554,0.00013004593],"category_scores_gemma":[0.0043386524,0.00009224516,0.00013475977,0.00026488554,0.00018088566,0.00085033174,0.00009656293,0.00011659018,0.00011420843],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008242283,0.00008149245,0.008634653,0.0000037721038,0.000030755164,5.4582745e-7,0.0049467864,0.0000030416609,0.0017278363,0.0020640537,0.00009530145,0.98232937],"study_design_scores_gemma":[0.0004893067,0.00022142995,0.017832365,0.00008623903,0.00024992382,0.000017107408,0.036676098,0.0010817678,0.007509589,0.9325164,0.003059068,0.00026070396],"about_ca_topic_score_codex":0.000008829121,"about_ca_topic_score_gemma":0.000014361222,"teacher_disagreement_score":0.98206866,"about_ca_system_score_codex":0.000020363255,"about_ca_system_score_gemma":0.000043950942,"threshold_uncertainty_score":0.5194086},"labels":[],"label_agreement":null},{"id":"W2042218778","doi":"10.1371/journal.pone.0020262","title":"Of Black Swans and Tossed Coins: Is the Description-Experience Gap in Risky Choice Limited to Rare Events?","year":2011,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":140,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; University of Alberta","keywords":"Rare events; Black swan theory; Probabilistic logic; Psychology; Weighting; Preference; Reflection (computer programming); Actuarial science; Ask price; Social psychology; Risk-seeking; Economics; Computer science; Medicine; Microeconomics; Statistics; Mathematics; Artificial intelligence","score_opus":0.3907233306597909,"score_gpt":0.3642609721010951,"score_spread":0.02646235855869583,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2042218778","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99768984,0.0000430903,0.00011209826,0.0005724621,0.000067956076,0.00029368282,0.000028254315,0.000015046135,0.0011775678],"genre_scores_gemma":[0.9971434,0.000030932413,0.0016709834,0.000563112,0.000019797315,0.000021408596,7.5464305e-7,0.000009569065,0.00054004375],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9980456,0.00009274713,0.00062921015,0.0004209617,0.0006053508,0.00020608988],"domain_scores_gemma":[0.99818814,0.00058297603,0.00021395153,0.0006814938,0.00022419351,0.00010924883],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008592821,0.00012440576,0.00031813091,0.0002184661,0.00008385165,0.00008607174,0.00072187936,0.00007153266,0.0005857713],"category_scores_gemma":[0.001969127,0.0000844237,0.000054952667,0.0006540618,0.00015266589,0.0003388076,0.00018561324,0.00012760317,0.00021962759],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026453024,0.002597548,0.8935496,0.000013737922,0.000042768137,0.0000099651525,0.055335194,0.000028446228,0.011007037,0.00020839785,0.0018971002,0.035045665],"study_design_scores_gemma":[0.0011414485,0.00056160806,0.9318015,0.00040753334,0.000079537655,0.0000036949243,0.013477433,0.0028027622,0.022858761,0.024474831,0.0018862344,0.0005046534],"about_ca_topic_score_codex":0.00031535918,"about_ca_topic_score_gemma":0.00041091815,"teacher_disagreement_score":0.04185776,"about_ca_system_score_codex":0.00003061622,"about_ca_system_score_gemma":0.000033008237,"threshold_uncertainty_score":0.64137846},"labels":[],"label_agreement":null},{"id":"W2042331900","doi":"10.1111/j.1754-9434.2010.01258.x","title":"What If Industrial–Organizational Psychology Decided to Take Workplace Decisions Seriously?","year":2010,"lang":"en","type":"article","venue":"Industrial and Organizational Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":55,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Premise; Conversation; Psychology; Public relations; Field (mathematics); Applied psychology; Engineering ethics; Political science; Epistemology; Engineering","score_opus":0.18721704547401288,"score_gpt":0.4220267278344396,"score_spread":0.23480968236042674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2042331900","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.944376,0.000045693163,0.0029395015,0.032292757,0.018175375,0.00053990853,0.00011098737,0.00011910783,0.0014006795],"genre_scores_gemma":[0.97794163,0.00009335001,0.0037604151,0.012689822,0.0033885958,0.000024106983,0.00014638675,0.000101819845,0.0018538564],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99441844,0.00034759613,0.0017646777,0.0017180488,0.0011074072,0.00064381014],"domain_scores_gemma":[0.99353343,0.002880431,0.00053653395,0.0011848216,0.0011244407,0.000740351],"candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication","research_integrity","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00259888,0.0004739866,0.0007566298,0.0009955874,0.0006048943,0.0010991981,0.0016266872,0.0014322364,0.0102640195],"category_scores_gemma":[0.016339896,0.00041053497,0.000120470664,0.0036328558,0.0003994331,0.00083175936,0.00048320877,0.0012604103,0.0027836803],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006405292,0.00054708007,0.1492052,4.4829994e-7,0.00006317141,0.000053548352,0.00047566227,0.00014744859,0.00514545,0.0081324205,0.3565039,0.47908515],"study_design_scores_gemma":[0.0056636813,0.0004920672,0.06318414,0.00005780872,0.00006332717,0.0007880931,0.00053444214,0.000062456325,0.00036569848,0.28128034,0.64642656,0.0010813606],"about_ca_topic_score_codex":0.000014273381,"about_ca_topic_score_gemma":0.00015965363,"teacher_disagreement_score":0.4780038,"about_ca_system_score_codex":0.00005307906,"about_ca_system_score_gemma":0.0004443217,"threshold_uncertainty_score":0.9999378},"labels":[],"label_agreement":null},{"id":"W2042676943","doi":"10.1037/0033-2909.131.5.757","title":"Biases and fallacies, memories and predictions: Comment on Roy, Christenfeld, and McKenzie (2005).","year":2005,"lang":"en","type":"letter","venue":"Psychological Bulletin","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University; University of British Columbia","funders":"","keywords":"Fallacy; Psychology; Epistemology; Value (mathematics); Cognitive psychology; Scope (computer science); Positive economics; Social psychology; Econometrics; Philosophy; Statistics; Mathematics; Computer science; Economics","score_opus":0.19113782122074144,"score_gpt":0.4033344578184449,"score_spread":0.21219663659770346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2042676943","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0920764,0.0030523774,0.000044882654,0.8970037,0.0009867057,0.00042302485,0.0003382556,0.000121145,0.0059534987],"genre_scores_gemma":[0.053483333,0.0033240302,0.001830136,0.93375635,0.0023186812,0.00008812728,0.000088919565,0.000053642343,0.0050567593],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9956426,0.00031592263,0.0010135507,0.0016361699,0.00083566847,0.0005560796],"domain_scores_gemma":[0.99438536,0.003994577,0.00041005178,0.00085751805,0.00010627409,0.00024622292],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0016176311,0.00053294416,0.0008650466,0.0003278015,0.00040205623,0.0010023509,0.00059855805,0.00093542045,0.0027697857],"category_scores_gemma":[0.001954348,0.0003561904,0.00013148774,0.00014631232,0.0008178562,0.0000719047,0.00039689842,0.001367386,0.00053477596],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006116417,0.00010576704,0.00048782967,0.000004384697,0.000012805749,0.00010149158,0.000037644033,0.000003977108,7.4103923e-7,0.000025284608,0.8833263,0.11583259],"study_design_scores_gemma":[0.0005358567,0.0005833984,0.004091225,0.00010484843,0.000039941464,0.00020248773,0.00012455828,0.000026676335,0.0000014144819,0.0058158045,0.98805887,0.00041489716],"about_ca_topic_score_codex":0.000028946408,"about_ca_topic_score_gemma":0.000011376749,"teacher_disagreement_score":0.1154177,"about_ca_system_score_codex":0.000055355595,"about_ca_system_score_gemma":0.000014295377,"threshold_uncertainty_score":0.999889},"labels":[],"label_agreement":null},{"id":"W2043155959","doi":"10.1037/h0087354","title":"Belief-Based and covariation-based cues affect causal discounting.","year":2001,"lang":"en","type":"article","venue":"Canadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Psychology; Causality (physics); Attribution; Discounting; Causal inference; Causal model; Social psychology; Affect (linguistics); Cognitive psychology; Temporal discounting; Delay discounting; Counterfactual conditional; Counterfactual thinking; Developmental psychology; Econometrics; Statistics; Impulsivity; Communication","score_opus":0.12376577122614013,"score_gpt":0.40684286137227116,"score_spread":0.283077090146131,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2043155959","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.986917,0.0016377459,0.0014199169,0.0031772137,0.003507888,0.0002914766,0.00009135514,0.000025542884,0.0029318263],"genre_scores_gemma":[0.9913875,0.000012426915,0.003396564,0.004614653,0.00032906406,0.000021712161,0.000017531456,0.000053628024,0.0001669437],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9957464,0.00034183968,0.0014037776,0.000966331,0.0002909973,0.0012507],"domain_scores_gemma":[0.9953094,0.0006511068,0.0009186767,0.0009754158,0.0002755952,0.0018697697],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0032553277,0.0004567941,0.00074439857,0.0013601326,0.00047550007,0.00043664378,0.0014934766,0.0003278632,0.0014477454],"category_scores_gemma":[0.0008900562,0.00042640654,0.00031746746,0.000743576,0.00068627956,0.00047426278,0.000042844717,0.00052774156,0.000107507905],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011781643,0.0012847036,0.76361877,0.000012252064,0.00018877121,0.0059439233,0.0053124623,0.0012979473,0.05287227,0.0008455713,0.08037493,0.08707026],"study_design_scores_gemma":[0.026779259,0.01215665,0.6253221,0.0008789803,0.00036347602,0.013615582,0.029067585,0.0040641655,0.028294481,0.04560392,0.20873849,0.0051152953],"about_ca_topic_score_codex":0.003757318,"about_ca_topic_score_gemma":0.04222528,"teacher_disagreement_score":0.13829662,"about_ca_system_score_codex":0.001038246,"about_ca_system_score_gemma":0.0008509402,"threshold_uncertainty_score":0.9998188},"labels":[],"label_agreement":null},{"id":"W2043253163","doi":"10.3758/bf03211578","title":"Not only base rates are neglected in the Engineer-Lawyer problem: An investigation of reasoners’ underutilization of complementarity","year":2000,"lang":"en","type":"article","venue":"Memory & Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of Waterloo; University of Cambridge","keywords":"Complementarity (molecular biology); Normative; Probabilistic logic; Psychology; Base (topology); Task (project management); Constraint (computer-aided design); Cognitive psychology; Social psychology; Computer science; Mathematical economics; Artificial intelligence; Epistemology; Mathematics; Economics","score_opus":0.17929786430127426,"score_gpt":0.37477334283953,"score_spread":0.19547547853825575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2043253163","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99800664,0.000009991589,0.00034886427,0.0003770984,0.000053661355,0.00035450846,0.000091756636,0.000019591009,0.00073788804],"genre_scores_gemma":[0.99823034,0.0000073113656,0.0011455567,0.0003089959,0.000021230719,0.000012336478,0.00022695053,0.000008528825,0.00003876688],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99771696,0.0004388854,0.00079585915,0.00031378536,0.0005963944,0.00013810996],"domain_scores_gemma":[0.9982922,0.0005518372,0.0003821634,0.00036132446,0.0003646091,0.00004786288],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015275325,0.00012226775,0.00024736297,0.00025070668,0.0000829864,0.00008164394,0.00032008992,0.0000735217,0.00090202043],"category_scores_gemma":[0.00031504763,0.00009257713,0.000059454665,0.00080868165,0.00011846377,0.0005040348,0.000020268148,0.00011803482,0.0000331386],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006767803,0.0013243125,0.078826666,0.00006227554,0.00002706676,0.000014705335,0.008863838,0.006885903,0.06158096,0.00065400935,0.0019682604,0.8391152],"study_design_scores_gemma":[0.001914706,0.00043206834,0.8473231,0.00028197895,0.00010122449,0.000018559147,0.0073874914,0.016323583,0.033343896,0.09226264,0.00025006037,0.00036065365],"about_ca_topic_score_codex":0.00027635458,"about_ca_topic_score_gemma":0.001577027,"teacher_disagreement_score":0.8387546,"about_ca_system_score_codex":0.00003828824,"about_ca_system_score_gemma":0.000082351915,"threshold_uncertainty_score":0.9876491},"labels":[],"label_agreement":null},{"id":"W2044003764","doi":"10.1080/13546783.2013.791642","title":"When emotions improve reasoning: The possible roles of relevance and utility","year":2013,"lang":"en","type":"article","venue":"Thinking & Reasoning","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":44,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Relevance (law); Psychology; Cognitive psychology; Cognition; Cognitive science","score_opus":0.050805653278423506,"score_gpt":0.3322174880239647,"score_spread":0.2814118347455412,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2044003764","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9894172,0.00048224992,0.0023316888,0.00085495587,0.000352632,0.00024900588,0.000010549008,0.00007551064,0.006226199],"genre_scores_gemma":[0.9783604,0.00003110857,0.020136442,0.00014107316,0.00007514754,0.000013066161,0.0000015873886,0.000018702518,0.0012224647],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99728745,0.00020317623,0.00078032224,0.0006010376,0.000773763,0.00035422615],"domain_scores_gemma":[0.9956421,0.002158793,0.0005967793,0.0010876523,0.0003934826,0.00012117298],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003927334,0.00020309948,0.00040290185,0.00013863212,0.0006303098,0.0007978173,0.0010457532,0.00012144084,0.0003245312],"category_scores_gemma":[0.0053460463,0.00012779237,0.00013969699,0.0003475105,0.00030841713,0.00072952907,0.00043736649,0.00035002688,0.00013396895],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022202774,0.000060461378,0.035135236,0.0000054182688,0.000019004603,0.0000027720582,0.0057732654,0.000091995484,0.0015352449,0.0065848487,0.0020741855,0.94869536],"study_design_scores_gemma":[0.00041078212,0.0001269934,0.14728472,0.00040377633,0.00005387465,0.000049856917,0.004547674,0.023008186,0.0013610166,0.81720597,0.005166178,0.00038097968],"about_ca_topic_score_codex":0.0005125658,"about_ca_topic_score_gemma":0.00009999663,"teacher_disagreement_score":0.94831437,"about_ca_system_score_codex":0.000029966157,"about_ca_system_score_gemma":0.00007264548,"threshold_uncertainty_score":0.76933706},"labels":[],"label_agreement":null},{"id":"W2044641675","doi":"10.1080/13546780500172490","title":"Conditional probability and pragmatic conditionals: Dissociating truth and effectiveness","year":2006,"lang":"en","type":"article","venue":"Thinking & Reasoning","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Conditional probability; Inference; Regular conditional probability; Statement (logic); Conditional expectation; Conditional independence; Law of total probability; Mathematics; Conditional probability distribution; Psychology; Econometrics; Statistics; Artificial intelligence; Cognitive psychology; Computer science; Random variable; Epistemology; Posterior probability; Philosophy; Probability mass function","score_opus":0.04135405219078417,"score_gpt":0.35201243388704573,"score_spread":0.3106583816962616,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2044641675","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99478734,0.0001705124,0.0029183677,0.00012065676,0.00017171678,0.00021210518,0.000053590313,0.00008009193,0.001485631],"genre_scores_gemma":[0.9910309,0.0000018279258,0.00870677,0.000050246665,0.000097055185,0.000021754662,0.000039552848,0.000014114085,0.00003777775],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9974343,0.00039105295,0.00058691093,0.0005999902,0.0007304447,0.00025726165],"domain_scores_gemma":[0.99098,0.00810061,0.0004071746,0.00024644998,0.00018369772,0.00008203968],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00618606,0.00018336708,0.00039351432,0.00013782652,0.00066945795,0.0007456675,0.00022838521,0.00010245414,0.00008775134],"category_scores_gemma":[0.0048462353,0.0001501502,0.00007209672,0.00023210899,0.00022361138,0.0005080475,0.00016528548,0.0002009263,0.000025210433],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006076775,0.00018153436,0.6307395,0.0000501261,0.000033234708,0.000026244126,0.0010891386,0.0010993186,0.0004139343,0.2808871,0.00030894665,0.08511016],"study_design_scores_gemma":[0.00026887015,0.000023117911,0.381179,0.00013238948,0.000014984076,0.000037340065,0.00014467,0.0016154652,0.000037797225,0.61633253,0.00008840653,0.0001254195],"about_ca_topic_score_codex":0.00007487295,"about_ca_topic_score_gemma":0.00001852405,"teacher_disagreement_score":0.3354454,"about_ca_system_score_codex":0.00009798244,"about_ca_system_score_gemma":0.00005104367,"threshold_uncertainty_score":0.71904886},"labels":[],"label_agreement":null},{"id":"W2045154181","doi":"10.2308/bria.2001.13.1.111","title":"A Research Note on the Effects of Gender and Task Complexity on an Audit Judgment","year":2001,"lang":"en","type":"article","venue":"Behavioral Research in Accounting","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":180,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Task (project management); Audit; Psychology; Consistency (knowledge bases); Social psychology; Cognition; Cognitive psychology; Balance (ability); Applied psychology; Computer science; Artificial intelligence; Accounting; Economics","score_opus":0.6534902337883695,"score_gpt":0.5838730889860605,"score_spread":0.06961714480230896,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2045154181","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9952298,0.000043720836,0.000013979382,0.00066667976,0.0002093334,0.0007648782,0.000012959866,0.000018649593,0.003040002],"genre_scores_gemma":[0.99924046,0.000039487906,0.00023125616,0.000086792395,0.00011743458,0.000077995384,0.0000026415235,0.000026844265,0.00017711725],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9905587,0.001877147,0.0008414328,0.0009972254,0.0046758326,0.0010496748],"domain_scores_gemma":[0.9856454,0.011655448,0.00019887576,0.0013672889,0.00090668024,0.00022628377],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.033328436,0.0002134153,0.0004113596,0.0015621636,0.0007703598,0.0008948299,0.0016902032,0.00017960786,0.00025901417],"category_scores_gemma":[0.0042232815,0.00013894994,0.00009829188,0.0022462127,0.0009424229,0.0004771032,0.00084745866,0.001660265,0.0003249478],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048442974,0.0016156832,0.09031713,0.000019863446,0.0000043399446,0.00025168073,0.0012990376,0.000052468593,0.005233132,0.004569038,0.0031230198,0.89303017],"study_design_scores_gemma":[0.0019106871,0.0038731408,0.72965527,0.00082158414,0.000016413476,0.000031050397,0.0079698395,0.003887869,0.00338967,0.23415767,0.013616628,0.00067016785],"about_ca_topic_score_codex":0.0012789002,"about_ca_topic_score_gemma":0.00053778285,"teacher_disagreement_score":0.89236003,"about_ca_system_score_codex":0.00032685173,"about_ca_system_score_gemma":0.00020230569,"threshold_uncertainty_score":0.9953918},"labels":[],"label_agreement":null},{"id":"W2045364899","doi":"10.1007/s11299-012-0100-6","title":"Analytic thinking: do you feel like it?","year":2012,"lang":"en","type":"article","venue":"Mind & Society","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":91,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Feeling; Fluency; Processing fluency; Type (biology); Quality (philosophy); Cognitive psychology; Philosophy of science; Psychology; Process (computing); Epistemology; Computer science; Social psychology; Mathematics education; Philosophy","score_opus":0.1506949779290272,"score_gpt":0.4053496154379318,"score_spread":0.2546546375089046,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2045364899","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9871935,0.0004291941,0.00061352015,0.0011635883,0.0015515365,0.00009702121,0.000017970448,0.00003239735,0.008901233],"genre_scores_gemma":[0.9857394,0.000020241918,0.0056836745,0.0015122616,0.00038377507,0.0000046715495,0.0000041997446,0.000018134535,0.0066336235],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9972183,0.000071451235,0.0005896242,0.00052788795,0.0010462283,0.00054649496],"domain_scores_gemma":[0.9977451,0.0006629705,0.0002720726,0.0008859218,0.00016686307,0.00026709354],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00433949,0.00020691588,0.00036352384,0.00007214888,0.00036757006,0.00060979265,0.0009827656,0.0002040921,0.002330676],"category_scores_gemma":[0.00041186277,0.0001508479,0.0006049195,0.00058740255,0.00014045037,0.00062408304,0.00029725628,0.00028056517,0.0039419774],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001078398,0.00025101745,0.051959183,0.000001957527,0.000036810874,0.0000037845518,0.017496563,0.000028752394,0.000107255866,0.00021975052,0.48771304,0.4421711],"study_design_scores_gemma":[0.0004314702,0.000055257064,0.0155741805,0.00002569535,0.00007710801,0.000024574985,0.018004816,0.0009292722,0.0001567414,0.019614875,0.9446177,0.00048830785],"about_ca_topic_score_codex":0.000017012984,"about_ca_topic_score_gemma":0.000010645425,"teacher_disagreement_score":0.45690465,"about_ca_system_score_codex":0.00012314344,"about_ca_system_score_gemma":0.00007938464,"threshold_uncertainty_score":0.99858135},"labels":[],"label_agreement":null},{"id":"W2045702439","doi":"10.1007/s10899-013-9411-8","title":"Using Sound to Unmask Losses Disguised as Wins in Multiline Slot Machines","year":2013,"lang":"en","type":"article","venue":"Journal of Gambling Studies","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":108,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Silence; Sight; Psychology; Sound (geography); Audiology; Social psychology; Acoustics; Physics; Medicine; Optics","score_opus":0.41006021259346714,"score_gpt":0.5406725113553841,"score_spread":0.13061229876191693,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2045702439","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9950901,0.0009936654,0.00058457337,0.0016370167,0.0013839939,0.00014586336,0.0000033831795,0.00001034835,0.00015102235],"genre_scores_gemma":[0.9887001,0.000121587735,0.010265085,0.00036420926,0.00031500802,0.00000240523,1.11486266e-7,0.000016535734,0.00021497138],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9967701,0.000113063514,0.0016590654,0.0003035924,0.0008517019,0.00030250006],"domain_scores_gemma":[0.9958387,0.0018564982,0.00079048023,0.00031772454,0.0010382612,0.00015831708],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0026042499,0.00021266671,0.0008268072,0.0009426449,0.00018773369,0.00044583023,0.0006660783,0.00008095406,0.00010681886],"category_scores_gemma":[0.0093688825,0.00013570212,0.00021619305,0.00075115555,0.00010751963,0.0006774313,0.00028114414,0.00034170705,0.00017284341],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033481896,0.0007407399,0.38144964,0.000021391294,0.00024311061,0.00032085928,0.009555371,0.07557903,0.009835177,0.000106219464,0.006988072,0.5148256],"study_design_scores_gemma":[0.006306307,0.0020748298,0.34263712,0.002028688,0.00030761407,0.0007823118,0.05781132,0.030780239,0.0017161567,0.5396856,0.0139,0.0019698027],"about_ca_topic_score_codex":0.00014689207,"about_ca_topic_score_gemma":0.00019956529,"teacher_disagreement_score":0.5395794,"about_ca_system_score_codex":0.0001471424,"about_ca_system_score_gemma":0.00008855004,"threshold_uncertainty_score":0.99897563},"labels":[],"label_agreement":null},{"id":"W2046545429","doi":"10.2307/3505086","title":"10.2307/3505086","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Political philosophy; Philosophy of law; Political science; Epistemology; Law; Politics; Philosophy; Comparative law","score_opus":0.06514964823937326,"score_gpt":0.32069619570708313,"score_spread":0.2555465474677099,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2046545429","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14316608,0.000016241846,0.0000032127869,0.0003850318,0.000014106489,0.00009322673,0.000019265268,0.000076254066,0.85622656],"genre_scores_gemma":[0.0077570556,1.7697407e-7,0.00039781348,0.00017195333,0.00009988986,0.000006050504,0.0000027642263,0.000015215989,0.9915491],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99813634,0.00005762977,0.0004913573,0.00047154498,0.0005709105,0.00027219654],"domain_scores_gemma":[0.9983836,0.0004434133,0.00006893475,0.00077158824,0.00010980021,0.00022268527],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0010374361,0.00013684497,0.0002616214,0.00019256683,0.00012140204,0.0003605116,0.00088493066,0.000073626805,0.9968942],"category_scores_gemma":[0.00049377215,0.000106894644,0.00012139713,0.00042823073,0.000043130374,0.00023317749,0.00009851993,0.00008948522,0.99796295],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031880314,0.000028694636,0.0000010609369,9.2510035e-8,0.0000014230225,0.0000058882183,0.000009295766,0.00014757925,0.0000104158735,0.0000012339219,0.25286797,0.7468945],"study_design_scores_gemma":[0.00012066109,0.00010284276,0.00012374311,0.0000061590413,0.0000056162985,0.000011206139,0.0000028016802,0.0003404515,0.000021303866,0.0016860615,0.9974207,0.00015845195],"about_ca_topic_score_codex":0.000014366404,"about_ca_topic_score_gemma":3.4225445e-7,"teacher_disagreement_score":0.746736,"about_ca_system_score_codex":0.000035902303,"about_ca_system_score_gemma":0.00003928299,"threshold_uncertainty_score":0.4359037},"labels":[],"label_agreement":null},{"id":"W2047410999","doi":"10.1177/1745691613483774","title":"Theory and Metatheory in the Study of Dual Processing","year":2013,"lang":"en","type":"article","venue":"Perspectives on Psychological Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":135,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Metatheory; Falsifiability; Dual (grammatical number); Constructive; Epistemology; Task (project management); Testability; Process (computing); Categorization; Confusion; Duality (order theory); Computer science; Psychology; Philosophy; Mathematics","score_opus":0.1527094310187146,"score_gpt":0.48689829322513534,"score_spread":0.33418886220642074,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2047410999","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9898862,0.000096610755,0.000103769315,0.00038878698,0.00009617333,0.00035664332,7.806656e-7,0.000011343509,0.009059647],"genre_scores_gemma":[0.99943066,0.000005796821,0.00025029771,0.00022497654,0.000014880107,0.000025289544,1.8231763e-8,0.0000025053553,0.000045600904],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99692845,0.0005747458,0.00040847957,0.000892412,0.00095918955,0.00023674063],"domain_scores_gemma":[0.9967933,0.0021971844,0.00017445281,0.00056489935,0.00020044345,0.00006967366],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.013380671,0.000113039925,0.00022587343,0.00029831118,0.0002386342,0.00042553793,0.0012536446,0.000037498954,0.00024753265],"category_scores_gemma":[0.004498743,0.000050949795,0.000039820876,0.0015143185,0.0014856354,0.00047417317,0.00013607247,0.0002107272,0.00007511004],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011399746,0.002882557,0.008883006,4.2279336e-7,0.0000018487953,0.000010387231,0.04688743,0.000031375974,0.00096967374,0.025812997,0.00008627639,0.91432005],"study_design_scores_gemma":[0.00022107192,0.0007524654,0.44853482,0.000004818672,0.0000024939825,0.0000101000405,0.20747173,0.000078572506,0.00000943889,0.34282112,0.000020050475,0.00007334483],"about_ca_topic_score_codex":0.000017613265,"about_ca_topic_score_gemma":0.000005843419,"teacher_disagreement_score":0.9142467,"about_ca_system_score_codex":0.00002729028,"about_ca_system_score_gemma":0.000018142593,"threshold_uncertainty_score":0.54738855},"labels":[],"label_agreement":null},{"id":"W2049536075","doi":"10.1016/j.jebo.2008.11.004","title":"Stereotypes in intertemporal choice","year":2008,"lang":"en","type":"article","venue":"Journal of Economic Behavior & Organization","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Respondent; Intertemporal choice; Social psychology; Psychology; Economics; Microeconomics; Political science","score_opus":0.14509064838325295,"score_gpt":0.3881977480230911,"score_spread":0.24310709963983815,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2049536075","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9976038,0.00002689059,0.00027512637,0.00027429117,0.001540495,0.00008770571,0.0000047644935,0.000010905403,0.00017602394],"genre_scores_gemma":[0.9988998,0.000023916811,0.00046431902,0.00007679196,0.00021631592,9.482208e-7,0.000003891288,0.000024850973,0.00028915986],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9974541,0.00009197466,0.0017153188,0.00025856335,0.00028929097,0.00019076225],"domain_scores_gemma":[0.99809915,0.00024384254,0.0008376637,0.0003230533,0.00037861505,0.00011767387],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0012991057,0.00014664438,0.0004561919,0.0006973085,0.00009491346,0.00016712137,0.00072357204,0.00011582001,0.001460197],"category_scores_gemma":[0.00066364085,0.00010945572,0.000116574774,0.00031760227,0.00006658812,0.0011263959,0.00010563935,0.0002298947,0.00064396503],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021980022,0.00016900856,0.962001,5.6700986e-7,0.0000047749477,0.0000771156,0.00064297294,0.0004455226,0.0012058578,0.00003362968,0.0022868207,0.03311074],"study_design_scores_gemma":[0.0016158441,0.00028968469,0.9788735,0.000038537837,0.000050937793,0.0013307297,0.0006677351,0.0002556713,0.005331733,0.003056264,0.008101581,0.0003877711],"about_ca_topic_score_codex":0.00004831755,"about_ca_topic_score_gemma":0.000102489474,"teacher_disagreement_score":0.03272297,"about_ca_system_score_codex":0.00037887212,"about_ca_system_score_gemma":0.00019488561,"threshold_uncertainty_score":0.9994526},"labels":[],"label_agreement":null},{"id":"W2049641104","doi":"10.1037/0033-295x.109.2.358","title":"False memories of the future: A critique of the applications of probabilistic reasoning to the study of cognitive processes.","year":2002,"lang":"en","type":"review","venue":"Psychological Review","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Probabilistic logic; A priori and a posteriori; Set (abstract data type); Cognition; Computer science; Cognitive science; Psychology; Space (punctuation); Outcome (game theory); Cognitive psychology; Epistemology; Artificial intelligence; Mathematics; Mathematical economics","score_opus":0.25478039883417036,"score_gpt":0.5171935579952102,"score_spread":0.2624131591610398,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2049641104","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011890765,0.9899271,0.000087083856,0.00039436665,0.00024077174,0.0072300415,0.00020089452,0.0000071715485,0.0007234847],"genre_scores_gemma":[0.01715306,0.98128235,0.000103181854,0.00021652505,0.00006277563,0.0010809695,0.0000018625288,0.000016205928,0.00008308885],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99349713,0.0014352753,0.0030621756,0.00073416135,0.0010789118,0.00019231519],"domain_scores_gemma":[0.98649836,0.0063920757,0.0034098572,0.0022085907,0.001424168,0.00006692993],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.004381165,0.00034730596,0.0027380125,0.00009139909,0.00012903828,0.000034939574,0.0037975917,0.00018356678,0.0002075589],"category_scores_gemma":[0.027946217,0.000119724216,0.0008720969,0.0037473352,0.00051658007,0.00005053288,0.0005426898,0.00047328736,0.000027971762],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005294421,0.0008326062,0.000041864852,0.004754211,0.000026524429,3.0331597e-7,0.0001835249,8.853497e-7,5.0697082e-8,0.00026166328,0.000949934,0.9929431],"study_design_scores_gemma":[0.0001589596,0.00046545643,0.00053328014,0.07813927,0.0016309299,0.000032924014,0.00089094904,6.0925305e-7,0.0000011224446,0.0075025177,0.91038686,0.00025710568],"about_ca_topic_score_codex":0.0000058247892,"about_ca_topic_score_gemma":0.0000375342,"teacher_disagreement_score":0.99268603,"about_ca_system_score_codex":0.000024674988,"about_ca_system_score_gemma":0.00015123123,"threshold_uncertainty_score":0.98024184},"labels":[],"label_agreement":null},{"id":"W2050105116","doi":"10.1037/0033-295x.114.4.994","title":"Sophisticated approval voting, ignorance priors, and plurality heuristics: A behavioral social choice analysis in a Thurstonian framework.","year":2007,"lang":"en","type":"article","venue":"Psychological Review","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":49,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Air Force Office of Scientific Research; Natural Sciences and Engineering Research Council of Canada; University of Illinois at Urbana-Champaign; National Institute of Mental Health; Institut Européen d'Administration des Affaires; University of Illinois System","keywords":"Heuristics; Voting; Condorcet method; Heuristic; Approval voting; Social choice theory; Computer science; Ignorance; Artificial intelligence; Operations research; Psychology; Economics; Microeconomics; Mathematics; Political science; Law","score_opus":0.2599384395697572,"score_gpt":0.5439416231756281,"score_spread":0.2840031836058709,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2050105116","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9769199,0.008624904,0.011222597,0.0016896236,0.00025768715,0.00049689814,0.000033665274,0.00007110349,0.00068361347],"genre_scores_gemma":[0.9912839,0.0012426078,0.00562516,0.0016498518,0.000108588305,0.000020480304,0.000009097445,0.000012958498,0.000047337453],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9950631,0.00039107614,0.0018613946,0.0012675545,0.000830558,0.00058631826],"domain_scores_gemma":[0.9963041,0.0018569899,0.0006622451,0.00068464736,0.0002209545,0.0002710703],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007912232,0.00032049112,0.0013064719,0.0003500499,0.00019410055,0.00023270118,0.00096292567,0.00033474772,0.00060743885],"category_scores_gemma":[0.00700677,0.00022663336,0.00041065828,0.0029487358,0.00039320753,0.00015020766,0.0001926879,0.00072004343,0.00018255928],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005484707,0.0006175362,0.13478616,0.000036424644,0.000020049867,0.00007860194,0.00011646547,0.0000025033187,0.000007977821,0.0015552108,0.0007495265,0.8619747],"study_design_scores_gemma":[0.00046384832,0.00019673842,0.9371442,0.00044131515,0.00047460684,0.000025000158,0.00007512089,0.00030769492,0.0000011748838,0.034044415,0.026239246,0.00058660284],"about_ca_topic_score_codex":0.00004914127,"about_ca_topic_score_gemma":0.00016438894,"teacher_disagreement_score":0.8613881,"about_ca_system_score_codex":0.00009310099,"about_ca_system_score_gemma":0.000020594685,"threshold_uncertainty_score":0.924184},"labels":[],"label_agreement":null},{"id":"W2050140390","doi":"10.1108/jpbm-11-2012-0211","title":"Price sequences, perceived variability, and choice","year":2013,"lang":"en","type":"article","venue":"Journal of Product & Brand Management","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; Brock University","funders":"","keywords":"Predictability; Preference; Revealed preference; Economics; Value (mathematics); Variance (accounting); Originality; Econometrics; Vendor; Willingness to pay; Microeconomics; Marketing; Psychology; Social psychology; Statistics; Business; Mathematics","score_opus":0.06607155138578254,"score_gpt":0.35446210262587446,"score_spread":0.28839055124009194,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2050140390","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9866192,0.00015298097,0.00103565,0.003979406,0.00089729537,0.00034220496,0.0000014111373,0.000010468468,0.0069613936],"genre_scores_gemma":[0.9882698,0.00016026902,0.008800001,0.0003024428,0.00025802615,0.000005163445,2.4341207e-7,0.000008498726,0.002195552],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9973416,0.00017350458,0.0010093772,0.0004197882,0.00083655235,0.0002192078],"domain_scores_gemma":[0.9976913,0.00048092622,0.0006221708,0.00052861345,0.000508928,0.00016807605],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0051623047,0.00014726318,0.0003746445,0.00031457652,0.0001269583,0.0006467859,0.0007364264,0.000036213416,0.0008247477],"category_scores_gemma":[0.0013340948,0.00009456247,0.00011370972,0.00033149312,0.00010167331,0.0009690146,0.0002574204,0.00018258023,0.00016257491],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032440137,0.00017324492,0.009451019,0.000018888213,0.000047483263,0.000024624727,0.0003346378,0.00015127429,0.0007948027,0.00029851502,0.026019964,0.9626531],"study_design_scores_gemma":[0.0013257385,0.00027014676,0.59705406,0.000096400465,0.000119234755,0.00019703279,0.000939035,0.00028928518,0.000089442176,0.18830653,0.21096824,0.000344843],"about_ca_topic_score_codex":0.000029583936,"about_ca_topic_score_gemma":0.0000051127054,"teacher_disagreement_score":0.9623083,"about_ca_system_score_codex":0.0000624978,"about_ca_system_score_gemma":0.0000395577,"threshold_uncertainty_score":0.90304095},"labels":[],"label_agreement":null},{"id":"W2050297329","doi":"10.5539/ijsp.v2n1p1","title":"A Competitor of the Kolmogorov--Smirnov Test for the Goodness-of-fit Problem","year":2012,"lang":"en","type":"article","venue":"International Journal of Statistics and Probability","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Kolmogorov–Smirnov test; Mathematics; Test statistic; Goodness of fit; Anderson–Darling test; Null distribution; One- and two-tailed tests; Empirical distribution function; Statistic; Pearson's chi-squared test; Statistics; Null hypothesis; Test (biology); Statistical hypothesis testing; Applied mathematics","score_opus":0.14465956577144715,"score_gpt":0.41062203538503056,"score_spread":0.2659624696135834,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2050297329","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9272909,0.00024878903,0.066191845,0.0018169242,0.0025875408,0.00033426489,0.0013046215,0.000001941994,0.00022315854],"genre_scores_gemma":[0.9701349,0.000020210296,0.029584704,0.000039995684,0.00016034838,0.0000032179862,7.48896e-7,0.000004168529,0.000051694256],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99800617,0.00006781603,0.0010009998,0.00010255197,0.0007207599,0.000101720405],"domain_scores_gemma":[0.99035615,0.0064360714,0.0011670163,0.00021470831,0.0017705318,0.00005553231],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035145637,0.00007823748,0.00023042593,0.0000573063,0.00007118516,0.00008733752,0.0008414517,0.000035364803,0.00007463989],"category_scores_gemma":[0.0049573276,0.00003727831,0.00012362,0.00009397808,0.00027639704,0.0001717032,0.0001456285,0.000119335615,0.0000015341368],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002636802,0.00079547346,0.45721155,0.000026981003,0.000097994605,9.4859604e-7,0.0010490627,0.00047603686,0.00040858233,0.037181243,0.004266063,0.49822238],"study_design_scores_gemma":[0.0006688858,0.00027422264,0.2365927,0.00009416382,0.000071644296,0.00006093773,0.00034197592,0.0021344137,0.0005283278,0.7309221,0.028204821,0.000105820705],"about_ca_topic_score_codex":0.000022639175,"about_ca_topic_score_gemma":0.000023509143,"teacher_disagreement_score":0.69374084,"about_ca_system_score_codex":0.000037675887,"about_ca_system_score_gemma":0.00012141422,"threshold_uncertainty_score":0.59347427},"labels":[],"label_agreement":null},{"id":"W2050439739","doi":"10.3758/mc.38.4.485","title":"Conditional reasoning, frequency of counterexamples, and the effect of response modality","year":2010,"lang":"en","type":"article","venue":"Memory & Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":33,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Categorical variable; Psychology; Geiger counter; Probabilistic logic; Set (abstract data type); Modality (human–computer interaction); Frequency; Response bias; Cognitive psychology; Counterexample; Mode (computer interface); Information processing; Certainty; Response time; Statistics; Social psychology; Mathematics; Artificial intelligence; Computer science; Discrete mathematics","score_opus":0.042735545157592064,"score_gpt":0.3620443540357183,"score_spread":0.3193088088781262,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2050439739","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99704885,0.00003101593,0.0002774911,0.00020304034,0.0002484551,0.00022291402,0.00021110965,0.000011653204,0.0017454576],"genre_scores_gemma":[0.9995257,0.0000021074834,0.00027921714,0.00005025293,0.000034575674,0.000014219921,0.000019818393,0.0000060959987,0.0000679894],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9978121,0.0006655835,0.00059260137,0.00027386512,0.000549776,0.00010607866],"domain_scores_gemma":[0.9924388,0.0063069235,0.00045753628,0.00041577042,0.00033173067,0.00004924661],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0092858635,0.00010696559,0.00033328062,0.00013271638,0.00011405988,0.000066292865,0.00028095357,0.00008902122,0.0005924739],"category_scores_gemma":[0.007166538,0.00006405387,0.0001155327,0.00017104375,0.0007423724,0.00020251947,0.000065465116,0.00018608032,0.000037666323],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.022727223,0.0004170378,0.06832917,0.00007320355,0.000133517,0.000033432203,0.0023265837,0.000052438245,0.3211907,0.018453088,0.0038018757,0.56246173],"study_design_scores_gemma":[0.006602885,0.0007340048,0.28835553,0.00012101203,0.00019230314,0.00012781449,0.00053206144,0.0009752841,0.06624896,0.6352395,0.00056490925,0.000305763],"about_ca_topic_score_codex":0.00009074022,"about_ca_topic_score_gemma":0.0000687736,"teacher_disagreement_score":0.6167864,"about_ca_system_score_codex":0.000009738893,"about_ca_system_score_gemma":0.000054265176,"threshold_uncertainty_score":0.8579533},"labels":[],"label_agreement":null},{"id":"W2050646562","doi":"10.1509/jmkr.45.2.159","title":"Can Trade-Ins Hurt You? Exploring the Effect of a Trade-In on Consumers' Willingness to Pay for a New Product","year":2008,"lang":"en","type":"article","venue":"Journal of Marketing Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":95,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Product (mathematics); Willingness to pay; Value (mathematics); Database transaction; Negotiation; Business; Marketing; Economics; Microeconomics; Advertising; Computer science","score_opus":0.3619868966167896,"score_gpt":0.4739426407358499,"score_spread":0.11195574411906029,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2050646562","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9864584,0.00010172796,0.00006623483,0.011990932,0.0006030748,0.00059822766,0.000007874106,0.0000052569603,0.00016827631],"genre_scores_gemma":[0.9987805,0.00008014706,0.0004427032,0.0000377211,0.00031745847,0.000021865779,2.0373481e-7,0.000023226965,0.00029616145],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9930657,0.0022318638,0.0013707889,0.0004319212,0.0022884936,0.00061122765],"domain_scores_gemma":[0.965694,0.032672413,0.00047328757,0.00057659415,0.0003037092,0.0002799876],"candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.074017845,0.000172643,0.00064896647,0.0009246695,0.00032906752,0.0001672023,0.0014056698,0.000059562724,0.000036076264],"category_scores_gemma":[0.053986523,0.00008832428,0.00030537153,0.0013188288,0.00015295944,0.00021407485,0.00011922659,0.00093588774,0.000008426519],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.007219676,0.00012290585,0.07666922,0.00002576542,0.00002396597,0.000091102695,0.0025622325,0.0006656965,0.0009630364,0.000007857866,0.013087997,0.8985605],"study_design_scores_gemma":[0.0075106444,0.0116922315,0.8326355,0.003119702,0.00007832354,0.0008584494,0.0072276206,0.0011006687,0.025095928,0.004971228,0.10488015,0.00082952104],"about_ca_topic_score_codex":0.0000749451,"about_ca_topic_score_gemma":0.00007463535,"teacher_disagreement_score":0.897731,"about_ca_system_score_codex":0.00019343183,"about_ca_system_score_gemma":0.0005619253,"threshold_uncertainty_score":0.9539822},"labels":[],"label_agreement":null},{"id":"W2051536116","doi":"10.1007/s10111-015-0334-2","title":"The effect of time constraint on anticipation, decision making, and option generation in complex and dynamic environments","year":2015,"lang":"en","type":"article","venue":"Cognition Technology & Work","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":22,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Anticipation (artificial intelligence); Constraint (computer-aided design); Cognition; Heuristic; Intervention (counseling); Computer science; Cognitive psychology; Process (computing); Psychology; Task (project management); Time constraint; Action (physics); Artificial intelligence; Mathematics; Engineering","score_opus":0.07022785863943765,"score_gpt":0.37403135774618934,"score_spread":0.3038034991067517,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2051536116","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99533874,0.00011845654,0.0035284234,0.00046405307,0.00009784043,0.00027213784,0.000007985396,0.000020056657,0.00015232449],"genre_scores_gemma":[0.9988924,0.000046624245,0.0009458288,0.000040582003,0.000009317097,0.000020027412,0.000012774942,0.0000069587136,0.000025438223],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99856085,0.00014444199,0.00051051966,0.00034753612,0.00029986197,0.00013678541],"domain_scores_gemma":[0.9983881,0.00095604535,0.00026715503,0.0002807425,0.00006175666,0.000046181474],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018062697,0.00011940068,0.00023376431,0.00041059084,0.00014508219,0.0000892691,0.00017813545,0.00017718093,0.000034394652],"category_scores_gemma":[0.0023120332,0.00008223408,0.000025247116,0.00041049518,0.00048700513,0.00010474712,0.00010657359,0.00013822716,0.00013435088],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013394006,0.000026103131,0.0117943315,5.752953e-7,0.000003696146,0.000002623841,0.00003443693,0.00015915386,0.0011670352,0.00013051061,0.00042854666,0.98611903],"study_design_scores_gemma":[0.008255804,0.004716816,0.2120328,0.0006743417,0.00016812989,0.00014983947,0.001223988,0.10483742,0.009893668,0.6510896,0.0059905127,0.000967095],"about_ca_topic_score_codex":6.10018e-7,"about_ca_topic_score_gemma":0.000008878681,"teacher_disagreement_score":0.98515195,"about_ca_system_score_codex":0.000049558275,"about_ca_system_score_gemma":0.000014298054,"threshold_uncertainty_score":0.33534083},"labels":[],"label_agreement":null},{"id":"W2052329640","doi":"10.1037/a0031451","title":"Magnitude comparison extended: How lack of knowledge informs comparative judgments under uncertainty.","year":2013,"lang":"en","type":"article","venue":"Journal of Experimental Psychology General","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Heuristics; Per capita; Context (archaeology); Magnitude (astronomy); Heuristic; Gross domestic product; Product (mathematics); Econometrics; Object (grammar); Psychology; Cognitive psychology; Social psychology; Computer science; Economics; Mathematics; Artificial intelligence; Demography; Sociology; Geography","score_opus":0.37136963209648177,"score_gpt":0.5385508077202639,"score_spread":0.1671811756237821,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2052329640","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9897137,0.00091089663,0.0005016285,0.0006259207,0.0021531691,0.00018294787,0.0000079029005,0.000007750209,0.0058960845],"genre_scores_gemma":[0.9940516,0.000014009067,0.0040797205,0.0006398429,0.00020623268,0.0000072082125,0.0000030061253,0.000013247159,0.0009851843],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.9967021,0.00025836835,0.0016845617,0.00034631396,0.0006754222,0.00033324197],"domain_scores_gemma":[0.9967612,0.00030836722,0.0015736724,0.00047531907,0.0006394249,0.00024200852],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0011617367,0.00026256288,0.0009475609,0.00048141126,0.00011667407,0.00019170085,0.0010965522,0.00017262461,0.0014963531],"category_scores_gemma":[0.00009643048,0.00017801384,0.00034579198,0.00032359918,0.00038367038,0.00074894517,0.00017845124,0.00041475167,0.00046039344],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011408966,0.0065533556,0.030628527,0.0000049015002,0.0003702873,0.000030460022,0.009303571,0.00421096,0.26641747,0.0009725223,0.52862763,0.1517394],"study_design_scores_gemma":[0.027284741,0.018163789,0.4402233,0.00030369207,0.00023890026,0.0015801772,0.10276374,0.014315511,0.18114941,0.13152415,0.07953337,0.0029192066],"about_ca_topic_score_codex":0.000021694346,"about_ca_topic_score_gemma":0.000012451222,"teacher_disagreement_score":0.44909427,"about_ca_system_score_codex":0.00012403236,"about_ca_system_score_gemma":0.000090051966,"threshold_uncertainty_score":0.9994164},"labels":[],"label_agreement":null},{"id":"W2053346049","doi":"10.1007/s00355-011-0568-8","title":"Rationality, external norms, and the epistemic value of menus","year":2011,"lang":"en","type":"article","venue":"Social Choice and Welfare","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Rationality; Norm (philosophy); Epistemology; Criticism; Value (mathematics); Decision maker; Positive economics; Rational choice theory (criminology); Social psychology; Mathematical economics; Psychology; Economics; Computer science; Management science; Philosophy; Political science; Law","score_opus":0.13705170116549992,"score_gpt":0.3743954543775198,"score_spread":0.2373437532120199,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2053346049","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99279505,0.00024443443,0.000095769945,0.0023381414,0.00018594063,0.000085796986,0.000028202758,0.000007164455,0.004219483],"genre_scores_gemma":[0.99935484,0.000020564623,0.00012544652,0.00017390966,0.00011882714,0.0000042803267,0.0000011245792,0.000004438305,0.00019658801],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9988494,0.00011904795,0.00038089353,0.00020876814,0.00033927476,0.00010261428],"domain_scores_gemma":[0.999022,0.00044043362,0.00021578559,0.00015770404,0.00012145327,0.000042642416],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013523902,0.00008016155,0.00022562414,0.00004403391,0.0003619839,0.000099492456,0.00027654052,0.00006667671,0.0002147107],"category_scores_gemma":[0.0003691543,0.00004714199,0.000077039775,0.000112026595,0.0003553467,0.00017176494,0.00013396349,0.000089205336,0.000012424522],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019448291,0.00008738952,0.16322218,0.000012131718,0.000029267749,0.0000042004226,0.008585555,0.0000019329734,0.00009244785,0.31498298,0.0010658879,0.51172155],"study_design_scores_gemma":[0.00082269195,0.000031714633,0.46928814,0.000010732637,0.000028569122,0.000008755179,0.0015847062,0.00005168751,0.00003803858,0.5213079,0.006724121,0.00010296351],"about_ca_topic_score_codex":0.00057732116,"about_ca_topic_score_gemma":0.00010322869,"teacher_disagreement_score":0.5116186,"about_ca_system_score_codex":0.000010091338,"about_ca_system_score_gemma":0.00002221218,"threshold_uncertainty_score":0.2784124},"labels":[],"label_agreement":null},{"id":"W2053520992","doi":"10.1080/13546783.2012.687892","title":"Effects of perspective and belief on analytic reasoning in a scientific reasoning task","year":2012,"lang":"en","type":"article","venue":"Thinking & Reasoning","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Psychology; Perspective (graphical); Cognitive psychology; Context (archaeology); Social psychology; Test (biology); Dual process theory (moral psychology); Task (project management); Scale (ratio); Artificial intelligence; Moral reasoning; Computer science","score_opus":0.03947755928593623,"score_gpt":0.35931031318835016,"score_spread":0.31983275390241395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2053520992","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99190086,0.0017403617,0.0005256401,0.00007904164,0.0008339351,0.00028026538,0.0000047511808,0.000073621406,0.0045615034],"genre_scores_gemma":[0.9912102,0.000016477103,0.008189795,0.000080858845,0.00013398462,0.000012287853,0.000002316559,0.000038836657,0.0003152036],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9954953,0.00038323386,0.0008970269,0.001021753,0.001394148,0.0008085176],"domain_scores_gemma":[0.9945835,0.0033316326,0.0006951813,0.00081050774,0.00030493469,0.00027422825],"candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00921765,0.00035149464,0.00078269176,0.0011954085,0.0005902747,0.00075775385,0.0007916144,0.00018688853,0.000040090214],"category_scores_gemma":[0.012015231,0.00029597167,0.0001884165,0.0016855109,0.00033018124,0.0009365968,0.0003959912,0.0005696004,0.00009422288],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004175455,0.0010286553,0.4854731,0.00006717385,0.00010965745,0.00018039299,0.085027136,0.0016611809,0.0050355876,0.11069248,0.0008004146,0.3095067],"study_design_scores_gemma":[0.004506108,0.0009989694,0.71814966,0.01076796,0.0004104213,0.00035356847,0.032238718,0.026987873,0.007320646,0.19330269,0.0024322679,0.00253112],"about_ca_topic_score_codex":0.00044283166,"about_ca_topic_score_gemma":0.00006248846,"teacher_disagreement_score":0.30697557,"about_ca_system_score_codex":0.00035811466,"about_ca_system_score_gemma":0.000112186775,"threshold_uncertainty_score":0.9999492},"labels":[],"label_agreement":null},{"id":"W2054517012","doi":"10.1002/bdm.595","title":"To buy or to sell: cultural differences in stock market decisions based on price trends","year":2008,"lang":"en","type":"article","venue":"Journal of Behavioral Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":102,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Stock market; Stock (firearms); Stock price; Financial economics; Economics; Business; Geography","score_opus":0.27664190879715905,"score_gpt":0.45870632994063953,"score_spread":0.18206442114348048,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2054517012","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9848206,0.0000312962,0.011307922,0.0006052567,0.0018675058,0.00029873836,0.000046163226,0.00003288893,0.000989641],"genre_scores_gemma":[0.9389937,0.000016547256,0.05852131,0.000895472,0.00019650842,0.000013710061,7.7129494e-7,0.000047047506,0.0013149657],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.98981917,0.00042127917,0.003640669,0.0010462767,0.0042606555,0.00081195653],"domain_scores_gemma":[0.98831624,0.007061054,0.0013171982,0.0011904621,0.0012319778,0.0008830411],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0046154456,0.00059020147,0.001513025,0.00495979,0.00046688382,0.0007603314,0.002852704,0.0002940041,0.003175728],"category_scores_gemma":[0.007194691,0.00036468566,0.00067795056,0.004672063,0.00010338814,0.00094599405,0.0004571234,0.00084469735,0.00042400407],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003680079,0.0008393277,0.058983628,7.7276553e-7,0.0000053478398,0.0013450971,0.0008447871,0.0049472963,0.00016437644,0.0000053625636,0.04940889,0.87977505],"study_design_scores_gemma":[0.003318218,0.005953169,0.94769174,0.001813078,0.00008477987,0.0011961715,0.0020614306,0.0070043136,0.00009949249,0.003762164,0.025636941,0.0013785074],"about_ca_topic_score_codex":0.000024005032,"about_ca_topic_score_gemma":0.00023534901,"teacher_disagreement_score":0.8887081,"about_ca_system_score_codex":0.0005363128,"about_ca_system_score_gemma":0.00037233598,"threshold_uncertainty_score":0.9998805},"labels":[],"label_agreement":null},{"id":"W2054821576","doi":"10.1016/s0749-5978(03)00089-x","title":"Planning, personality, and prediction: The role of future focus in optimistic time predictions","year":2003,"lang":"en","type":"article","venue":"Organizational Behavior and Human Decision Processes","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":133,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Wilfrid Laurier University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Procrastination; Psychology; Focus (optics); Optimism; Task (project management); Trait; Neglect; Personality; Cognitive psychology; Cognitive bias; Optimism bias; Cognition; Big Five personality traits; Social psychology; Debiasing; Computer science","score_opus":0.03458387996993406,"score_gpt":0.33035030470469373,"score_spread":0.29576642473475967,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2054821576","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9961615,0.0013981491,0.00050469785,0.00009727805,0.00012830019,0.00021459394,0.000121631514,0.000027432532,0.0013463687],"genre_scores_gemma":[0.99878913,0.00005758025,0.00065700716,0.00002650248,0.000080665624,0.000019952206,0.00001676113,0.000018909197,0.00033346066],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9976955,0.00008247643,0.000762776,0.0005073722,0.00078654895,0.00016530264],"domain_scores_gemma":[0.9977692,0.00089106406,0.00024741577,0.00030855858,0.0006754203,0.0001083653],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00097465777,0.00018179284,0.0002911722,0.0002975454,0.0005064013,0.00030422537,0.00035742132,0.00013227217,0.0015064428],"category_scores_gemma":[0.0015417142,0.00012492877,0.000037709007,0.0009211979,0.00023386684,0.00034592804,0.00011804725,0.00017212257,0.000022817394],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000036605445,0.0003980504,0.9569635,0.000009070671,0.000009360638,0.000007455756,0.0015594234,0.00037803242,0.00038653487,0.009208601,0.0013682235,0.029675148],"study_design_scores_gemma":[0.00090068975,0.00022276923,0.7412224,0.00012315586,0.00011465234,0.00024389323,0.0032265985,0.00023116675,0.0005750311,0.24029623,0.012503971,0.0003394315],"about_ca_topic_score_codex":0.000010088475,"about_ca_topic_score_gemma":0.00003036084,"teacher_disagreement_score":0.23108763,"about_ca_system_score_codex":0.000029316454,"about_ca_system_score_gemma":0.0001629977,"threshold_uncertainty_score":0.99940634},"labels":[],"label_agreement":null},{"id":"W2054922874","doi":"10.1007/s11166-014-9186-z","title":"Take-up for genetic tests and ambiguity","year":2014,"lang":"en","type":"article","venue":"Journal of Risk and Uncertainty","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":68,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"Pennsylvania State University","keywords":"Ambiguity; Ambiguity aversion; Affect (linguistics); Economics; Test (biology); Value (mathematics); Expected utility hypothesis; Decision maker; Private information retrieval; Subjective expected utility; Ex-ante; Value of information; Outcome (game theory); Econometrics; Microeconomics; Mathematical economics; Computer science; Psychology; Mathematics; Statistics; Biology; Machine learning","score_opus":0.07214745918230582,"score_gpt":0.3764352568517761,"score_spread":0.3042877976694703,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2054922874","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9884865,0.00034517466,0.010124111,0.00026442297,0.00060677214,0.000057930727,0.00001926352,0.000003900728,0.000091893184],"genre_scores_gemma":[0.9922771,0.00024444607,0.006983374,0.00014216822,0.00022553882,8.257349e-7,2.381492e-7,0.0000061549104,0.00012014149],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99853987,0.000104355306,0.0006632027,0.00020608454,0.00033433715,0.00015215173],"domain_scores_gemma":[0.9964029,0.0021948304,0.00064206426,0.00020166315,0.0003767127,0.00018179408],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032576371,0.00010387094,0.00035230993,0.00015633504,0.0001728492,0.00027033864,0.0002637968,0.00006912475,0.00002671586],"category_scores_gemma":[0.0045391438,0.00006459209,0.000119150965,0.00010569542,0.00009921305,0.0001563554,0.000054749537,0.0001478448,0.0000059950335],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000895904,0.00001995409,0.0388983,0.0000014167188,0.0000049216733,0.0000019007346,0.00015930999,0.00031995395,0.000034209792,0.000088763685,0.0036908393,0.95669085],"study_design_scores_gemma":[0.0017292949,0.0007386902,0.36763835,0.000039468916,0.00008666306,0.00018567777,0.00051198195,0.01184735,0.000040676518,0.44714358,0.1698323,0.00020593763],"about_ca_topic_score_codex":0.00003827688,"about_ca_topic_score_gemma":0.00008817426,"teacher_disagreement_score":0.9564849,"about_ca_system_score_codex":0.000018501545,"about_ca_system_score_gemma":0.00004400346,"threshold_uncertainty_score":0.54341066},"labels":[],"label_agreement":null},{"id":"W2055973933","doi":"10.1007/978-3-319-50727-9_7","title":"Postulates of Rational Preference","year":2017,"lang":"en","type":"book-chapter","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Northern British Columbia","funders":"","keywords":"Normative; Preference; Revealed preference; Rationality; Epistemology; Mathematical economics; Von Neumann architecture; Rational choice theory (criminology); Empirical research; Positive economics; Psychology; Mathematics; Economics; Philosophy; Econometrics; Pure mathematics; Statistics","score_opus":0.4073150163547902,"score_gpt":0.421594037110577,"score_spread":0.014279020755786798,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2055973933","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007491127,0.00008404664,0.00017752312,0.00015196529,0.0006055679,0.00011945976,0.0001295196,0.00001846591,0.9912223],"genre_scores_gemma":[0.1666543,0.000028401775,0.0010103676,0.000046430338,0.00008119228,0.0000012032981,0.000015498576,0.000015388385,0.83214724],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99744236,0.000011516079,0.00094395876,0.00052915676,0.00095651107,0.000116498035],"domain_scores_gemma":[0.99614185,0.0008036923,0.0010686681,0.0013100873,0.0005983256,0.00007739611],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00096514163,0.00021217101,0.0005439333,0.00026050137,0.00012386877,0.00029930452,0.0014663741,0.00028354922,0.01219003],"category_scores_gemma":[0.00078516256,0.00014578922,0.0002577494,0.000010897439,0.00020738292,0.00023260996,0.00030494074,0.0001779029,0.0025889317],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003673021,0.000023897634,0.00031206978,0.0000024741753,0.000021301086,0.000007901119,0.00004046227,0.000018038736,0.000040587278,0.21026962,0.02969008,0.75953686],"study_design_scores_gemma":[0.00008584085,0.000051495143,0.0006184106,0.00005341109,0.000014758403,0.000005408932,0.000005813526,0.000057791865,0.000056109067,0.75691664,0.24196474,0.00016958301],"about_ca_topic_score_codex":0.000016963313,"about_ca_topic_score_gemma":0.00007155378,"teacher_disagreement_score":0.7593673,"about_ca_system_score_codex":0.000023527831,"about_ca_system_score_gemma":0.00018772847,"threshold_uncertainty_score":0.99818766},"labels":[],"label_agreement":null},{"id":"W2056274577","doi":"10.1126/science.1214777","title":"When More Is More","year":2011,"lang":"en","type":"letter","venue":"Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Biology; Computational biology","score_opus":0.2241226963501991,"score_gpt":0.4202479743812988,"score_spread":0.1961252780310997,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2056274577","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08909677,0.00021847994,0.00034422788,0.87434363,0.007455189,0.00039314255,0.0002444251,0.0001623222,0.027741821],"genre_scores_gemma":[0.008857666,0.000013005433,0.004515364,0.94347274,0.001606368,0.000017469421,0.0000095600835,0.000050051833,0.04145775],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99214673,0.00006100345,0.0009583152,0.002090086,0.0038547267,0.0008891229],"domain_scores_gemma":[0.99489135,0.0005225948,0.0006503296,0.0029476022,0.000759873,0.0002282541],"candidate_categories":["metaepi_narrow","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0039267186,0.00040914884,0.00062704174,0.0011275791,0.00051974814,0.0015478731,0.008100023,0.00056188746,0.004814956],"category_scores_gemma":[0.0017835415,0.00028693595,0.00031107778,0.0014596937,0.00246554,0.0010486584,0.0010812269,0.0012844315,0.008553847],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000021767958,0.000010852641,0.0003211868,0.000001447763,0.0000016337267,0.00010639783,0.0010310714,9.882338e-7,0.000019331328,0.000010310375,0.8716291,0.1268655],"study_design_scores_gemma":[0.00006319835,0.000033510343,0.00076948764,0.000035975674,0.000012699867,0.00003863318,0.00017569451,0.00012248423,0.0001518916,0.09497182,0.9032336,0.00039100242],"about_ca_topic_score_codex":0.00008693619,"about_ca_topic_score_gemma":0.0000058713954,"teacher_disagreement_score":0.12647451,"about_ca_system_score_codex":0.00015261196,"about_ca_system_score_gemma":0.00075006555,"threshold_uncertainty_score":0.9999583},"labels":[],"label_agreement":null},{"id":"W2057532890","doi":"10.1016/j.cognition.2013.01.001","title":"Money is essential: Ownership intuitions are linked to physical currency","year":2013,"lang":"en","type":"article","venue":"Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":32,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Currency; Value (mathematics); Monetary economics; Velocity of money; Economics; Psychology; Money measurement concept; Virtual currency; Medium of exchange; Devaluation; Commerce; Endogenous money; Monetary policy; Computer science","score_opus":0.16532815738149167,"score_gpt":0.4136104585457624,"score_spread":0.24828230116427072,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2057532890","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98799884,0.000012003273,0.0031044437,0.0029078454,0.0005538658,0.00031039494,0.00008266727,0.00008581564,0.004944098],"genre_scores_gemma":[0.9976049,0.0000040885866,0.00039591736,0.0010451707,0.00028078415,0.00008846824,0.000027907101,0.0000144471105,0.000538286],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9981178,0.00008055827,0.0004527453,0.00052932237,0.0005697197,0.0002498503],"domain_scores_gemma":[0.99800056,0.00046297166,0.0002035491,0.00046086774,0.0006401328,0.00023189657],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003672711,0.00015748652,0.0002601382,0.00029356987,0.00019305511,0.0005763595,0.00042042765,0.00008928937,0.0025020747],"category_scores_gemma":[0.001248244,0.000119445525,0.00017111078,0.0006040654,0.00006608005,0.0006014057,0.00012835933,0.00017307154,0.03007099],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016191825,0.00040322443,0.0009903607,0.000003098687,0.000008661166,0.0000047943217,0.001006334,0.000017656408,0.0028064288,0.00022338104,0.10955858,0.8849613],"study_design_scores_gemma":[0.00057174,0.0001792985,0.038492687,0.00014712775,0.00007270977,0.000009591646,0.0024901284,0.003184906,0.003548442,0.9359216,0.014805593,0.0005761505],"about_ca_topic_score_codex":0.00001771204,"about_ca_topic_score_gemma":0.000023608683,"teacher_disagreement_score":0.9356983,"about_ca_system_score_codex":0.00004010771,"about_ca_system_score_gemma":0.00003312945,"threshold_uncertainty_score":0.99840975},"labels":[],"label_agreement":null},{"id":"W2057837355","doi":"10.1016/j.addbeh.2011.08.012","title":"Effects of cigarette smoking status on delay discounting in schizophrenia and healthy controls","year":2011,"lang":"en","type":"article","venue":"Addictive Behaviors","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":66,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"Canadian Institutes of Health Research; Health Canada","keywords":"Delay discounting; Schizophrenia (object-oriented programming); Cigarette smoking; Psychology; Discounting; Clinical psychology; Medicine; Impulsivity; Psychiatry; Internal medicine","score_opus":0.059359211605640984,"score_gpt":0.34760865621068276,"score_spread":0.28824944460504176,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2057837355","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99687207,0.000148494,0.00015894692,0.000016867762,0.00030515282,0.00047319327,0.00003812739,0.000029118377,0.0019580268],"genre_scores_gemma":[0.99930763,0.000014581127,0.00041340472,0.00010363398,0.00002036602,0.00004772476,0.0000017013114,0.00003307628,0.000057884547],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9974606,0.00017965886,0.0007774745,0.00061434146,0.0005647046,0.00040321698],"domain_scores_gemma":[0.99754775,0.0013065005,0.00047823982,0.00039408106,0.00010256497,0.00017086847],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011178567,0.0002179852,0.00051682943,0.00059891556,0.000096317584,0.00007174224,0.00033277876,0.00013146838,0.00019777249],"category_scores_gemma":[0.0008267401,0.00017366196,0.00009642461,0.00042320506,0.0002461029,0.00030550204,0.00013373552,0.00028860357,0.00003166801],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005703456,0.00029302458,0.34463662,0.000003109977,0.0000117834525,0.00006954204,0.0013531653,0.000007130764,0.00048149,0.0006874375,0.000079061465,0.6518073],"study_design_scores_gemma":[0.00207018,0.0006241694,0.98985887,0.00014934175,0.000060226423,0.000005347685,0.000562619,0.00007891512,0.001591697,0.004451547,0.00030916324,0.00023793057],"about_ca_topic_score_codex":0.00035883416,"about_ca_topic_score_gemma":0.00015495405,"teacher_disagreement_score":0.65156937,"about_ca_system_score_codex":0.000084771986,"about_ca_system_score_gemma":0.000055418182,"threshold_uncertainty_score":0.7081729},"labels":[],"label_agreement":null},{"id":"W2058559675","doi":"10.1037/a0023493","title":"Choice by value encoding and value construction: Processes of loss aversion.","year":2011,"lang":"en","type":"article","venue":"Journal of Experimental Psychology General","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada; Nederlandse Organisatie voor Wetenschappelijk Onderzoek","keywords":"Loss aversion; Value (mathematics); Encoding (memory); Economics; Tracing; Process (computing); Point (geometry); Cognition; Econometrics; Microeconomics; Cognitive psychology; Psychology; Computer science; Mathematics; Machine learning","score_opus":0.1435569179202225,"score_gpt":0.43169264435010923,"score_spread":0.2881357264298867,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2058559675","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99240285,0.0016198681,0.00041941504,0.00013177132,0.0017595275,0.000054032218,0.000009861387,0.000005295692,0.0035973499],"genre_scores_gemma":[0.9867963,0.00009934612,0.012491388,0.00032399053,0.00017031156,0.0000010738643,5.373937e-7,0.000009744422,0.00010726842],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99790686,0.00015316102,0.0010210546,0.00030835762,0.00043053337,0.00018000037],"domain_scores_gemma":[0.9981382,0.000259501,0.0009458702,0.000245288,0.00025860878,0.00015251599],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010547881,0.00015054987,0.00041926076,0.00026258652,0.000122039986,0.000050298648,0.0005296454,0.00012780054,0.00055234286],"category_scores_gemma":[0.00032700016,0.00011344534,0.00012511833,0.0002463232,0.0004423438,0.0004740473,0.000095011375,0.00021396959,0.00001730608],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00173178,0.0023908094,0.23615853,0.00001592303,0.00021791733,0.00020282384,0.007910675,0.00009024772,0.5815107,0.0025058668,0.07184418,0.09542051],"study_design_scores_gemma":[0.008438865,0.005507623,0.02638519,0.00020518439,0.00014823709,0.009711254,0.011999813,0.00019891067,0.8360411,0.067424655,0.032870386,0.0010687863],"about_ca_topic_score_codex":0.00001917685,"about_ca_topic_score_gemma":8.643824e-7,"teacher_disagreement_score":0.25453037,"about_ca_system_score_codex":0.000034558187,"about_ca_system_score_gemma":0.00006643074,"threshold_uncertainty_score":0.60477674},"labels":[],"label_agreement":null},{"id":"W2058762417","doi":"10.1016/j.addbeh.2014.04.019","title":"Delay discounting rates: A strong prognostic indicator of smoking relapse","year":2014,"lang":"en","type":"article","venue":"Addictive Behaviors","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":164,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Lethbridge","funders":"National Center for Advancing Translational Sciences; National Center for Research Resources; National Institute of General Medical Sciences; National Institute on Drug Abuse; National Institute on Alcohol Abuse and Alcoholism; National Institutes of Health","keywords":"Delay discounting; Impulsivity; Barratt Impulsiveness Scale; Hazard ratio; Discounting; Nicotine; Perceived Stress Scale; Psychology; Proportional hazards model; Clinical psychology; Confidence interval; Medicine; Demography; Internal medicine; Stress (linguistics)","score_opus":0.06541762475443866,"score_gpt":0.3803476065844001,"score_spread":0.31492998182996146,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2058762417","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9922786,0.000042224096,0.0050692,0.00004468047,0.00057423074,0.00029207076,0.000083669394,0.0000628757,0.0015524972],"genre_scores_gemma":[0.99857116,0.0000025088495,0.0010632545,0.000045007204,0.00008033226,0.000042423984,0.0000143126945,0.000037495876,0.00014350905],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9960209,0.00026532568,0.0012816737,0.0008206931,0.0011577993,0.00045361638],"domain_scores_gemma":[0.9955561,0.002039732,0.0010109044,0.0008590987,0.00033671784,0.0001974035],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030508784,0.00028515427,0.0005883173,0.00055463606,0.00025892147,0.00023843917,0.0010216621,0.00018168501,0.0005540427],"category_scores_gemma":[0.0031839863,0.00022417601,0.00026061962,0.0007007841,0.00041293597,0.0006361878,0.00030322655,0.0003672645,0.00026114626],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032205007,0.00020169663,0.7376221,0.0000019388397,0.000015034751,0.000011347861,0.00071663223,0.00011442453,0.000392784,0.0007570949,0.00046273618,0.25967205],"study_design_scores_gemma":[0.0015734995,0.0008829305,0.9598042,0.0003387748,0.00045591028,0.00004602153,0.0056116455,0.0030253173,0.0028316914,0.017388014,0.00702523,0.0010167806],"about_ca_topic_score_codex":0.00007530402,"about_ca_topic_score_gemma":0.000035970184,"teacher_disagreement_score":0.25865525,"about_ca_system_score_codex":0.00010337384,"about_ca_system_score_gemma":0.000115538984,"threshold_uncertainty_score":0.91416323},"labels":[],"label_agreement":null},{"id":"W2058941826","doi":"10.2308/ajpt-10180","title":"Does Time Constraint Lead to Poorer Audit Performance? Effects of Forewarning of Impending Time Constraints and Instructions","year":2011,"lang":"en","type":"article","venue":"Auditing A Journal of Practice & Theory","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":52,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute of Particle Physics","funders":"","keywords":"Audit; Task (project management); Warning system; Constraint (computer-aided design); Computer science; Time constraint; Performance audit; Response time; Accounting; Operations management; Business; Internal audit; Joint audit; Economics; Engineering; Political science; Management","score_opus":0.03663617092621924,"score_gpt":0.32887178716782506,"score_spread":0.2922356162416058,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2058941826","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99247867,0.00005123958,0.0021426033,0.00017582843,0.0006847084,0.00013965686,0.000013692934,0.000010980389,0.0043026484],"genre_scores_gemma":[0.98171073,0.000026495412,0.017909978,0.00010128986,0.00010777611,0.0000015269817,3.5054612e-7,0.000017465683,0.00012437685],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9967443,0.0005380704,0.0015293161,0.00027769757,0.0006394219,0.00027122413],"domain_scores_gemma":[0.98459256,0.010352451,0.0037123084,0.00031021755,0.0008495211,0.00018291995],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00982039,0.0001922543,0.0006569606,0.0006247717,0.00018788676,0.0000938472,0.000511891,0.00010188162,0.0009399513],"category_scores_gemma":[0.026104048,0.000121979196,0.00018787428,0.0003359116,0.000628507,0.0013136057,0.00018221408,0.0004284618,0.00011487013],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005837899,0.00016883758,0.003452415,0.000030763455,0.00015765175,0.0000821,0.0067817797,0.000073719435,0.026590608,0.0012926006,0.00024948144,0.96053624],"study_design_scores_gemma":[0.011036356,0.0150101315,0.08768648,0.011208461,0.0039410065,0.02278535,0.096884154,0.0027595926,0.2765994,0.45933366,0.009483667,0.0032717388],"about_ca_topic_score_codex":0.000008539204,"about_ca_topic_score_gemma":7.640115e-7,"teacher_disagreement_score":0.95726454,"about_ca_system_score_codex":0.00005484528,"about_ca_system_score_gemma":0.00022323949,"threshold_uncertainty_score":0.9999733},"labels":[],"label_agreement":null},{"id":"W2059574116","doi":"10.1371/journal.pone.0123740","title":"The Effect of Time Pressure on Risky Financial Decisions from Description and Decisions from Experience","year":2015,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Risk-seeking; Actuarial science; Risk analysis (engineering); Economics; Psychology; Econometrics; Finance; Medicine","score_opus":0.2101182564957566,"score_gpt":0.34751355669183087,"score_spread":0.13739530019607427,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2059574116","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.997163,0.00069661177,0.00046399207,0.00015285611,0.00035884694,0.00031639962,0.00035832872,0.000033053057,0.00045690726],"genre_scores_gemma":[0.9967224,0.00008203071,0.0024084493,0.000048409656,0.0001418009,0.00003348279,0.000013773171,0.000016787932,0.000532864],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9962218,0.00037685674,0.00081954343,0.0006843065,0.001638408,0.0002591341],"domain_scores_gemma":[0.98177844,0.016025959,0.00037808868,0.0012278117,0.00031469006,0.00027500474],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0019042898,0.00022460298,0.0005942148,0.00015101286,0.00035830936,0.00041818488,0.0010590277,0.00017996825,0.00023079247],"category_scores_gemma":[0.033064526,0.00013283716,0.00012211547,0.00035477325,0.0002532763,0.000379164,0.0003447299,0.00024544564,0.00085821777],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0027201916,0.0013703397,0.062887356,0.0000012696848,0.00012565417,0.000022612878,0.0033557254,0.00032080425,0.01602593,0.00011171943,0.026611207,0.8864472],"study_design_scores_gemma":[0.008792909,0.007937811,0.23506854,0.0022821066,0.0013841477,0.000008366523,0.0021494797,0.040134292,0.090234905,0.56309265,0.046950158,0.0019646354],"about_ca_topic_score_codex":0.00031634961,"about_ca_topic_score_gemma":0.00012796356,"teacher_disagreement_score":0.88448256,"about_ca_system_score_codex":0.00003823186,"about_ca_system_score_gemma":0.000078481644,"threshold_uncertainty_score":0.9999197},"labels":[],"label_agreement":null},{"id":"W2059764265","doi":"10.1007/s001990100207","title":"Subjective ambiguity, expected utility and Choquet expected utility","year":2002,"lang":"en","type":"article","venue":"Economic Theory","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":69,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Ambiguity; Axiom; Choquet integral; Expected utility hypothesis; Subjective expected utility; Mathematical economics; Decision maker; Simple (philosophy); Set (abstract data type); Mathematics; Key (lock); Measure (data warehouse); Computer science; Artificial intelligence; Fuzzy logic; Operations research; Data mining","score_opus":0.14138795755228675,"score_gpt":0.35802778432695087,"score_spread":0.21663982677466412,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2059764265","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9608188,0.00038169645,0.00037935696,0.00018302775,0.0010265245,0.0002612565,0.00013198954,0.00016055704,0.03665675],"genre_scores_gemma":[0.99734414,0.000033732947,0.00022880439,0.00016689993,0.00015224812,0.000020006804,0.000004927236,0.000026576061,0.002022664],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9961953,0.00064547086,0.0011135057,0.0013046826,0.00026848484,0.0004725192],"domain_scores_gemma":[0.9953657,0.0023553208,0.00042736728,0.0014479075,0.00012066853,0.00028304762],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0038514547,0.0003385741,0.000687656,0.00030890014,0.00033288676,0.00049128925,0.0009450553,0.00021888732,0.01844001],"category_scores_gemma":[0.0017589519,0.0002961736,0.00023153792,0.00022868665,0.00052716397,0.00066633895,0.0004471516,0.00031424395,0.0027379363],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029409034,0.00030176877,0.052796837,0.0000028436914,0.00004954828,0.000019423147,0.0030510537,0.000013175359,0.00009691142,0.0052797697,0.011505893,0.9265887],"study_design_scores_gemma":[0.0011358461,0.00011763865,0.26745078,0.000014775517,0.00003011273,0.000050648137,0.00326666,0.005421148,0.00057295215,0.70478845,0.016498376,0.0006526381],"about_ca_topic_score_codex":0.00011483815,"about_ca_topic_score_gemma":0.00020054735,"teacher_disagreement_score":0.92593604,"about_ca_system_score_codex":0.00019252497,"about_ca_system_score_gemma":0.000056522622,"threshold_uncertainty_score":0.99994904},"labels":[],"label_agreement":null},{"id":"W2059998814","doi":"10.1080/02699931003593942","title":"Negative emotions can attenuate the influence of beliefs on logical reasoning","year":2010,"lang":"en","type":"article","venue":"Cognition & Emotion","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Psychology; Syllogism; Content (measure theory); Affect (linguistics); Consistency (knowledge bases); Scrutiny; Contrast (vision); Cognitive psychology; Social psychology; Logical reasoning; Epistemology","score_opus":0.09933546512834393,"score_gpt":0.37330175466992443,"score_spread":0.27396628954158053,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2059998814","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99360526,0.0000016415221,0.0008077664,0.0016575679,0.00048283883,0.00019969355,0.0000636395,0.000039834027,0.0031417354],"genre_scores_gemma":[0.99871254,0.0000052062305,0.0005149969,0.0004515894,0.0001151891,0.000011235301,0.00001549389,0.000009044116,0.00016473378],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99798214,0.0001854036,0.00059265736,0.00040947224,0.0006452539,0.00018508047],"domain_scores_gemma":[0.99689794,0.0013084413,0.00043906024,0.0005077205,0.00075799745,0.000088844885],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016276415,0.00013831256,0.00020849134,0.00019540856,0.0003785587,0.00017528255,0.0004426074,0.0001255386,0.00040103478],"category_scores_gemma":[0.005989592,0.000088062705,0.00012830581,0.0005498958,0.0003071617,0.000275999,0.00008278751,0.00041018997,0.00057208835],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011354664,0.00054311403,0.0066363146,0.0000040612636,0.000022959415,0.000011719666,0.0027241888,0.005923983,0.028293662,0.010819643,0.0023261423,0.94258064],"study_design_scores_gemma":[0.00049063144,0.00025597942,0.71538544,0.00012672262,0.000037354348,0.000030958865,0.0008895817,0.0011863909,0.0031180717,0.27742672,0.0008329704,0.00021917172],"about_ca_topic_score_codex":0.000040632873,"about_ca_topic_score_gemma":0.00013296395,"teacher_disagreement_score":0.9423615,"about_ca_system_score_codex":0.00002522368,"about_ca_system_score_gemma":0.000054055803,"threshold_uncertainty_score":0.73532295},"labels":[],"label_agreement":null},{"id":"W2060242101","doi":"10.1080/10517120903000363","title":"Purchasing Higher-Value, Higher-Price Offerings in Business Markets","year":2010,"lang":"en","type":"article","venue":"Journal of Business-to-Business Marketing","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":93,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Purchasing; Ambiguity; Value (mathematics); Incentive; Marketing; Business; Revenue; Construct (python library); Business value; Empirical evidence; Empirical research; Microeconomics; Economics; Industrial organization; Accounting","score_opus":0.05685151412834891,"score_gpt":0.34777481226170015,"score_spread":0.29092329813335127,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2060242101","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9617934,0.00010828368,0.0035452123,0.017731486,0.013024044,0.00038503917,0.000014357151,0.00006856413,0.0033296165],"genre_scores_gemma":[0.9753805,0.000049105736,0.02036636,0.0011408479,0.001950074,0.000013278589,0.0000030746817,0.00014299207,0.00095377595],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.98991764,0.0005741051,0.004089761,0.0012610398,0.0029113272,0.0012461432],"domain_scores_gemma":[0.98274887,0.004365533,0.0026652757,0.0014361547,0.008026713,0.0007574426],"candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.020293368,0.0007958333,0.0018211547,0.0037924347,0.00043162372,0.0018582497,0.0032538571,0.00046821832,0.0015041294],"category_scores_gemma":[0.032639936,0.0006553573,0.00031537242,0.013090552,0.00019138024,0.0023164395,0.0011414365,0.0012704773,0.00030389967],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004916457,0.0009831376,0.14882298,0.00018945329,0.00006549493,0.0014206205,0.00038346258,0.012761316,0.056591704,0.00022533853,0.012402207,0.7612378],"study_design_scores_gemma":[0.0011384349,0.000033348282,0.88336694,0.0009787752,0.000042856707,0.00036452775,0.00010416549,0.00032430838,0.000071702874,0.001970419,0.11087251,0.00073200476],"about_ca_topic_score_codex":0.00012983367,"about_ca_topic_score_gemma":0.00007215604,"teacher_disagreement_score":0.7605058,"about_ca_system_score_codex":0.00033021602,"about_ca_system_score_gemma":0.0007073034,"threshold_uncertainty_score":0.99958974},"labels":[],"label_agreement":null},{"id":"W2061532330","doi":"10.1006/jmps.2000.1357","title":"Random Relations, Random Utilities, and Random Functions","year":2001,"lang":"en","type":"article","venue":"Journal of Mathematical Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":60,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Probabilistic logic; Complement (music); Mathematics; Random element; Random variable; Measure (data warehouse); Metric (unit); Sample space; Random function; Probability measure; Function (biology); Binary relation; Binary number; Respondent; Discrete mathematics; Statistics; Computer science; Data mining; Arithmetic","score_opus":0.1565933696493799,"score_gpt":0.4396660119605228,"score_spread":0.28307264231114293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2061532330","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7952362,0.00064945396,0.1746764,0.005082765,0.0012009958,0.000178955,0.000006714197,0.000018054554,0.022950474],"genre_scores_gemma":[0.9877407,0.00019933752,0.0066221696,0.00064108754,0.00027978723,0.0000055630153,8.473703e-7,0.000017910088,0.0044926163],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99639714,0.00040784385,0.002019031,0.00029340512,0.00063020014,0.00025237724],"domain_scores_gemma":[0.9910285,0.0071200053,0.00077879336,0.0004722388,0.00036035062,0.0002401226],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0067406525,0.0001702535,0.00090030365,0.0004693206,0.00017659146,0.00018535946,0.00047305206,0.00018897346,0.0043410016],"category_scores_gemma":[0.007366618,0.00010804058,0.0003367862,0.00034555822,0.00028861384,0.00036337168,0.00006141436,0.0004243844,0.0008180021],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.013526063,0.0014986808,0.009051028,0.000012244243,0.00020735007,0.000344939,0.0014408802,0.00023295518,0.0002729344,0.005131359,0.25811967,0.71016186],"study_design_scores_gemma":[0.017539179,0.00030476638,0.0026580805,0.000056789067,0.00010957263,0.0037411442,0.00071595784,0.0009022479,0.0000033996303,0.8558205,0.117979124,0.00016925443],"about_ca_topic_score_codex":0.0000010988523,"about_ca_topic_score_gemma":0.0000030373124,"teacher_disagreement_score":0.8506891,"about_ca_system_score_codex":0.000030138324,"about_ca_system_score_gemma":0.000057341826,"threshold_uncertainty_score":0.99996},"labels":[],"label_agreement":null},{"id":"W2061592058","doi":"10.1142/9789814417358_0016","title":"Choices, Values, and Frames","year":2013,"lang":"en","type":"book-chapter","venue":"World Scientific handbook in financial economic series","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5411,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Psychology","score_opus":0.06283925947885162,"score_gpt":0.3116454462296101,"score_spread":0.2488061867507585,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2061592058","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0958621,0.008562867,0.000040780964,0.0006568111,0.018055575,0.0012286799,0.00058371475,0.00015256298,0.8748569],"genre_scores_gemma":[0.0052226307,0.0002886057,0.0010616762,0.0001962953,0.0004930805,0.00004010893,0.000037447924,0.00007111746,0.99258906],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9944675,0.000058755293,0.0020496708,0.0021659469,0.00062551576,0.000632643],"domain_scores_gemma":[0.996217,0.0007822523,0.0009771839,0.0015555171,0.00018353468,0.00028452283],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0031020022,0.00067302334,0.0014170695,0.0019506704,0.0005952327,0.0032534366,0.0014768149,0.0004934795,0.009859551],"category_scores_gemma":[0.000513664,0.00061726576,0.0003123008,0.00018213324,0.0017077383,0.0012984854,0.00068107207,0.0006652766,0.009578068],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007859666,0.00003260049,0.0006361394,0.000014981515,0.000016260572,0.00004241677,0.0006019358,0.00008734815,0.00002057332,0.0811348,0.31729475,0.6000396],"study_design_scores_gemma":[0.00019104974,0.000029913215,0.00028759285,0.00023823409,0.000012330706,0.000010526693,0.00002701248,0.00007499674,0.000030699102,0.41327992,0.5853775,0.0004402045],"about_ca_topic_score_codex":0.000103878,"about_ca_topic_score_gemma":0.009022753,"teacher_disagreement_score":0.5995994,"about_ca_system_score_codex":0.0003883064,"about_ca_system_score_gemma":0.00073321466,"threshold_uncertainty_score":0.9996279},"labels":[],"label_agreement":null},{"id":"W2062195281","doi":"10.1177/0146167202239041","title":"Younger Achievement Age Predicts Shorter Life for Governors: Testing the Precocity-Longevity Hypothesis With Artifact Controls","year":2003,"lang":"en","type":"article","venue":"Personality and Social Psychology Bulletin","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Cape Breton University","funders":"","keywords":"Longevity; Life expectancy; Psychology; Artifact (error); Expectancy theory; Demography; Life span; Test (biology); Developmental psychology; Social psychology; Gerontology; Biology; Medicine; Population","score_opus":0.25249491907979255,"score_gpt":0.3877270803772464,"score_spread":0.13523216129745386,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2062195281","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9727448,0.00007639285,0.0011915537,0.020651517,0.0002550051,0.0005394853,0.00013121076,0.000032902797,0.0043771067],"genre_scores_gemma":[0.98807794,0.000005834982,0.0018552693,0.009047539,0.00021904966,0.000088235414,0.000003781564,0.000018391902,0.0006839612],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9971062,0.00061564636,0.0005947871,0.00074354664,0.00051565445,0.000424172],"domain_scores_gemma":[0.99506795,0.0039025364,0.00034722715,0.00036370856,0.0001872175,0.00013136967],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0052955174,0.0002362724,0.0005170716,0.000047384223,0.0008514522,0.00032663342,0.00041721054,0.00020798526,0.0008752869],"category_scores_gemma":[0.0035409925,0.00014716997,0.00017736941,0.0001540725,0.0005669346,0.00009343211,0.00004764619,0.0002884984,0.000093678864],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0029680259,0.0017576545,0.30245727,0.000032541713,0.0004981516,0.000038143407,0.009019633,0.00003132024,0.00049086777,0.0025342007,0.22226511,0.45790708],"study_design_scores_gemma":[0.0016937929,0.00038248362,0.66368496,0.00001530232,0.00012250476,0.00001780967,0.0015924731,0.000030587336,0.000008395467,0.024540061,0.30755633,0.0003552896],"about_ca_topic_score_codex":0.00006930244,"about_ca_topic_score_gemma":0.000105549916,"teacher_disagreement_score":0.45755178,"about_ca_system_score_codex":0.000041540425,"about_ca_system_score_gemma":0.00005924744,"threshold_uncertainty_score":0.9583777},"labels":[],"label_agreement":null},{"id":"W2063479817","doi":"10.1007/s11238-007-9065-z","title":"Utility of Gambling when Events are Valued: an Application of Inset Entropy","year":2007,"lang":"en","type":"article","venue":"Theory and Decision","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria; University of Waterloo","funders":"","keywords":"Mathematics; Entropy (arrow of time); Binary entropy function; Mathematical economics; Utility theory; Statistics; Principle of maximum entropy","score_opus":0.12925279367505316,"score_gpt":0.42914729220514236,"score_spread":0.2998944985300892,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2063479817","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.74496305,0.00009751769,0.25433496,0.0000065711833,0.00014297836,0.000121883175,0.000026623218,0.000012476067,0.00029392156],"genre_scores_gemma":[0.99274594,0.000012080815,0.0071210875,0.000042004016,0.00003482336,0.0000012858002,0.0000048138545,0.000008745691,0.000029211002],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99714255,0.00024080307,0.0011539254,0.00049127796,0.00078717317,0.00018424676],"domain_scores_gemma":[0.9946122,0.0032715937,0.00071666355,0.0009107217,0.0003462206,0.00014255439],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.015090469,0.00013721069,0.00042014476,0.00034869876,0.0001062942,0.000040141098,0.00057710166,0.00013303407,0.00022259928],"category_scores_gemma":[0.0020786098,0.00010107411,0.00011049396,0.00033220288,0.00015078773,0.0003717391,0.00018085376,0.00010903045,0.000038685404],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013765862,0.00019470204,0.034264397,0.0000029630369,0.0000037841783,0.0000014423688,0.00038416224,0.00002570992,0.0014779093,0.008101834,0.0000682493,0.9540983],"study_design_scores_gemma":[0.00039201725,0.00011226044,0.11790256,0.00003895701,0.000014060783,0.000005400378,0.0009402794,0.0014678588,0.0034084874,0.8750756,0.00054450345,0.00009805163],"about_ca_topic_score_codex":0.00001898508,"about_ca_topic_score_gemma":0.000028165661,"teacher_disagreement_score":0.95400023,"about_ca_system_score_codex":0.000012109087,"about_ca_system_score_gemma":0.000025605206,"threshold_uncertainty_score":0.5230085},"labels":[],"label_agreement":null},{"id":"W2063976265","doi":"10.1016/j.jmoneco.2006.11.001","title":"Consumption–leisure nonseparabilities in asset market participants’ preferences","year":2007,"lang":"en","type":"article","venue":"Journal of Monetary Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Economics; Asset (computer security); Consumption (sociology); Econometrics; Panel data; Sample (material); Permanent income hypothesis; Microeconomics; Financial economics; Finance; Market liquidity; Computer science","score_opus":0.2275205569344006,"score_gpt":0.4053023670920823,"score_spread":0.17778181015768169,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2063976265","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99596065,0.00040198135,0.0002216813,0.00030236447,0.0012376765,0.00010261599,0.00003359779,0.000007724491,0.0017317218],"genre_scores_gemma":[0.99674886,0.00034964608,0.0023386474,0.000115194474,0.00016498246,0.0000012171653,0.0000015777257,0.000012291849,0.00026756138],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9959494,0.00018594255,0.0027034674,0.00035164403,0.0003615752,0.0004479761],"domain_scores_gemma":[0.9943965,0.0033439475,0.0013106959,0.000476412,0.00020726411,0.000265201],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.012670845,0.00020408432,0.00076579006,0.0007247695,0.000077276614,0.0002723761,0.0008984196,0.00016296931,0.0012789131],"category_scores_gemma":[0.0011582666,0.00016210636,0.00026461398,0.00019123044,0.00017919274,0.00095055695,0.000097941025,0.00039649746,0.00019530048],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00042407488,0.00014705252,0.8623789,0.0000030667393,0.0000261465,0.000056330875,0.00032720054,0.004113036,0.000014758045,0.00006920813,0.0037865238,0.1286537],"study_design_scores_gemma":[0.000884555,0.00028220087,0.8830787,0.00005558795,0.00003471426,0.00016537274,0.0015558986,0.0031170468,0.0001218904,0.09721564,0.013192121,0.00029625336],"about_ca_topic_score_codex":0.00003620403,"about_ca_topic_score_gemma":0.001262627,"teacher_disagreement_score":0.12835744,"about_ca_system_score_codex":0.00017284299,"about_ca_system_score_gemma":0.00020082103,"threshold_uncertainty_score":0.999634},"labels":[],"label_agreement":null},{"id":"W2064245470","doi":"10.3758/s13423-013-0542-9","title":"Remembering the best and worst of times: Memories for extreme outcomes bias risky decisions","year":2013,"lang":"en","type":"article","venue":"Psychonomic Bulletin & Review","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":136,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Alberta Gambling Research Institute, University of Calgary; National Research Council Canada; Natural Sciences and Engineering Research Council of Canada; National Institute on Aging; National Institutes of Health","keywords":"Psychology; Recall; Outcome (game theory); Social psychology; Task (project management); Salient; Cognitive psychology; Economics","score_opus":0.3309553820656819,"score_gpt":0.42014273025082266,"score_spread":0.08918734818514074,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2064245470","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.80051965,0.12296427,0.0016744044,0.054251824,0.0032534301,0.004768366,0.00011726771,0.0000887985,0.012361974],"genre_scores_gemma":[0.75781554,0.15504856,0.05362277,0.010886052,0.00055890874,0.0013961084,0.000017544804,0.00020469294,0.020449841],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99659693,0.0001715409,0.0018131856,0.00069348933,0.0003964527,0.00032842296],"domain_scores_gemma":[0.9903879,0.0068232804,0.0008716148,0.0014422414,0.00032267816,0.0001522735],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0041748905,0.0002973081,0.0010183958,0.00014166062,0.0002697676,0.00033566408,0.0012228119,0.00008678102,0.0031625535],"category_scores_gemma":[0.005696456,0.00016702611,0.0004305496,0.00029201756,0.00025267957,0.00015347921,0.00025499595,0.00016749893,0.0026582398],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011845468,0.0000597956,0.0029619697,0.00004608526,0.00002178736,3.3170804e-7,0.00006662675,0.0000072552575,0.000010800205,0.00021546098,0.19476283,0.80183524],"study_design_scores_gemma":[0.0003638371,0.00006873724,0.0025325662,0.0013421188,0.00010297883,0.000015673202,0.00044386197,0.00009044256,0.0000120738005,0.025540676,0.9692212,0.00026588095],"about_ca_topic_score_codex":0.000080578604,"about_ca_topic_score_gemma":0.000028831762,"teacher_disagreement_score":0.80156934,"about_ca_system_score_codex":0.00003125954,"about_ca_system_score_gemma":0.000042793192,"threshold_uncertainty_score":0.9981183},"labels":[],"label_agreement":null},{"id":"W2064661564","doi":"10.1002/mar.20162","title":"Developing heuristic‐based quality judgments: Blocking in consumer choice","year":2007,"lang":"en","type":"article","venue":"Psychology and Marketing","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Heuristics; Quality (philosophy); Blocking (statistics); Affect (linguistics); Product (mathematics); Order (exchange); Heuristic; Psychology; Process (computing); Advertising; Block (permutation group theory); Marketing; Information quality; Computer science; Business; Information system; Artificial intelligence; Communication","score_opus":0.2684398167341324,"score_gpt":0.5225066344660648,"score_spread":0.2540668177319324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2064661564","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9776834,0.00025070185,0.011187157,0.0008212523,0.0007340422,0.000100308156,0.0000030736421,0.00003109683,0.009188972],"genre_scores_gemma":[0.98833466,0.000023527737,0.009231634,0.002262899,0.000052412073,0.0000038482062,0.0000015440138,0.000009841843,0.000079630474],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9970332,0.0005108987,0.0010790041,0.0006674828,0.00029275904,0.0004167009],"domain_scores_gemma":[0.9895622,0.009524605,0.0003357325,0.000373548,0.00010889153,0.00009501054],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.023775479,0.00015130853,0.00032884482,0.0003873709,0.0001935986,0.000109764136,0.00034797564,0.00016447733,0.00016282826],"category_scores_gemma":[0.010383708,0.00013338307,0.0000522183,0.0004384209,0.00014802303,0.00012914573,0.00010957289,0.00027518347,0.000059331225],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014623339,0.000036848935,0.44544202,0.000003342385,0.0000029295295,0.000018416076,0.000046864232,0.0000037290683,0.00013922866,0.0000923818,0.00029613753,0.55377185],"study_design_scores_gemma":[0.00089594565,0.00001712068,0.9527298,0.00007771709,0.0000059070735,0.000016472322,0.0002593223,0.00015008244,0.00004886336,0.011142328,0.034422886,0.00023353408],"about_ca_topic_score_codex":0.000043976313,"about_ca_topic_score_gemma":0.00029520408,"teacher_disagreement_score":0.5535383,"about_ca_system_score_codex":0.00004230925,"about_ca_system_score_gemma":0.00004005399,"threshold_uncertainty_score":0.9979522},"labels":[],"label_agreement":null},{"id":"W2066188514","doi":"10.1007/s11238-012-9348-x","title":"Emotional balance and probability weighting","year":2012,"lang":"en","type":"article","venue":"Theory and Decision","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":37,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"National Taiwan University","keywords":"Weighting; Balance (ability); Normative; Balance theory; Psychology; Econometrics; Social psychology; Mathematics; Statistics; Physics; Political science","score_opus":0.08542908166859771,"score_gpt":0.3755244638367624,"score_spread":0.2900953821681647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2066188514","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98156327,0.000640858,0.015035462,0.000068706395,0.0004762436,0.00009874463,0.0000097730135,0.00002966523,0.002077305],"genre_scores_gemma":[0.9909294,0.000028831968,0.008590906,0.00015712967,0.00014262935,0.0000029833334,0.000001130382,0.000007392114,0.00013960064],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9980599,0.00024986346,0.00051362655,0.00042568796,0.0004893506,0.00026156195],"domain_scores_gemma":[0.99318725,0.0059070596,0.0001512216,0.00043184633,0.00010383834,0.0002187794],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0114076035,0.00013815603,0.00025665291,0.00012819938,0.00029561628,0.00022671557,0.00024748442,0.000094875504,0.00046717213],"category_scores_gemma":[0.003591264,0.00009147703,0.000058040838,0.00020025956,0.0001920463,0.000688086,0.0002757842,0.00013095653,0.00024966363],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001682965,0.000059548616,0.0457003,0.0000012623075,0.000001893285,0.0000010462228,0.00028125715,0.000005350858,0.00011008943,0.046870396,0.00037494212,0.9064256],"study_design_scores_gemma":[0.00021946707,0.00003445297,0.08771411,0.000024904106,0.0000059100485,0.00004745177,0.00019734027,0.00027197867,0.000079817466,0.9076682,0.0036161612,0.00012025347],"about_ca_topic_score_codex":0.0000014716622,"about_ca_topic_score_gemma":0.00000131137,"teacher_disagreement_score":0.9063054,"about_ca_system_score_codex":0.00001969378,"about_ca_system_score_gemma":0.000016708726,"threshold_uncertainty_score":0.51152074},"labels":[],"label_agreement":null},{"id":"W2066502531","doi":"10.1108/10610421011086892","title":"Consumer perceptions of ambiguous price promotions: scratch and save promotions versus tensile price claims","year":2010,"lang":"en","type":"article","venue":"Journal of Product & Brand Management","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta; University of Northern British Columbia","funders":"","keywords":"Business; Marketing; Originality; Value (mathematics); Advertising; Perception; Economics; Psychology; Computer science","score_opus":0.06286572568324492,"score_gpt":0.3672024036046912,"score_spread":0.30433667792144625,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2066502531","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99148756,0.0001092941,0.0014913894,0.002508169,0.0019296882,0.00055770756,0.000013063776,0.000017280357,0.0018858201],"genre_scores_gemma":[0.9778357,0.00015679156,0.021024594,0.00005378829,0.00017607906,0.000011419637,0.0000013374131,0.000014573271,0.00072571595],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9971035,0.00008601177,0.0012455172,0.0004562445,0.0008568102,0.0002518922],"domain_scores_gemma":[0.99696165,0.00016815987,0.00094968895,0.00071646797,0.0010195115,0.00018450446],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032753667,0.0001906604,0.00045942955,0.0005597651,0.000256086,0.0003015316,0.00059415214,0.000071870876,0.0003583332],"category_scores_gemma":[0.0007438468,0.00013855456,0.00018586902,0.0005616197,0.00025377318,0.0005866013,0.00027800314,0.0004307431,0.00005533912],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005760632,0.002412229,0.007367546,0.0000858739,0.00031595002,0.00008614002,0.0023039416,0.00035178504,0.02612071,0.002806633,0.016991012,0.9405821],"study_design_scores_gemma":[0.012309111,0.0028625077,0.7065817,0.00053521997,0.0015431542,0.0008337943,0.012602051,0.0009125628,0.0045194146,0.18069157,0.0751002,0.0015086822],"about_ca_topic_score_codex":0.000013712539,"about_ca_topic_score_gemma":0.000043193326,"teacher_disagreement_score":0.93907344,"about_ca_system_score_codex":0.00004167159,"about_ca_system_score_gemma":0.00009546149,"threshold_uncertainty_score":0.5650091},"labels":[],"label_agreement":null},{"id":"W2067023889","doi":"10.1016/j.paid.2011.09.002","title":"Failing to commit: Maximizers avoid commitment in a way that contributes to reduced satisfaction","year":2011,"lang":"en","type":"article","venue":"Personality and Individual Differences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":84,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Satisficing; Commit; Cognitive dissonance; Psychology; Social psychology; Preference; Economics; Microeconomics","score_opus":0.3897874075789352,"score_gpt":0.3802634405871916,"score_spread":0.009523966991743626,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2067023889","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99570525,0.00009198246,0.00035996028,0.0018308497,0.00044321414,0.00037886182,0.00016504197,0.000030683997,0.0009941772],"genre_scores_gemma":[0.997402,0.000015955327,0.0014730153,0.00092291593,0.000026904549,0.00004559925,0.000006104567,0.000007774408,0.00009969503],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9972228,0.00029657388,0.000648365,0.00069755263,0.0007459862,0.000388752],"domain_scores_gemma":[0.9981545,0.00093563664,0.00016900661,0.00035674823,0.00010282906,0.00028123474],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026880393,0.00024087966,0.0005471245,0.00044227723,0.00029667869,0.00053989294,0.00061570253,0.00012852887,0.00051683787],"category_scores_gemma":[0.0008343883,0.00018119722,0.00009661934,0.000469697,0.00014119901,0.0003432022,0.00030080028,0.00023201792,0.00014320202],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014159613,0.00010209049,0.715801,0.0000033028607,0.00001918854,0.0000031647435,0.0123837255,0.0000041317057,0.00009662748,0.0005212155,0.0007515306,0.27017242],"study_design_scores_gemma":[0.00040987317,0.00018565445,0.9485689,0.00007044908,0.000019781699,0.000003146273,0.009940037,0.000051838768,0.00039978622,0.039418302,0.0006925722,0.00023970167],"about_ca_topic_score_codex":0.0023446293,"about_ca_topic_score_gemma":0.0036133348,"teacher_disagreement_score":0.26993272,"about_ca_system_score_codex":0.00008349287,"about_ca_system_score_gemma":0.000042519187,"threshold_uncertainty_score":0.73890084},"labels":[],"label_agreement":null},{"id":"W2067563274","doi":"10.1016/j.jmateco.2011.07.006","title":"Cardinal versus ordinal criteria in choice under risk with disconnected utility ranges","year":2011,"lang":"en","type":"article","venue":"Journal of Mathematical Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Irrational number; Mathematical economics; Expected utility hypothesis; Mathematics; Range (aeronautics); Subjective expected utility; Outcome (game theory); Certainty; Expected value; Preference; Function (biology); Econometrics; Statistics","score_opus":0.28101133384067,"score_gpt":0.4006125456551103,"score_spread":0.11960121181444028,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2067563274","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98970854,0.000025891048,0.0031003072,0.0002096809,0.0006197969,0.00012343776,0.000020562964,0.000012094698,0.0061796927],"genre_scores_gemma":[0.98187673,0.000021016484,0.017869977,0.00003731084,0.00013333267,0.0000032861635,4.1371217e-7,0.000019160132,0.00003874286],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9971166,0.00017895,0.0017152864,0.00034901916,0.0003309425,0.0003091939],"domain_scores_gemma":[0.9950343,0.0027766326,0.0011405919,0.00054159627,0.00026170618,0.00024518085],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0038141967,0.00022650033,0.00090106484,0.00035431763,0.00007735048,0.00024491647,0.00083862577,0.00012980387,0.001809531],"category_scores_gemma":[0.0025389055,0.000147394,0.0002718524,0.0002339499,0.00021041486,0.00072535686,0.000120112716,0.00044391846,0.00015250292],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.02272162,0.0065382645,0.12416308,0.00007634786,0.00081936765,0.00061042985,0.0065174405,0.0025381292,0.00009857306,0.018501362,0.0050901226,0.81232524],"study_design_scores_gemma":[0.0065642535,0.0019653873,0.15577637,0.00017497918,0.00025789766,0.00051139103,0.003909972,0.0128361555,0.00020883286,0.81490993,0.0022361458,0.0006487154],"about_ca_topic_score_codex":0.000029566172,"about_ca_topic_score_gemma":0.00018659339,"teacher_disagreement_score":0.81167656,"about_ca_system_score_codex":0.00014721332,"about_ca_system_score_gemma":0.00016547363,"threshold_uncertainty_score":0.99910295},"labels":[],"label_agreement":null},{"id":"W2067959363","doi":"10.5334/pb-48-4-283","title":"The Effects of Instructions on Reasoning with Stereotypical Premises","year":2009,"lang":"en","type":"article","venue":"Psychologica Belgica","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Belgica; Psychology; Association (psychology); Applied psychology; Social psychology; Psychotherapist","score_opus":0.06025698013853421,"score_gpt":0.39362255391381495,"score_spread":0.33336557377528075,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2067959363","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97226465,0.000090776084,0.00023586642,0.0010735674,0.00044918683,0.00018924127,0.0000030268727,0.00004796376,0.025645724],"genre_scores_gemma":[0.99701697,0.000040640676,0.0019589835,0.00035349405,0.000050815175,0.000009973605,4.991668e-7,0.000005569466,0.0005630702],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99807924,0.00014769533,0.00048326288,0.00048579933,0.00056049303,0.00024351536],"domain_scores_gemma":[0.9962621,0.0023236498,0.00030572468,0.00088047405,0.00013189805,0.00009617964],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007505666,0.00015043776,0.00027220513,0.00010185379,0.00037621477,0.00018140186,0.00084543263,0.000095807925,0.000075975404],"category_scores_gemma":[0.001986592,0.00006811519,0.00011145233,0.0005198401,0.0002215798,0.00010228958,0.000042229287,0.00022362996,0.00011349512],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039310896,0.00025411294,0.0033920987,7.1713777e-7,0.000007848381,0.000011620665,0.0000941298,0.000025810163,0.00037165754,0.0045148027,0.0037440665,0.98719],"study_design_scores_gemma":[0.00131381,0.0058350307,0.7255182,0.00018226559,0.00003906847,0.000113929185,0.00037858714,0.000055391432,0.0010742076,0.20124581,0.063860096,0.000383577],"about_ca_topic_score_codex":0.0000014040804,"about_ca_topic_score_gemma":0.000003377236,"teacher_disagreement_score":0.98680645,"about_ca_system_score_codex":0.000019495186,"about_ca_system_score_gemma":0.000018457713,"threshold_uncertainty_score":0.28935778},"labels":[],"label_agreement":null},{"id":"W2068077127","doi":"10.1016/s0010-0285(02)00515-7","title":"An evidential support accumulation model of subjective probability","year":2003,"lang":"en","type":"article","venue":"Cognitive Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":25,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Psychology; Cognitive psychology; Statistics; Social psychology; Mathematics","score_opus":0.46493024468392175,"score_gpt":0.5474355811487335,"score_spread":0.08250533646481173,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2068077127","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89328957,0.000009780641,0.09326876,0.000044088792,0.00048154403,0.00026603206,0.000057873895,0.000022007234,0.012560368],"genre_scores_gemma":[0.9972843,0.000003001617,0.0022562935,0.000285743,0.000027550806,0.000017562556,0.00001006264,0.000011809559,0.00010369604],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99722815,0.00053895096,0.00079728884,0.00079257105,0.00040623435,0.0002368139],"domain_scores_gemma":[0.99701184,0.00086797547,0.0003995932,0.0005783736,0.0010306683,0.00011153082],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003010402,0.00014893126,0.00036965212,0.00027405642,0.00008613185,0.00006287488,0.00040913996,0.00017297472,0.0011497093],"category_scores_gemma":[0.0040259995,0.00012773981,0.00014160709,0.00037994495,0.00030472787,0.00050512573,0.000038593826,0.00015520684,0.000309206],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009675348,0.0018893784,0.19745836,0.0000043823634,0.000038479368,0.000011198754,0.0021573864,0.0019508828,0.007177884,0.0037659202,0.00093787024,0.78364074],"study_design_scores_gemma":[0.0011398636,0.00064984354,0.100625485,0.000011832533,0.000043311433,0.000022035896,0.0005387829,0.004643377,0.0027052173,0.8891361,0.00023057581,0.00025358124],"about_ca_topic_score_codex":0.0000066643875,"about_ca_topic_score_gemma":0.00003678671,"teacher_disagreement_score":0.8853702,"about_ca_system_score_codex":0.000030430934,"about_ca_system_score_gemma":0.00013059557,"threshold_uncertainty_score":0.99976337},"labels":[],"label_agreement":null},{"id":"W2068575306","doi":"10.3758/bf03196883","title":"Dilution and confirmation of probability judgments based on nondiagnostic evidence","year":2004,"lang":"en","type":"article","venue":"Memory & Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":52,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Psychology; Set (abstract data type); Dilution; Contrast (vision); Cognitive psychology; Computer science; Physics; Artificial intelligence","score_opus":0.23704983544421054,"score_gpt":0.4016666025871041,"score_spread":0.16461676714289358,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2068575306","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9917609,0.000024675968,0.0060710614,0.0004572617,0.00021609508,0.00037027072,0.000026301881,0.000025935928,0.0010475132],"genre_scores_gemma":[0.99870026,0.000008671622,0.0009743112,0.00024303407,0.000021041094,0.00002114343,0.000013559881,0.0000053600047,0.000012597784],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9981586,0.00013352312,0.00056152395,0.00038505625,0.0006396411,0.000121676836],"domain_scores_gemma":[0.9975405,0.0014165795,0.00031518532,0.0003304401,0.00032978717,0.0000675565],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018382954,0.000110699315,0.00020024065,0.00021488637,0.00011009997,0.00009887231,0.00015857672,0.000073149604,0.00015673004],"category_scores_gemma":[0.004662856,0.00009228515,0.00006148801,0.0002730233,0.00013200795,0.00047931419,0.000034180885,0.00008815505,0.00020678871],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006429319,0.001156148,0.008835328,0.00006913267,0.000009748124,0.000014202719,0.00056190416,0.016814403,0.011756062,0.0006275442,0.00034553072,0.95916706],"study_design_scores_gemma":[0.0032960845,0.0014783682,0.30324286,0.0017245541,0.00014149847,0.000017515906,0.00045905416,0.00929211,0.050925616,0.6287018,0.00019004135,0.00053049857],"about_ca_topic_score_codex":0.000028018381,"about_ca_topic_score_gemma":0.000024320567,"teacher_disagreement_score":0.9586366,"about_ca_system_score_codex":0.0000834847,"about_ca_system_score_gemma":0.00007880087,"threshold_uncertainty_score":0.5582211},"labels":[],"label_agreement":null},{"id":"W2068737255","doi":"10.1506/l5la-l863-cf9k-wej5","title":"A Note on the Relation between Frames, Perceptions, and Taxpayer Behavior*","year":2005,"lang":"en","type":"article","venue":"Contemporary Accounting Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":49,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Taxpayer; Perception; Function (biology); Cognition; Order (exchange); Social psychology; Psychology; Public economics; Economics","score_opus":0.30446379298876824,"score_gpt":0.47939591042466245,"score_spread":0.1749321174358942,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2068737255","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9765764,0.00019559721,0.00014511457,0.01172768,0.00013755883,0.00048489284,0.000029930958,0.000053702377,0.010649147],"genre_scores_gemma":[0.99654186,0.000016991702,0.0004746242,0.00035909392,0.0005137195,0.000047902027,0.0000107278875,0.000025466788,0.0020096453],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9955074,0.00061752956,0.0008042946,0.0007407489,0.0019030855,0.00042689647],"domain_scores_gemma":[0.99099994,0.007014911,0.00023887036,0.0010326717,0.0005734314,0.00014016934],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.015880981,0.00018114991,0.0002902095,0.0006143434,0.0012119951,0.0014434529,0.0010509549,0.00021518634,0.0006328301],"category_scores_gemma":[0.0057392553,0.00011566797,0.00010837949,0.0008372721,0.00037758282,0.0010589933,0.0004463915,0.0011360903,0.0024347904],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000036598954,0.000074118645,0.30094874,0.0000013801937,0.00000455186,0.000006574621,0.00067475415,0.000010893161,0.0002964909,0.0007578556,0.041402403,0.6557856],"study_design_scores_gemma":[0.00035517427,0.00012770967,0.7246957,0.0000859386,0.000008074517,0.000007661989,0.0015782143,0.0010862539,0.00008719495,0.01913718,0.2525659,0.0002650368],"about_ca_topic_score_codex":0.0000963467,"about_ca_topic_score_gemma":0.00002958758,"teacher_disagreement_score":0.6555206,"about_ca_system_score_codex":0.00011645916,"about_ca_system_score_gemma":0.00019050672,"threshold_uncertainty_score":0.99959314},"labels":[],"label_agreement":null},{"id":"W2068787935","doi":"10.3917/cca.111.0023","title":"Caractéristiques de l'information, surcharge d'information et qualité de la prédiction","year":2005,"lang":"fr","type":"article","venue":"Comptabilité - Contrôle - Audit","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Diction; Humanities; Philosophy; Political science; Linguistics","score_opus":0.03601035421984589,"score_gpt":0.38275648399141754,"score_spread":0.34674612977157165,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2068787935","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8567081,0.0017226933,0.09889893,0.018629806,0.0029030205,0.0008665357,0.0006402687,0.0003265485,0.01930411],"genre_scores_gemma":[0.98735267,0.00048162972,0.0061086337,0.0036908737,0.00051830406,0.000081930055,0.00011816502,0.000027843316,0.001619932],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9936978,0.0015200919,0.0024598662,0.00047113077,0.00095546973,0.00089562434],"domain_scores_gemma":[0.99163175,0.0046545584,0.0011726994,0.0010891281,0.00096306216,0.0004888328],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.012518972,0.00047584195,0.0007367431,0.0004955272,0.00049311225,0.0019507582,0.0010077369,0.0006326983,0.0035897656],"category_scores_gemma":[0.0059432765,0.00047204702,0.00041293734,0.00050560734,0.00050412863,0.008516216,0.00024618657,0.0007373938,0.006883981],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013947063,0.00026195985,0.012074382,0.000047077196,0.000029947916,0.000004007637,0.0071563777,0.0035220967,0.00003409517,0.017983954,0.05332098,0.90542567],"study_design_scores_gemma":[0.0011086904,0.00013873402,0.040114697,0.00013144506,0.0000631987,0.000111799585,0.0013996643,0.033928107,0.00021755786,0.03308758,0.889198,0.00050052657],"about_ca_topic_score_codex":0.0013240748,"about_ca_topic_score_gemma":0.00034485673,"teacher_disagreement_score":0.9049251,"about_ca_system_score_codex":0.0013801419,"about_ca_system_score_gemma":0.0012515932,"threshold_uncertainty_score":0.99977314},"labels":[],"label_agreement":null},{"id":"W2069812862","doi":"10.3389/fpsyg.2015.00537","title":"Communicating numeric quantities in context: implications for decision science and rationality claims","year":2015,"lang":"en","type":"article","venue":"Frontiers in Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University; Defence Research and Development Canada","funders":"","keywords":"Rationality; Psychology; Context (archaeology); Epistemology; Decision theory; Social psychology; Management science; Cognitive science; Cognitive psychology; Data science; Computer science; Mathematics","score_opus":0.27315012421069956,"score_gpt":0.5010961476828564,"score_spread":0.2279460234721568,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2069812862","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.85668737,0.0008925952,0.13463895,0.0037501277,0.001802363,0.0003472448,0.000027182998,0.000017006947,0.0018371883],"genre_scores_gemma":[0.90222824,0.000054375436,0.096810214,0.00080011465,0.000019338246,0.000056499543,0.00000293969,0.000007118941,0.000021186608],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.997805,0.00015142627,0.00082231336,0.0006082845,0.00033039684,0.00028260858],"domain_scores_gemma":[0.9968375,0.001447891,0.00023935153,0.00088364707,0.00047255203,0.0001190879],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0077795945,0.00011042942,0.00034689048,0.0007561708,0.00018670659,0.00018320487,0.0011977296,0.00010510621,0.000008521893],"category_scores_gemma":[0.0062483163,0.00009727036,0.00003798073,0.0011405882,0.0008304218,0.000462771,0.00019551803,0.00016603264,0.000014868168],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007603894,0.000064119886,0.25949305,4.4485543e-7,9.604748e-7,4.0220283e-7,0.00050488557,0.000020280057,0.00002504184,0.0037298542,0.017538583,0.71854633],"study_design_scores_gemma":[0.0007730777,0.000072835865,0.16833302,0.00001535407,0.0000019807608,0.000009181734,0.0025145106,0.0029585117,0.0000037006907,0.79806256,0.027138809,0.00011646057],"about_ca_topic_score_codex":0.00006328441,"about_ca_topic_score_gemma":0.00036198922,"teacher_disagreement_score":0.7943327,"about_ca_system_score_codex":0.00015357767,"about_ca_system_score_gemma":0.0002174535,"threshold_uncertainty_score":0.74802697},"labels":[],"label_agreement":null},{"id":"W2070341805","doi":"10.1037/0096-3445.132.3.419","title":"Judgment dissociation theory: An analysis of differences in causal, counterfactual and covariational reasoning.","year":2003,"lang":"en","type":"article","venue":"Journal of Experimental Psychology General","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":123,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Counterfactual thinking; Categorization; Outcome (game theory); Counterfactual conditional; Psychology; Causal reasoning; Focus (optics); Contrast (vision); Cognitive psychology; Dissociation (chemistry); Social psychology; Econometrics; Cognition; Computer science; Mathematical economics; Economics; Artificial intelligence","score_opus":0.12943558866206265,"score_gpt":0.45714020044750975,"score_spread":0.3277046117854471,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2070341805","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9966393,0.00034752858,0.002076685,0.000067918634,0.00054150866,0.00004385123,0.000012800274,0.0000018969971,0.00026847946],"genre_scores_gemma":[0.9969503,0.000025542005,0.0027529523,0.0001705877,0.00004730701,0.0000015480971,0.0000028185102,0.0000050677695,0.000043831897],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9974901,0.00060797995,0.0010006607,0.00026346752,0.0004963532,0.00014141167],"domain_scores_gemma":[0.9982111,0.00048801498,0.0008731039,0.00019568631,0.00014139924,0.0000907348],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033592044,0.00011712239,0.0005172705,0.000542735,0.0000646154,0.00007969378,0.00026645846,0.00009889594,0.0004811289],"category_scores_gemma":[0.00050648453,0.00008676776,0.00013160572,0.0004123611,0.00012195767,0.00031539114,0.000024770963,0.00014606972,0.0000023114042],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005496091,0.001248521,0.9538208,4.3139326e-7,0.00030794286,0.000017383252,0.0038367393,0.0013191468,0.018254453,0.011947198,0.00037100865,0.008326732],"study_design_scores_gemma":[0.0019004002,0.0012004605,0.95788974,0.0000145030535,0.00016787513,0.000065897715,0.004205653,0.0023106642,0.0032432731,0.028628614,0.00016544982,0.00020747002],"about_ca_topic_score_codex":0.000014708377,"about_ca_topic_score_gemma":0.000029850726,"teacher_disagreement_score":0.016681416,"about_ca_system_score_codex":0.00008558902,"about_ca_system_score_gemma":0.000056479294,"threshold_uncertainty_score":0.5268024},"labels":[],"label_agreement":null},{"id":"W2071292773","doi":"10.1155/2010/838240","title":"The Foundations of Probability with Black Swans","year":2010,"lang":"en","type":"article","venue":"Journal of Probability and Statistics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"U.S. Air Force; Universitetet i Oslo; Division of Mathematical Sciences; University of Toronto","keywords":"Black swan theory; Axiom; Mathematics; Mathematical economics; Arrow; Rare events; Econometrics; Statistics; Computer science","score_opus":0.10649993398141018,"score_gpt":0.38531583773937944,"score_spread":0.2788159037579693,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2071292773","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9125243,0.000013378047,0.08566593,0.00082035677,0.00034665212,0.00016533697,0.000100325975,0.000003162725,0.0003605567],"genre_scores_gemma":[0.7798105,0.00001284813,0.22003336,0.000016303893,0.000041794283,0.0000011812441,6.3560196e-7,0.000004288341,0.0000790778],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.997569,0.0001570816,0.0012276241,0.00019908465,0.000698191,0.00014900956],"domain_scores_gemma":[0.9927862,0.0039371126,0.0009869899,0.0005130892,0.0016486989,0.00012786378],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0061251046,0.00010618038,0.00033033223,0.000069530084,0.00024896147,0.00028970066,0.0004992256,0.000066301305,0.000094298615],"category_scores_gemma":[0.00868095,0.000053119158,0.00007543046,0.00022265657,0.0011819126,0.00024887596,0.00006989256,0.0004031334,0.0000069308726],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047583473,0.00060000585,0.09799144,0.000031999443,0.000044227185,0.000010075328,0.001362007,0.00055380026,0.00028903238,0.27203295,0.0030123855,0.62359625],"study_design_scores_gemma":[0.00026888537,0.00039809858,0.040112246,0.000012775873,0.000035057907,0.00004514047,0.00030089452,0.0008571678,0.000041032166,0.94952273,0.008331189,0.00007476034],"about_ca_topic_score_codex":0.000012874976,"about_ca_topic_score_gemma":0.0010378085,"teacher_disagreement_score":0.6774898,"about_ca_system_score_codex":0.000027355429,"about_ca_system_score_gemma":0.0003582271,"threshold_uncertainty_score":0.9996694},"labels":[],"label_agreement":null},{"id":"W2072427808","doi":"10.2117/psysoc.2004.277","title":"A POWER STRUGGLE: BETWEEN- VS. WITHIN-SUBJECTS DESIGNS IN DEDUCTIVE REASONING RESEARCH","year":2004,"lang":"en","type":"article","venue":"PSYCHOLOGIA","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Expectancy theory; Psychology; Power (physics); External validity; Contrast (vision); Social psychology; Research design; Measure (data warehouse); Cognitive psychology; Statistics; Computer science; Mathematics; Artificial intelligence; Data mining","score_opus":0.3916198528619041,"score_gpt":0.5215943490546544,"score_spread":0.1299744961927503,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2072427808","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9853634,0.000064418906,0.0008555652,0.00081366196,0.0008795508,0.00029189556,0.000012857076,0.000062179155,0.011656448],"genre_scores_gemma":[0.99084234,0.0000050808644,0.008607519,0.00017311309,0.000100799836,0.00002406521,0.0000021156425,0.000024075902,0.00022086606],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99545664,0.00051199674,0.0009270695,0.0011667717,0.0012316123,0.0007059335],"domain_scores_gemma":[0.99640113,0.001635324,0.00025734628,0.0011029498,0.0003946627,0.00020861512],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.010515613,0.00021932824,0.0004583721,0.0009827848,0.00025619048,0.00044646172,0.0014421637,0.00027252786,0.00039313568],"category_scores_gemma":[0.005806227,0.00017127971,0.000110183835,0.0023382895,0.00036759282,0.00044465976,0.00023554737,0.0009445761,0.0019299762],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010588961,0.0013616495,0.58982,0.000004356313,0.000047533813,0.0007085535,0.016860103,0.0024761045,0.0033194753,0.009367562,0.019013999,0.35596177],"study_design_scores_gemma":[0.0014408819,0.0007593607,0.44148642,0.0001263696,0.000005843448,0.000050497798,0.0044994974,0.000018568817,0.001251594,0.5485365,0.0013984408,0.0004260401],"about_ca_topic_score_codex":0.000112374844,"about_ca_topic_score_gemma":0.000095226584,"teacher_disagreement_score":0.53916895,"about_ca_system_score_codex":0.00029366743,"about_ca_system_score_gemma":0.00022371931,"threshold_uncertainty_score":0.9988471},"labels":[],"label_agreement":null},{"id":"W2072665327","doi":"10.1177/1046878104270471","title":"In the long run: Biological versus economic rationality","year":2005,"lang":"en","type":"article","venue":"Simulation & Gaming","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Rationality; Value (mathematics); Economics; Game of chance; Subjective expected utility; Expected utility hypothesis; Psychology; Actuarial science; Microeconomics; Financial economics; Computer science","score_opus":0.3368642494284023,"score_gpt":0.4854850767944849,"score_spread":0.14862082736608256,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2072665327","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9937726,0.000029005156,0.0023087158,0.0014382856,0.00051948056,0.00011571021,0.0000057592424,0.000017540971,0.0017928763],"genre_scores_gemma":[0.99868727,0.0000021589383,0.0005102489,0.0003900036,0.00031078773,0.0000047684302,0.0000063252014,0.0000041282683,0.00008432185],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99838114,0.00018713275,0.0006212684,0.00034339394,0.0003055841,0.00016147787],"domain_scores_gemma":[0.99540526,0.0039612576,0.0001802993,0.00036502906,0.00005377018,0.000034398723],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0028665361,0.00009612511,0.00015714986,0.00013587066,0.00014789439,0.00027068262,0.00046189132,0.00008062844,0.0009212092],"category_scores_gemma":[0.0010621542,0.00006218107,0.00008701659,0.00019093501,0.00005666961,0.0005647427,0.000062138206,0.000120073055,0.0012188202],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007779958,0.000043581316,0.019739565,2.0270664e-7,0.0000021262074,0.0000031699751,0.0004906609,0.67738974,0.000017478937,0.0015799385,0.00035130288,0.3003044],"study_design_scores_gemma":[0.0015006991,0.00008355895,0.26210585,0.000008881191,0.000008197772,0.000005143269,0.0009410709,0.60299027,0.00005899751,0.046498924,0.08548311,0.00031531244],"about_ca_topic_score_codex":0.000015287138,"about_ca_topic_score_gemma":0.00017087629,"teacher_disagreement_score":0.2999891,"about_ca_system_score_codex":0.00013862833,"about_ca_system_score_gemma":0.00004038494,"threshold_uncertainty_score":0.9999921},"labels":[],"label_agreement":null},{"id":"W2073102303","doi":"10.1257/mic.3.4.35","title":"Mnemonomics: The Sunk Cost Fallacy as a Memory Kludge","year":2011,"lang":"en","type":"article","venue":"American Economic Journal Microeconomics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":50,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Sunk costs; Fallacy; Economics; Simple (philosophy); Mental accounting; Econometrics; Microeconomics","score_opus":0.14573624000007926,"score_gpt":0.38155029018719855,"score_spread":0.2358140501871193,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2073102303","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9611889,0.00018880298,0.00057697966,0.001833951,0.0033233666,0.00043225984,0.0000840301,0.000059621467,0.032312084],"genre_scores_gemma":[0.9893057,0.000662005,0.0029485547,0.004510446,0.00084203307,0.0000287393,0.0000044421936,0.00011450174,0.0015836323],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99430394,0.00035423922,0.002876854,0.0011628121,0.00023124546,0.001070887],"domain_scores_gemma":[0.99259454,0.0015246205,0.0030521636,0.0019508157,0.00019737516,0.0006804663],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.005155058,0.0006218293,0.00125599,0.00067514385,0.0008391942,0.0016174886,0.00435907,0.00015389011,0.0042575053],"category_scores_gemma":[0.00053164776,0.00047020544,0.00086236873,0.00025733994,0.0013842895,0.0012620016,0.0006110916,0.0009846864,0.019270672],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031609993,0.00012921005,0.011995997,8.8394006e-7,0.00015005525,0.00004986891,0.002140705,0.0008715456,0.00010646649,0.0011772002,0.0286471,0.95441484],"study_design_scores_gemma":[0.0028138957,0.0010365392,0.018074173,0.000039538467,0.00022450286,0.006397035,0.034423187,0.0029211089,0.0015097213,0.21955897,0.7105587,0.0024426132],"about_ca_topic_score_codex":0.0012288381,"about_ca_topic_score_gemma":0.00070745155,"teacher_disagreement_score":0.95197225,"about_ca_system_score_codex":0.0012292548,"about_ca_system_score_gemma":0.0009622786,"threshold_uncertainty_score":0.999775},"labels":[],"label_agreement":null},{"id":"W2073606051","doi":"10.1037/a0015582","title":"L'impact de l'information saillante et du niveau de gravité du crime sur la décision du jury.","year":2010,"lang":"fr","type":"article","venue":"Canadian Journal of Behavioural Science/Revue canadienne des sciences du comportement","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Psychology; Humanities; Jury; Political science; Philosophy; Law","score_opus":0.09492800671451536,"score_gpt":0.3308381341712982,"score_spread":0.23591012745678286,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2073606051","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9785256,0.00030666278,0.00076431135,0.008466081,0.009108828,0.00037742002,0.00027388945,0.00001988716,0.0021573256],"genre_scores_gemma":[0.9939775,0.00018334569,0.004398583,0.00067073526,0.00048457703,0.000006440228,0.000008770931,0.000027508331,0.00024254355],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9921046,0.00043193632,0.002518414,0.0008759498,0.0013343439,0.0027347452],"domain_scores_gemma":[0.9873328,0.0008036511,0.00200311,0.00076203956,0.0028066759,0.0062916963],"candidate_categories":["metaresearch","metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["sts"],"category_scores_codex":[0.029101156,0.00065848336,0.0009372919,0.0029668324,0.00349123,0.0045490405,0.004979577,0.00033626257,0.0019295187],"category_scores_gemma":[0.004610549,0.00055712025,0.00064957625,0.003160669,0.008068344,0.0073895687,0.000272192,0.0011449761,0.00011657289],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":true,"study_design_scores_codex":[0.000035619403,0.0001665371,0.76464844,0.000011075958,0.000019401758,0.0016385816,0.008116488,0.0026234128,0.00092700124,0.004647821,0.0080578,0.20910779],"study_design_scores_gemma":[0.0011112152,0.0016110874,0.86267006,0.00049247715,0.00017869523,0.017912421,0.004302805,0.01542712,0.00015252401,0.013871506,0.08123387,0.0010362207],"about_ca_topic_score_codex":0.32983583,"about_ca_topic_score_gemma":0.61669964,"teacher_disagreement_score":0.28686383,"about_ca_system_score_codex":0.00549259,"about_ca_system_score_gemma":0.023867194,"threshold_uncertainty_score":0.99974465},"labels":[],"label_agreement":null},{"id":"W2074644642","doi":"10.1037/h0085797","title":"Informal reasoning: Theory and method.","year":2004,"lang":"en","type":"article","venue":"Canadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Psychology; Cognitive psychology; Cognitive science","score_opus":0.10117616676398551,"score_gpt":0.42505001661709146,"score_spread":0.32387384985310597,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2074644642","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9798627,0.0022625702,0.0030162444,0.0012179504,0.0031056406,0.00020195711,0.000046665646,0.000019123556,0.010267161],"genre_scores_gemma":[0.9776548,0.000022660164,0.018202802,0.003616014,0.00024756492,0.000011493868,0.0000044622725,0.00004108642,0.00019911124],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9959983,0.00038177418,0.0014167032,0.0007670966,0.00021519454,0.0012208814],"domain_scores_gemma":[0.9953653,0.0004528219,0.000799381,0.00090702705,0.00016833973,0.0023071],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0060736234,0.00039127446,0.0006887107,0.0011619816,0.0003880573,0.00031869835,0.0016869599,0.00033006512,0.00074339716],"category_scores_gemma":[0.0014018479,0.0003554042,0.00029747112,0.0005590509,0.00065007625,0.0007073651,0.00008771774,0.0006317103,0.00010307944],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0026535017,0.0013317815,0.06858946,0.000016525819,0.00054290454,0.009859012,0.072774336,0.0011530459,0.1758076,0.07399342,0.03725665,0.55602175],"study_design_scores_gemma":[0.01634257,0.0074249255,0.09765828,0.0004880396,0.00019403841,0.050699137,0.10370519,0.00005494543,0.054138552,0.5631711,0.10311816,0.0030050576],"about_ca_topic_score_codex":0.0021916865,"about_ca_topic_score_gemma":0.0104724355,"teacher_disagreement_score":0.5530167,"about_ca_system_score_codex":0.00069747417,"about_ca_system_score_gemma":0.0007048574,"threshold_uncertainty_score":0.9998898},"labels":[],"label_agreement":null},{"id":"W2077003671","doi":"10.1186/1744-9081-3-45","title":"Decision making: rational or hedonic?","year":2007,"lang":"en","type":"article","venue":"Behavioral and Brain Functions","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Pleasure; Psychology; Dimension (graph theory); Social psychology; Hedonism; Reading (process)","score_opus":0.17640941697110402,"score_gpt":0.4404082378967026,"score_spread":0.26399882092559857,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2077003671","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96076816,0.00005791945,0.034468535,0.0009331015,0.0017367254,0.0001869784,0.0000560467,0.000093353236,0.0016991758],"genre_scores_gemma":[0.9841977,0.0000039090305,0.0063398923,0.0006866444,0.00025003124,0.000011672026,0.00001440864,0.00001905848,0.0084767295],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99701446,0.0000581861,0.0009440743,0.00071238814,0.00087327365,0.00039764273],"domain_scores_gemma":[0.9960925,0.0026002778,0.00022106654,0.000554249,0.00029382817,0.00023809375],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0028367762,0.00022657304,0.00030992445,0.00048549706,0.0006617449,0.0005424372,0.00040502555,0.00018267521,0.0030879008],"category_scores_gemma":[0.001179867,0.00015176926,0.00016848065,0.00083067646,0.00018187662,0.0005445841,0.00021532385,0.00023711083,0.0008001474],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002951019,0.00025571923,0.016560348,5.2796486e-7,0.0000032083674,0.00004164019,0.00009684427,0.000027314027,0.00028187007,0.000492618,0.04330987,0.93863493],"study_design_scores_gemma":[0.0014789331,0.0010175438,0.2687271,0.000074148884,0.00008237137,0.0005276162,0.0025597517,0.0005249211,0.00009881119,0.07541185,0.6486873,0.0008096296],"about_ca_topic_score_codex":0.000028336155,"about_ca_topic_score_gemma":0.00089125085,"teacher_disagreement_score":0.9378253,"about_ca_system_score_codex":0.00007601451,"about_ca_system_score_gemma":0.00012172153,"threshold_uncertainty_score":0.9999778},"labels":[],"label_agreement":null},{"id":"W2078174609","doi":"10.1353/ils.2011.0030","title":"Addressing Uncertainty: When Information is Not Enough / Faire face à l'incertitude : quand l'information ne suffit pas","year":2011,"lang":"fr","type":"article","venue":"Canadian Journal of Information and Library Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Indeterminacy (philosophy); Face (sociological concept); Psychology; Epistemology; Sociology; Philosophy; Social science","score_opus":0.1631555707352942,"score_gpt":0.31135461134263126,"score_spread":0.14819904060733707,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078174609","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89839196,0.0012661311,0.012814361,0.034286063,0.008942704,0.0006840339,0.00092549005,0.0000541203,0.04263514],"genre_scores_gemma":[0.981566,0.00025558664,0.0063096997,0.0112704765,0.000115529976,0.0000024328065,0.000031643576,0.000007758013,0.00044087096],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9953427,0.00008498804,0.00250692,0.00017975709,0.001186167,0.00069952547],"domain_scores_gemma":[0.9946847,0.00018090157,0.002139902,0.00042765794,0.0009681179,0.0015987244],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0027319961,0.0003126293,0.00043642498,0.002437031,0.0011446933,0.0061646034,0.0016808733,0.00022570544,0.00264991],"category_scores_gemma":[0.001191247,0.00026559283,0.00015828073,0.0014786886,0.0011723816,0.1311937,0.00016361871,0.0005134829,0.0007742753],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000604622,0.000010129625,0.002274291,0.000028956558,0.000009149876,0.0000065150725,0.05259864,0.0005872912,0.0000020895868,0.0043026693,0.023027526,0.91709226],"study_design_scores_gemma":[0.00087459193,0.00037738748,0.021685652,0.000530133,0.00003663072,0.00037260953,0.01943221,0.016360084,0.0003445826,0.012224551,0.92722464,0.0005369136],"about_ca_topic_score_codex":0.0034103596,"about_ca_topic_score_gemma":0.0006929472,"teacher_disagreement_score":0.91655535,"about_ca_system_score_codex":0.00029143415,"about_ca_system_score_gemma":0.0073129013,"threshold_uncertainty_score":0.9999796},"labels":[],"label_agreement":null},{"id":"W2078191819","doi":"10.3389/fpsyg.2015.00398","title":"Uncertain deduction and conditional reasoning","year":2015,"lang":"en","type":"article","venue":"Frontiers in Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":76,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Psychology; Cognitive psychology; Deductive reasoning; Cognitive science; Artificial intelligence; Computer science","score_opus":0.17498182865155368,"score_gpt":0.45419041215364175,"score_spread":0.2792085835020881,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078191819","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92149836,0.0004942341,0.06371353,0.0015350188,0.005624967,0.00008000195,0.000009708331,0.000022871305,0.0070212916],"genre_scores_gemma":[0.9441083,0.000024467248,0.054664403,0.0007531069,0.0001321025,0.00000978627,0.000009688076,0.000008774015,0.00028937196],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9985729,0.000147192,0.00038679165,0.00045302,0.0002577607,0.00018237629],"domain_scores_gemma":[0.9992581,0.00011789031,0.00012419275,0.0002895564,0.00009198647,0.00011827458],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001870073,0.000087376735,0.00022213915,0.0004028619,0.000049051727,0.00007474072,0.0002681377,0.00012318452,0.00007779166],"category_scores_gemma":[0.0009890244,0.0000756157,0.000031306845,0.0003289718,0.00018944676,0.00021712611,0.00004710825,0.00014839187,0.000105972525],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000077343604,0.00003950185,0.11286485,2.0870912e-7,0.0000031098746,0.000017585464,0.00022208467,0.00008182341,0.000011996482,0.00049986935,0.30717707,0.5790046],"study_design_scores_gemma":[0.0007441469,0.00008395204,0.019677296,0.0000061037586,0.0000035721496,0.00011661997,0.0015194878,0.0013927795,0.000006360887,0.88111275,0.09521997,0.00011698365],"about_ca_topic_score_codex":0.000012411755,"about_ca_topic_score_gemma":0.000012275967,"teacher_disagreement_score":0.88061285,"about_ca_system_score_codex":0.000056772606,"about_ca_system_score_gemma":0.000045760447,"threshold_uncertainty_score":0.3083519},"labels":[],"label_agreement":null},{"id":"W2078362694","doi":"10.1126/science.1246799","title":"Response to Comment on “Poverty Impedes Cognitive Function”","year":2013,"lang":"en","type":"letter","venue":"Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Cognition; Poverty; Task (project management); Ceiling (cloud); Continuous variable; Control (management); Psychology; Function (biology); Ceiling effect; Cognitive psychology; Econometrics; Demographic economics; Social psychology; Developmental psychology; Economics; Computer science; Statistics; Mathematics; Biology; Artificial intelligence; Geography; Medicine; Genetics; Economic growth; Neuroscience","score_opus":0.14222507718703079,"score_gpt":0.4072034179859872,"score_spread":0.26497834079895644,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078362694","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12006091,0.000019550183,0.0007260382,0.8683784,0.0044153305,0.0006039893,0.00018024717,0.00007454286,0.0055409637],"genre_scores_gemma":[0.038763355,0.0000017022235,0.00043411148,0.94771427,0.0005478925,0.000060040333,0.000007830208,0.00002571556,0.012445102],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9924779,0.0003806284,0.00084258383,0.0018584618,0.0036513857,0.00078905444],"domain_scores_gemma":[0.99051964,0.0060978415,0.0004416897,0.0015524436,0.0010601433,0.00032822893],"candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.008121035,0.0003998475,0.00053640094,0.0014670059,0.0007306008,0.0022940498,0.003089244,0.00034147335,0.0028159583],"category_scores_gemma":[0.0107312305,0.0002728952,0.00020974687,0.0015161139,0.00071967643,0.00067246525,0.00076264754,0.0010094398,0.029170599],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019547636,0.000026915892,0.000037370937,5.760765e-7,0.0000029700448,0.000032223877,0.00014197662,0.000008262702,0.00011016942,0.000011325584,0.8678587,0.13157403],"study_design_scores_gemma":[0.00017196903,0.0006199688,0.0015074185,0.00009726447,0.00001609239,0.000009790667,0.00025510212,0.000050270854,0.00017892523,0.02048223,0.9762147,0.00039627933],"about_ca_topic_score_codex":0.00005682984,"about_ca_topic_score_gemma":0.0000058612536,"teacher_disagreement_score":0.13117775,"about_ca_system_score_codex":0.00034145935,"about_ca_system_score_gemma":0.0006083479,"threshold_uncertainty_score":0.99997234},"labels":[],"label_agreement":null},{"id":"W2078615059","doi":"10.1509/jmkr.45.6.665","title":"The Effect of Partitions on Controlling Consumption","year":2008,"lang":"en","type":"article","venue":"Journal of Marketing Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":133,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Consumption (sociology); Context (archaeology); Control (management); Decision process; Resource (disambiguation); Computer science; Habituation; Econometrics; Microeconomics; Economics; Psychology; Artificial intelligence","score_opus":0.35901842010287494,"score_gpt":0.5238326286858027,"score_spread":0.16481420858292778,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078615059","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9969301,0.00025260478,0.00006484347,0.00069238915,0.00034267685,0.0001076527,0.000002688745,0.000003169516,0.0016038434],"genre_scores_gemma":[0.99908435,0.00033560605,0.00008205386,0.000009631311,0.00013797283,0.000002430249,1.0264178e-7,0.000006436067,0.00034138572],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99209595,0.004079977,0.0010742712,0.00015826423,0.0022785014,0.00031303658],"domain_scores_gemma":[0.9054622,0.09232645,0.0006345625,0.00035692897,0.0011130017,0.0001068727],"candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.10979179,0.00007336979,0.00031126055,0.00043452854,0.00072475895,0.00016754867,0.0007326472,0.00005705591,0.00014797389],"category_scores_gemma":[0.07437043,0.000037143403,0.00022316484,0.00038005767,0.00037693928,0.0001409528,0.000085520165,0.0006552445,0.00012462755],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.010471233,0.00012864615,0.22912797,0.00001070565,0.00004838859,0.00012507907,0.00021396228,0.0017216939,0.0016136824,0.00010519086,0.04149861,0.7149348],"study_design_scores_gemma":[0.01047521,0.012194157,0.73943865,0.0020525423,0.00010409094,0.0015641393,0.0021599531,0.008523081,0.011921399,0.05120304,0.15973692,0.0006268319],"about_ca_topic_score_codex":0.0000036217862,"about_ca_topic_score_gemma":0.0000041360872,"teacher_disagreement_score":0.714308,"about_ca_system_score_codex":0.00007576312,"about_ca_system_score_gemma":0.00012265051,"threshold_uncertainty_score":0.93342656},"labels":[],"label_agreement":null},{"id":"W2078890878","doi":"10.3758/bf03196060","title":"A comparative approach to cue competition with one and two strong predictors","year":2005,"lang":"en","type":"article","venue":"Learning & Behavior","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Psychology; Competition (biology); Conditioning; Probabilistic logic; Classical conditioning; Competitor analysis; Social psychology; Cognitive psychology; Statistics; Mathematics; Ecology","score_opus":0.14063985846460078,"score_gpt":0.393702878170241,"score_spread":0.25306301970564027,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078890878","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9886309,0.00002423899,0.0069755577,0.00013103856,0.00008035828,0.00035843597,0.00001262978,0.00009761843,0.0036892227],"genre_scores_gemma":[0.97876716,0.0000013565807,0.020008497,0.00006483793,0.00011108899,0.000064069114,0.000014493526,0.00001984457,0.0009486692],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9976202,0.0001655912,0.00048294733,0.0006880017,0.0007338582,0.0003093783],"domain_scores_gemma":[0.9987233,0.00026938468,0.00022075574,0.00036843828,0.00016775639,0.00025035895],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008868454,0.0002113355,0.00044697267,0.00028272474,0.00030705912,0.00046002358,0.00036244254,0.00006165569,0.00020034409],"category_scores_gemma":[0.000110229295,0.00016476704,0.000058661175,0.00040651674,0.00013922188,0.000409275,0.00014278611,0.00037933956,0.00036845342],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023194106,0.0011271209,0.380776,0.0000025009704,0.000022640075,0.000012387793,0.00707704,0.0399208,0.0026335302,0.001389652,0.0004477771,0.5663586],"study_design_scores_gemma":[0.0028456121,0.001439213,0.9353405,0.00015812668,0.00026908427,0.00013595272,0.008487043,0.012751967,0.00083190226,0.0002316342,0.036350787,0.0011581569],"about_ca_topic_score_codex":0.00005452507,"about_ca_topic_score_gemma":0.00011405687,"teacher_disagreement_score":0.56520045,"about_ca_system_score_codex":0.00008354998,"about_ca_system_score_gemma":0.00003774391,"threshold_uncertainty_score":0.6719005},"labels":[],"label_agreement":null},{"id":"W2081301917","doi":"10.2501/s1470785309201314","title":"How far can you rely on a concept test: the generalizability of testing over occasions","year":2011,"lang":"en","type":"article","venue":"International Journal of Market Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Generalizability theory; Test (biology); Business; Marketing; Computer science; Psychology","score_opus":0.559281526593081,"score_gpt":0.5036483420894333,"score_spread":0.055633184503647626,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2081301917","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9834252,0.000059048118,0.00012138982,0.0044526183,0.00075481896,0.000108520646,0.000071455586,0.0000040383643,0.011002904],"genre_scores_gemma":[0.9961579,0.000024353403,0.0014226607,0.0001307103,0.00023832434,0.000002534045,5.168442e-7,0.000009907524,0.0020130961],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9943852,0.0007762732,0.0009417428,0.00027737496,0.003364023,0.00025542526],"domain_scores_gemma":[0.98168606,0.011801884,0.00074977597,0.00054775266,0.005057895,0.00015666107],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.015008373,0.000113901246,0.0002657061,0.0006019664,0.00015883055,0.00038650996,0.0027199825,0.00007552936,0.0011346947],"category_scores_gemma":[0.050378993,0.00006387057,0.00021938318,0.0005380381,0.00045674166,0.0002451717,0.00039949594,0.0006527717,0.000015418424],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008151036,0.0007806218,0.22885637,0.0000021546332,0.000083720035,0.00024045777,0.0019106006,0.00008939919,0.0022302489,0.0010730543,0.054878548,0.70903975],"study_design_scores_gemma":[0.0020078723,0.002611427,0.7023372,0.00034782206,0.00003267442,0.00062689686,0.006929062,0.003359734,0.004735124,0.2040039,0.07262498,0.00038332478],"about_ca_topic_score_codex":0.00023097495,"about_ca_topic_score_gemma":0.000058911824,"teacher_disagreement_score":0.7086564,"about_ca_system_score_codex":0.0001843073,"about_ca_system_score_gemma":0.0004000783,"threshold_uncertainty_score":0.9997784},"labels":[],"label_agreement":null},{"id":"W2082154704","doi":"10.3758/bf03196067","title":"A signal detection analysis of contingency data","year":2005,"lang":"en","type":"article","venue":"Learning & Behavior","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":78,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Contingency; Psychology; Task (project management); Detection theory; SIGNAL (programming language); Interpretation (philosophy); Contingency table; Cognitive psychology; Social psychology; Computer science; Machine learning; Epistemology","score_opus":0.20233569729112458,"score_gpt":0.4405534837010651,"score_spread":0.23821778640994054,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2082154704","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99393904,0.000068367335,0.005101749,0.000051019095,0.00019260855,0.000099992845,0.000038157923,0.000062250016,0.00044681216],"genre_scores_gemma":[0.99678916,0.0000054696243,0.0020983478,0.000023771567,0.000089824025,0.0000082113975,0.000034589113,0.000014509403,0.00093613425],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99702376,0.00019080113,0.0009914744,0.0007181576,0.00082572957,0.00025007155],"domain_scores_gemma":[0.99720913,0.00059844827,0.0006466773,0.001201636,0.00024205846,0.00010204813],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0028123525,0.00015282659,0.0005175319,0.0008727236,0.00018956151,0.00020995263,0.0012898878,0.00010362299,0.002141182],"category_scores_gemma":[0.0011509999,0.00012992283,0.00025602616,0.0017486244,0.000082895735,0.00054116524,0.0003611771,0.00029863094,0.00035563833],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015685786,0.00011096626,0.13822846,2.523291e-7,0.000032740463,0.00000400472,0.00018114188,0.0030054478,0.009601725,0.000004677615,0.00009110437,0.84872377],"study_design_scores_gemma":[0.00067020673,0.00026552947,0.79734325,0.0000231926,0.0035569046,0.000016639893,0.0010629745,0.11122848,0.004580134,0.0001657139,0.08044661,0.000640378],"about_ca_topic_score_codex":0.00013864363,"about_ca_topic_score_gemma":0.00051841285,"teacher_disagreement_score":0.84808344,"about_ca_system_score_codex":0.000046989284,"about_ca_system_score_gemma":0.000036165715,"threshold_uncertainty_score":0.998771},"labels":[],"label_agreement":null},{"id":"W2082828419","doi":"10.1108/10610420910957843","title":"Consumer perceptions of bundles","year":2009,"lang":"en","type":"article","venue":"Journal of Product & Brand Management","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Bundle; Perception; Test (biology); Marketing; Business; Economics; Advertising; Microeconomics; Psychology","score_opus":0.07452767040881984,"score_gpt":0.39014927446866143,"score_spread":0.3156216040598416,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2082828419","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9875897,0.00040721783,0.0022928207,0.002639299,0.0007594983,0.00013980856,0.0000036967074,0.000006765049,0.0061612036],"genre_scores_gemma":[0.9896225,0.0002503068,0.008317856,0.00018951124,0.00014170202,5.422994e-7,3.31022e-7,0.000004679143,0.001472575],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99771106,0.000057686666,0.0010932283,0.00022371918,0.0007695056,0.00014479876],"domain_scores_gemma":[0.9982192,0.000113068454,0.00071866653,0.00045840172,0.0004074828,0.00008319059],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025939564,0.0001050912,0.00036867723,0.00048417042,0.0000774448,0.00013488006,0.0006118651,0.000025616439,0.00049656426],"category_scores_gemma":[0.0003233273,0.000070022215,0.0002233693,0.00033397574,0.00007052855,0.0003530465,0.00006412064,0.00011782444,0.000094578805],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008467844,0.0002970992,0.0014325234,0.000004020158,0.000030347648,0.000021532958,0.0001997284,0.00026628465,0.00096965255,0.0006937241,0.035492264,0.96050817],"study_design_scores_gemma":[0.0031603996,0.001211033,0.33087426,0.0002628307,0.00044537798,0.00028799873,0.0046534897,0.00008900965,0.001838912,0.25781962,0.39882633,0.00053073897],"about_ca_topic_score_codex":0.0000020646398,"about_ca_topic_score_gemma":0.0000029605662,"teacher_disagreement_score":0.9599774,"about_ca_system_score_codex":0.00003106577,"about_ca_system_score_gemma":0.00003153915,"threshold_uncertainty_score":0.5437031},"labels":[],"label_agreement":null},{"id":"W2084665677","doi":"10.1098/rsbl.2014.0451","title":"Reward context determines risky choice in pigeons and humans","year":2014,"lang":"en","type":"article","venue":"Biology Letters","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":51,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Alberta Gambling Research Institute, University of Calgary; Natural Sciences and Engineering Research Council of Canada","keywords":"Consilience; Biology; Context (archaeology); Key (lock); Cognitive psychology; Ecology; Psychology","score_opus":0.09896210205384492,"score_gpt":0.38890716183964497,"score_spread":0.28994505978580004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2084665677","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9943128,0.00005133786,0.00056474964,0.0041326066,0.0005525817,0.00007274929,0.0000080184145,0.000022532558,0.00028258914],"genre_scores_gemma":[0.99432516,0.000005975191,0.00032195603,0.0051450087,0.000101195175,0.000007230646,0.0000017709515,0.0000069187167,0.000084759704],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984333,0.0002610797,0.0004620056,0.000492728,0.000102493635,0.00024838376],"domain_scores_gemma":[0.99718595,0.0021546346,0.00015145754,0.0004066575,0.00003337475,0.000067910536],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016180017,0.00012700786,0.00031238628,0.0002566051,0.00009139568,0.000090961534,0.00044008557,0.00011295283,0.00006264908],"category_scores_gemma":[0.0018511425,0.00009332538,0.00005959507,0.00014564971,0.00027041408,0.00011524301,0.000121430894,0.00013188184,0.00020217671],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009943481,0.0000132649075,0.53570795,4.467152e-7,0.000002008808,0.000004662199,0.00010671971,0.0000064050137,0.0025649301,0.0001026129,0.003586323,0.45789474],"study_design_scores_gemma":[0.0010367979,0.00016795222,0.64741904,0.00002480613,0.000012866588,0.000024147508,0.00026876768,0.0005091401,0.00017683046,0.018619446,0.33132434,0.00041585547],"about_ca_topic_score_codex":0.0002962357,"about_ca_topic_score_gemma":0.001635663,"teacher_disagreement_score":0.45747888,"about_ca_system_score_codex":0.000020086172,"about_ca_system_score_gemma":0.000009392227,"threshold_uncertainty_score":0.38056988},"labels":[],"label_agreement":null},{"id":"W2084895529","doi":"10.1016/s1532-0464(02)00009-6","title":"Emerging paradigms of cognition in medical decision-making","year":2002,"lang":"en","type":"review","venue":"Journal of Biomedical Informatics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":340,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"U.S. National Library of Medicine","keywords":"R-CAST; Decision engineering; Business decision mapping; Decision support system; Management science; Decision analysis; Computer science; Evidential reasoning approach; Medical decision making; Scope (computer science); Knowledge management; Medical research; Clinical decision support system; Data science; Artificial intelligence; Medicine; Engineering","score_opus":0.15835805001409523,"score_gpt":0.47525694909480876,"score_spread":0.31689889908071356,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2084895529","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0017962207,0.9752366,0.017358493,0.00011699884,0.0032926279,0.00033288315,0.000076881726,0.000013350189,0.0017759592],"genre_scores_gemma":[0.001524891,0.98887205,0.00910654,0.00012024814,0.00032462497,0.0000029724679,0.000008205386,0.000026908301,0.000013555437],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.98148096,0.00026976332,0.012058012,0.0002067606,0.0055572307,0.00042728896],"domain_scores_gemma":[0.98089266,0.00940209,0.008074165,0.0005788569,0.0005323465,0.00051986624],"candidate_categories":["metaresearch","metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.012057923,0.00041963469,0.0036854337,0.0036215717,0.00006852945,0.00021903809,0.0025240148,0.0009676946,0.0019986832],"category_scores_gemma":[0.018547883,0.00025811174,0.0012392191,0.0021854031,0.00039707375,0.00076303544,0.0003890871,0.0015694981,0.00029065475],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013919283,0.00020134424,0.000005329247,0.0005212079,0.000043195258,0.00017125225,0.0003128545,0.000008051022,1.8042096e-8,0.000026796553,0.0054979185,0.9931981],"study_design_scores_gemma":[0.00049186114,0.00021355973,0.0000037844713,0.040696308,0.0002297873,0.0014679796,0.0004684242,0.002444074,1.13404106e-7,0.010110697,0.943604,0.0002694354],"about_ca_topic_score_codex":0.0000012181898,"about_ca_topic_score_gemma":0.0000030530819,"teacher_disagreement_score":0.9929287,"about_ca_system_score_codex":0.00020705332,"about_ca_system_score_gemma":0.00093220954,"threshold_uncertainty_score":0.9999871},"labels":[],"label_agreement":null},{"id":"W2085536117","doi":"10.1371/journal.pone.0033460","title":"Sensitivity and Bias in Decision-Making under Risk: Evaluating the Perception of Reward, Its Probability and Value","year":2012,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Canadian Institutes of Health Research","keywords":"Prospect theory; Subjective expected utility; Psychology; Discriminative model; Frequentist probability; Econometrics; Perception; Sensitivity (control systems); Expected utility hypothesis; Statistics; Cognitive psychology; Mathematics; Computer science; Economics; Artificial intelligence; Bayesian probability; Neuroscience","score_opus":0.38761188622295256,"score_gpt":0.42519829052051145,"score_spread":0.037586404297558884,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2085536117","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99856436,0.00019860295,0.00046791713,0.00017142168,0.000078840996,0.0003624485,0.000015935808,0.000014116522,0.00012635512],"genre_scores_gemma":[0.98610866,0.00003817114,0.013720649,0.000045579756,0.00005614717,0.0000072439198,4.4081352e-7,0.000009867372,0.000013219405],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99659395,0.0010052895,0.0007291385,0.0004405761,0.00097352004,0.000257527],"domain_scores_gemma":[0.989601,0.009106115,0.0004130679,0.0005308958,0.0002632377,0.00008564955],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.019721543,0.00014070618,0.00039962295,0.00017154886,0.00019871515,0.00013999233,0.00017719397,0.00010492282,0.000068943424],"category_scores_gemma":[0.017709171,0.000090730704,0.00005626222,0.00037028675,0.00016761827,0.0005065386,0.00029665005,0.00024832386,0.000035433884],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000094387564,0.000501088,0.5889027,0.000009725192,0.000012237662,7.8555337e-7,0.0016944822,0.00038969298,0.0038637647,0.00013175207,0.0000097999,0.40438956],"study_design_scores_gemma":[0.00025264308,0.00011016613,0.8943592,0.0002549519,0.000067724686,0.000009817782,0.0013052494,0.025231637,0.00022417073,0.07804087,0.000003396451,0.00014022252],"about_ca_topic_score_codex":0.00008076318,"about_ca_topic_score_gemma":0.0001536517,"teacher_disagreement_score":0.40424934,"about_ca_system_score_codex":0.000072972005,"about_ca_system_score_gemma":0.00004125609,"threshold_uncertainty_score":0.99056506},"labels":[],"label_agreement":null},{"id":"W2085887099","doi":"10.1037/a0028857","title":"Cognitive sophistication does not attenuate the bias blind spot.","year":2012,"lang":"en","type":"article","venue":"Journal of Personality and Social Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":356,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Canada Research Chairs","keywords":"Psychology; Cognitive bias; Blind spot; Sophistication; Cognition; Response bias; Heuristics; Confirmation bias; Cognitive psychology; Social cognition; Social psychology","score_opus":0.44430542555546176,"score_gpt":0.5126332451784136,"score_spread":0.06832781962295181,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2085887099","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9767428,0.00012658228,0.00053871213,0.020204408,0.001358274,0.00005219043,0.000032342883,0.000003079728,0.00094158633],"genre_scores_gemma":[0.99535847,0.00003578203,0.00011770048,0.003100027,0.0012025938,0.000001030998,8.937707e-7,0.00000501723,0.00017849321],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9980312,0.0004592821,0.0006656483,0.00016422234,0.00047781493,0.00020185082],"domain_scores_gemma":[0.9969747,0.001642254,0.00075828924,0.00011538385,0.00041441008,0.00009493286],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0068035913,0.000096366464,0.00030393864,0.0001130166,0.00035755144,0.00012741637,0.00032040192,0.00013668979,0.00031828106],"category_scores_gemma":[0.0014250235,0.000049673425,0.00018191444,0.00014707819,0.0004533568,0.00030418538,0.000043432767,0.00032972032,0.00008761424],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016175536,0.00057243835,0.08580781,0.0000041860744,0.000106024345,0.000014096775,0.024210537,7.604577e-7,0.00063151773,0.0051523247,0.0096755065,0.8722072],"study_design_scores_gemma":[0.0013550189,0.0001573933,0.85919446,0.000012670067,0.00012465242,0.00019913325,0.0095347315,0.000012459755,0.0000425989,0.102335714,0.026862519,0.00016864951],"about_ca_topic_score_codex":0.000010024349,"about_ca_topic_score_gemma":0.000014386743,"teacher_disagreement_score":0.8720386,"about_ca_system_score_codex":0.00002413427,"about_ca_system_score_gemma":0.000040997227,"threshold_uncertainty_score":0.34849545},"labels":[],"label_agreement":null},{"id":"W2086279032","doi":"10.1016/j.jcps.2010.08.005","title":"The role of computational ease on the decision to spend loyalty program points","year":2010,"lang":"en","type":"article","venue":"Journal of Consumer Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":51,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Loyalty program; Loyalty; Point (geometry); Cash; Marketing; Function (biology); Point of sale; Currency; Advertising; Computer science; Microeconomics; Business; Loyalty business model; Economics; Finance; Mathematics; Monetary economics; World Wide Web","score_opus":0.10265426817800227,"score_gpt":0.473280398755049,"score_spread":0.37062613057704674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2086279032","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.988889,0.00009214947,0.0005688394,0.0060069654,0.0022644384,0.00018951733,0.000009312323,0.0000052102923,0.0019745852],"genre_scores_gemma":[0.99101865,0.000012494474,0.0077271094,0.0010786887,0.00010334554,0.0000034754169,2.5328097e-7,0.000009120127,0.00004685538],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9971873,0.00023020267,0.0012458024,0.0002385885,0.0008899202,0.0002081757],"domain_scores_gemma":[0.9907126,0.006721218,0.00094849226,0.0006503565,0.0007921628,0.0001751892],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0053179087,0.0001246185,0.00031841348,0.0002705757,0.00019574647,0.00018736301,0.0014382093,0.00010148236,0.0005648106],"category_scores_gemma":[0.0042056036,0.000057441062,0.00022411734,0.00033971024,0.00031830842,0.00010271962,0.00009336729,0.00054749084,0.00058803987],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047322686,0.0002560983,0.007639124,1.2552252e-7,0.000016929527,0.00000986137,0.000076322256,0.000081115206,0.00025969054,0.0015492894,0.021222265,0.968416],"study_design_scores_gemma":[0.00053983927,0.0005541055,0.06769707,0.00001821016,0.0000157311,0.00025767583,0.0001666378,0.00019793611,0.00015961428,0.5430445,0.3872624,0.00008624199],"about_ca_topic_score_codex":0.0000030014694,"about_ca_topic_score_gemma":0.000040103303,"teacher_disagreement_score":0.9683297,"about_ca_system_score_codex":0.00001278727,"about_ca_system_score_gemma":0.00011623814,"threshold_uncertainty_score":0.75582594},"labels":[],"label_agreement":null},{"id":"W2086594387","doi":"10.1016/j.cognition.2007.06.002","title":"Conflict monitoring in dual process theories of thinking","year":2007,"lang":"en","type":"article","venue":"Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":431,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Psychology; Dual process theory (moral psychology); Heuristic; Cognitive psychology; Think aloud protocol; Epistemology; Thinking processes; Confirmation bias; Inference; Heuristics; Social psychology; Cognitive science; Moral reasoning; Computer science","score_opus":0.1551283694678041,"score_gpt":0.44587910394094915,"score_spread":0.29075073447314503,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2086594387","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.987898,0.000052916996,0.0017422215,0.000027224936,0.00040557046,0.00008286681,0.0000054240904,0.000021562431,0.009764237],"genre_scores_gemma":[0.99950016,0.0000054263883,0.0003395113,0.000022898457,0.00008035886,0.0000028206584,0.000002325166,0.000006093406,0.00004041969],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9984825,0.00003564543,0.0005828474,0.00022810801,0.00051322987,0.00015762917],"domain_scores_gemma":[0.9983346,0.0009339208,0.00022748276,0.00016831886,0.0002977602,0.0000379329],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034449399,0.00007688474,0.00017883908,0.00030495255,0.00006843412,0.00009976952,0.00017641047,0.00007272285,0.000072218536],"category_scores_gemma":[0.0013602366,0.00006288233,0.00004699469,0.0004390463,0.00007674898,0.00034326618,0.00004487061,0.00010718308,0.000064042404],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018507826,0.00015039071,0.0893654,0.000008964673,0.0000050970557,0.000051277282,0.005846036,0.000082489685,0.0038507343,0.0023428497,0.000029805542,0.8980819],"study_design_scores_gemma":[0.00044291018,0.00006679432,0.065253444,0.0001600003,0.000010484001,0.000013097337,0.006525047,0.00006785006,0.074742444,0.8521692,0.00039755742,0.00015116412],"about_ca_topic_score_codex":0.0000060228467,"about_ca_topic_score_gemma":0.000020627482,"teacher_disagreement_score":0.8979307,"about_ca_system_score_codex":0.000021918348,"about_ca_system_score_gemma":0.000030344943,"threshold_uncertainty_score":0.2564267},"labels":[],"label_agreement":null},{"id":"W2086656617","doi":"10.3758/s13423-011-0141-6","title":"Evidence affects hypothesis judgments more if accumulated gradually than if presented instantaneously","year":2011,"lang":"en","type":"article","venue":"Psychonomic Bulletin & Review","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"BC Research (Canada); BC Mental Health & Substance Use Services; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Michael Smith Health Research BC","keywords":"Psychology; Task (project management); Empirical evidence; Statistical evidence; Social psychology; Cognitive psychology; Statistics; Null hypothesis; Mathematics; Economics","score_opus":0.3740210754793285,"score_gpt":0.414861016562455,"score_spread":0.040839941083126496,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2086656617","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9295053,0.042618543,0.00022785422,0.00867236,0.0025584195,0.0025374277,0.000057335383,0.00030223158,0.013520537],"genre_scores_gemma":[0.92499566,0.061442543,0.005298089,0.0048032687,0.00015473245,0.00015367055,0.000007779709,0.0001128304,0.0030314187],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9940858,0.00063815294,0.0019426681,0.0016316969,0.0009839529,0.0007177464],"domain_scores_gemma":[0.9933208,0.0022803105,0.0011994521,0.002492796,0.00028127895,0.00042535906],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0040370584,0.0005998715,0.0013329678,0.0003233359,0.00024041826,0.00033411672,0.0029272127,0.00020588645,0.007873491],"category_scores_gemma":[0.0037754732,0.00046312064,0.00062394893,0.0007825973,0.0002199461,0.00032837607,0.00040510445,0.00040090032,0.01398441],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022554646,0.0003580584,0.0031401885,0.00015805528,0.00006675056,0.000108400294,0.00032340607,0.000011022502,0.00007901394,0.000049403105,0.21000738,0.78547275],"study_design_scores_gemma":[0.0012454285,0.00052784395,0.024590848,0.015626319,0.0004225026,0.0003943212,0.00029234504,0.00018467949,0.00019216827,0.00955617,0.9452369,0.0017304323],"about_ca_topic_score_codex":0.00013623972,"about_ca_topic_score_gemma":0.000019689194,"teacher_disagreement_score":0.7837423,"about_ca_system_score_codex":0.000154684,"about_ca_system_score_gemma":0.00013679173,"threshold_uncertainty_score":0.999782},"labels":[],"label_agreement":null},{"id":"W2086662877","doi":"10.1007/s11126-009-9094-6","title":"Does Intuition have a Role in Psychiatric Diagnosis?","year":2009,"lang":"en","type":"review","venue":"Psychiatric Quarterly","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":28,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Public health; Intuition; Psychiatry; Psychology; Medicine; Cognitive science; Nursing","score_opus":0.0742701567862718,"score_gpt":0.41360220549102233,"score_spread":0.33933204870475053,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2086662877","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0016405195,0.9877817,0.00018720646,0.00040710066,0.0057930453,0.0013555335,0.00015226555,0.00012995423,0.0025526816],"genre_scores_gemma":[0.0012544312,0.9947317,0.0015015982,0.00020247186,0.0013706633,0.0003888632,0.000058338042,0.000096180105,0.00039572883],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.990162,0.00082701066,0.0043931203,0.0022411095,0.0014812744,0.0008954637],"domain_scores_gemma":[0.9932463,0.0017808405,0.002237281,0.0022064766,0.00018519994,0.00034385562],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0032615343,0.0010317401,0.003389012,0.0043450724,0.00023367825,0.0011433612,0.0027505616,0.0009618923,0.0006364057],"category_scores_gemma":[0.0003280468,0.00059496524,0.001810713,0.0038164202,0.00008184275,0.0006339019,0.00007612562,0.0012045319,0.0041552475],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012791895,0.0004963902,0.00067718554,0.00017322268,0.000014529306,0.000018272816,0.0002471299,0.0000014271634,7.1142305e-9,0.00011640698,0.009202723,0.9890399],"study_design_scores_gemma":[0.00035772243,0.0005708279,0.00020521904,0.0008444176,0.00027645018,0.000031817166,0.00024683558,0.000026846252,1.2517242e-8,0.21023878,0.7864552,0.00074587826],"about_ca_topic_score_codex":0.00013042956,"about_ca_topic_score_gemma":0.0007248761,"teacher_disagreement_score":0.988294,"about_ca_system_score_codex":0.0003293178,"about_ca_system_score_gemma":0.00046328444,"threshold_uncertainty_score":0.99989355},"labels":[],"label_agreement":null},{"id":"W2087967090","doi":"10.1080/13546780902930917","title":"Inhibiting beliefs demands attention","year":2009,"lang":"en","type":"article","venue":"Thinking & Reasoning","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Psychology; Cognitive psychology; Analytic reasoning; Variety (cybernetics); Motivated reasoning; Task (project management); Social psychology; Content (measure theory); Deductive reasoning; Computer science; Artificial intelligence","score_opus":0.06805243705929927,"score_gpt":0.3762724253259446,"score_spread":0.3082199882666454,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2087967090","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.975345,0.00013771938,0.006515986,0.00065904704,0.0004940089,0.0000920764,0.0000020769178,0.00022247259,0.016531615],"genre_scores_gemma":[0.9842001,0.0000065028166,0.014009322,0.0006322872,0.00029497544,0.0000021101955,0.0000058988085,0.000016995442,0.0008318055],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9970061,0.00011856988,0.0008476397,0.0006570352,0.00093093107,0.00043971813],"domain_scores_gemma":[0.99803174,0.0005877714,0.00047278893,0.00056998176,0.00020250378,0.00013521113],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0048956727,0.00021140162,0.00036814838,0.00032808396,0.00068409584,0.0010415304,0.00078102906,0.00014119006,0.00016072625],"category_scores_gemma":[0.0022173522,0.00017440846,0.0002125093,0.0005684823,0.000047357542,0.0006851321,0.00015109449,0.00032937992,0.0006415459],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016018717,0.000048824808,0.016000815,8.341685e-7,0.0000045764996,0.000033574757,0.0009530655,0.0003250381,0.0013281566,0.0072684046,0.0008052757,0.9732154],"study_design_scores_gemma":[0.0007465589,0.00024553025,0.12482087,0.0006839423,0.000041043793,0.00015813098,0.0011569049,0.007495064,0.00081530295,0.8578818,0.005271199,0.0006836813],"about_ca_topic_score_codex":0.000029203324,"about_ca_topic_score_gemma":0.000011499639,"teacher_disagreement_score":0.97253174,"about_ca_system_score_codex":0.00009280839,"about_ca_system_score_gemma":0.000040010425,"threshold_uncertainty_score":0.99999547},"labels":[],"label_agreement":null},{"id":"W2090185959","doi":"10.1007/s00199-007-0259-y","title":"Utility of gambling II: risk, paradoxes, and data","year":2007,"lang":"en","type":"article","venue":"Economic Theory","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":42,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Event (particle physics); Mathematical economics; Expected utility hypothesis; Entropy (arrow of time); Mathematics; Representation (politics); Term (time); Computer science; Econometrics","score_opus":0.26794935313812746,"score_gpt":0.45613052440708524,"score_spread":0.18818117126895778,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2090185959","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9878147,0.00037065297,0.0034664387,0.000052763353,0.0006540963,0.00008661514,0.0002446161,0.000022145532,0.007287922],"genre_scores_gemma":[0.99784136,0.000058025886,0.001565303,0.00004476593,0.00009421215,4.2389843e-7,0.000007260478,0.000010444031,0.00037817957],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9977371,0.0001585144,0.001004374,0.0007108363,0.00015238568,0.00023677756],"domain_scores_gemma":[0.99379796,0.0036353772,0.0005508359,0.0018528593,0.000038186172,0.00012480629],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.02049767,0.00013272437,0.00037982644,0.00020766686,0.00018612825,0.000102719874,0.0013201457,0.000092934555,0.0011922886],"category_scores_gemma":[0.0019178132,0.000109578854,0.00007215808,0.000089101915,0.000271404,0.00046827734,0.0009296107,0.00016364237,0.00025698123],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013396965,0.000038384256,0.036399063,0.00000102739,0.000010749183,0.0000022456347,0.00023682133,0.000022948574,0.000022156537,0.005259999,0.0019167771,0.95595586],"study_design_scores_gemma":[0.00044026345,0.00005656482,0.07523549,0.000012699706,0.00002851731,0.000016533379,0.0012857375,0.004063913,0.00047529428,0.87634176,0.041814677,0.00022855587],"about_ca_topic_score_codex":0.000089014145,"about_ca_topic_score_gemma":0.0002316834,"teacher_disagreement_score":0.9557273,"about_ca_system_score_codex":0.00002076491,"about_ca_system_score_gemma":0.00006992608,"threshold_uncertainty_score":0.99972075},"labels":[],"label_agreement":null},{"id":"W2090200932","doi":"10.3758/bf03195272","title":"Generating alternatives: A key component in human reasoning?","year":2002,"lang":"en","type":"article","venue":"Memory & Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":48,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Syllogism; Psychology; Key (lock); Measure (data warehouse); Mental model; Component (thermodynamics); Cognitive psychology; Style (visual arts); Deductive reasoning; Cognition; Cognitive science; Artificial intelligence; Epistemology; Computer science","score_opus":0.1750069597705744,"score_gpt":0.39005024033152236,"score_spread":0.21504328056094796,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2090200932","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9761958,0.00006630548,0.00053972757,0.00015246174,0.00029197888,0.00014839563,0.000012060762,0.000046499776,0.022546781],"genre_scores_gemma":[0.99733275,0.000008230292,0.0013844765,0.0003306892,0.00014178475,0.000018352255,0.000012934116,0.000013591364,0.0007571873],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977478,0.00020709641,0.00070633565,0.00050973124,0.00059430994,0.00023473335],"domain_scores_gemma":[0.99880755,0.00034640875,0.00026934038,0.0003362042,0.0001572703,0.00008322956],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0014557588,0.00014622603,0.0002617527,0.0003648181,0.00022640353,0.0003265088,0.00035551834,0.00006802701,0.0019193575],"category_scores_gemma":[0.0007163039,0.00012918256,0.00009400404,0.00034027448,0.00006842442,0.00038823544,0.000092044545,0.00018902226,0.0010511313],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024410096,0.0005125791,0.0041293683,0.0000033492506,0.000009664492,0.0001484263,0.0028691199,0.0018453735,0.026552938,0.0002341047,0.003973741,0.95969695],"study_design_scores_gemma":[0.0112150805,0.0012531294,0.082751304,0.0015033442,0.00015997837,0.0003626757,0.0147627555,0.57709837,0.03365872,0.2455624,0.02807057,0.0036016346],"about_ca_topic_score_codex":0.000054508015,"about_ca_topic_score_gemma":0.00012045766,"teacher_disagreement_score":0.9560953,"about_ca_system_score_codex":0.00007832745,"about_ca_system_score_gemma":0.0000091069505,"threshold_uncertainty_score":0.99972665},"labels":[],"label_agreement":null},{"id":"W2090789917","doi":"10.1037/0022-3514.94.4.672","title":"On the relative independence of thinking biases and cognitive ability.","year":2008,"lang":"en","type":"article","venue":"Journal of Personality and Social Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":842,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada; Canada Research Chairs","keywords":"Psychology; Debiasing; Cognitive bias; Heuristics; Neglect; Confirmation bias; Framing effect; Cognitive psychology; Cognition; Social psychology; Axiom independence; Anchoring; Axiom; Persuasion","score_opus":0.32368536056585634,"score_gpt":0.4712949365361573,"score_spread":0.14760957597030094,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2090789917","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9932619,0.00015012782,0.00030663813,0.004804984,0.00020579515,0.00004796261,0.000017159791,0.0000017840724,0.0012036598],"genre_scores_gemma":[0.99851424,0.00004916713,0.00011577911,0.001204315,0.00008316369,4.1876203e-7,1.5941674e-7,0.0000028573093,0.000029914789],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9980643,0.0004906062,0.00058148196,0.00019428147,0.0005658609,0.00010348951],"domain_scores_gemma":[0.99266386,0.0060971854,0.00069262047,0.00008889253,0.0004118673,0.000045571804],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0042983047,0.00008313053,0.0003431351,0.00010767999,0.00037730776,0.0000375677,0.0002470186,0.000136966,0.00015331805],"category_scores_gemma":[0.0038402618,0.0000490703,0.00013526712,0.00014799299,0.0009949558,0.00021232896,0.000048642676,0.0004278612,0.0000047089848],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0034470353,0.0012787954,0.34685618,0.000012072217,0.00031674426,0.00021282582,0.17125314,0.0000083333025,0.00056695624,0.063805304,0.0074950727,0.40474755],"study_design_scores_gemma":[0.00047607336,0.00038054914,0.4841104,0.000034009936,0.00002587516,0.00022059002,0.0052019465,0.0000071361173,0.000013979995,0.50924313,0.00022115605,0.0000651889],"about_ca_topic_score_codex":0.00001766082,"about_ca_topic_score_gemma":0.000014605384,"teacher_disagreement_score":0.44543782,"about_ca_system_score_codex":0.0000132034675,"about_ca_system_score_gemma":0.0000624417,"threshold_uncertainty_score":0.45974296},"labels":[],"label_agreement":null},{"id":"W2091145675","doi":"10.1037/cep0000020","title":"Strategy selection in cue-based decision making.","year":2014,"lang":"en","type":"article","venue":"Canadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Psychology; Heuristics; Cognitive psychology; Salience (neuroscience); Cognition; Task (project management); Associative property; Heuristic; Set (abstract data type); Process tracing; Social psychology; Artificial intelligence; Computer science","score_opus":0.11201421002809482,"score_gpt":0.415463361557653,"score_spread":0.3034491515295582,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2091145675","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98601586,0.00064000057,0.0030461245,0.00064429874,0.0032160683,0.00024643255,0.000027658063,0.000020217672,0.0061433148],"genre_scores_gemma":[0.99043244,0.0000046437535,0.0064260834,0.0026842058,0.00029589978,0.000018078923,0.000004344588,0.00005220828,0.00008212042],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9949021,0.0004852288,0.0019060508,0.001019379,0.00030047807,0.001386764],"domain_scores_gemma":[0.99590373,0.0007086318,0.0009149608,0.0008142951,0.00026348158,0.0013949166],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0050147884,0.00043351474,0.0007923786,0.0023182407,0.00026856805,0.00032313433,0.0020612017,0.000420198,0.0017290828],"category_scores_gemma":[0.0013293248,0.00041873203,0.00036012422,0.0011949633,0.00038579974,0.00049030065,0.000042856896,0.0007386135,0.00021235517],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012188137,0.0010956726,0.2087628,0.000006509075,0.00006145027,0.0015294228,0.0030176817,0.0068655023,0.0399041,0.0010600416,0.0637465,0.6727315],"study_design_scores_gemma":[0.020112477,0.012877363,0.55516994,0.0012726984,0.000111309244,0.009388203,0.019682603,0.008600691,0.016746059,0.24184044,0.11027423,0.003923977],"about_ca_topic_score_codex":0.0022535003,"about_ca_topic_score_gemma":0.08960333,"teacher_disagreement_score":0.66880757,"about_ca_system_score_codex":0.0018511342,"about_ca_system_score_gemma":0.00071789976,"threshold_uncertainty_score":0.99982643},"labels":[],"label_agreement":null},{"id":"W2092744451","doi":"10.1167/14.10.335","title":"Attention improves precision while short-term memory load increases guessing","year":2014,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Cognitive psychology; Psychology; Orientation (vector space); Task (project management); Working memory; Luminance; Computer science; Artificial intelligence; Cognition; Neuroscience; Mathematics","score_opus":0.07448650184939973,"score_gpt":0.3909923257426867,"score_spread":0.31650582389328696,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2092744451","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99030083,0.0002618875,0.0053239935,0.0002274507,0.0018299699,0.000094611874,0.000003716862,0.00002128864,0.0019362227],"genre_scores_gemma":[0.9955219,0.000051804687,0.003384249,0.00009420881,0.0006031712,8.2117424e-7,0.000001757682,0.000021482701,0.00032058026],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9949304,0.00036631114,0.0018911121,0.00043106926,0.0021061786,0.00027495503],"domain_scores_gemma":[0.9950711,0.0015320451,0.001283063,0.00065996766,0.0011832875,0.00027049799],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008793497,0.00022384261,0.0006182896,0.0005700737,0.00026842664,0.0008469772,0.0009817895,0.00017148149,0.00023739257],"category_scores_gemma":[0.003863349,0.00014748519,0.0004515556,0.0003793246,0.0000926556,0.0016690108,0.0002642114,0.00034232342,0.00023225001],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001737776,0.0002235728,0.004343027,0.000002935705,0.000007202891,0.000017202823,0.00007905289,0.00008434079,0.059706952,0.0000132387395,0.00497367,0.93037504],"study_design_scores_gemma":[0.003764853,0.0049085114,0.82743025,0.0023098316,0.00028687637,0.0011777743,0.0015108885,0.017771356,0.008320643,0.07337363,0.05783773,0.0013076329],"about_ca_topic_score_codex":0.0000125842025,"about_ca_topic_score_gemma":0.000014039864,"teacher_disagreement_score":0.9290674,"about_ca_system_score_codex":0.00017639787,"about_ca_system_score_gemma":0.00014349534,"threshold_uncertainty_score":0.816742},"labels":[],"label_agreement":null},{"id":"W2092932206","doi":"10.1037/a0018039","title":"Spontaneous trait inferences and organisational actions: The formation of organisation personality perceptions.","year":2010,"lang":"en","type":"article","venue":"Canadian Journal of Behavioural Science/Revue canadienne des sciences du comportement","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Psychology; Trait; Personality; Social psychology; Perception; Impression formation; Big Five personality traits; Social perception","score_opus":0.22290343623434514,"score_gpt":0.33579183511071176,"score_spread":0.11288839887636662,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2092932206","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9960988,0.000026761,0.0002904065,0.0017165686,0.0012798583,0.00017235824,0.00006207466,0.00000483209,0.0003483154],"genre_scores_gemma":[0.99782294,0.000005759393,0.0019481444,0.00008238572,0.00010172447,0.0000029047133,0.00000274594,0.00000534942,0.000028044067],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9969828,0.0001002661,0.0012299336,0.00037354266,0.000804996,0.00050841906],"domain_scores_gemma":[0.99596786,0.00035222812,0.0010539232,0.00030876958,0.0014202793,0.0008969585],"candidate_categories":["sts","insufficient_payload"],"consensus_categories":["sts"],"category_scores_codex":[0.0089305295,0.00017521628,0.00030930477,0.0009634442,0.0024848434,0.00087764487,0.0016669808,0.000069955015,0.0018997017],"category_scores_gemma":[0.0012280026,0.00011759508,0.00011927334,0.0014222976,0.0058322535,0.0018890327,0.0000519002,0.00031448656,0.000010363777],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019541541,0.00011115447,0.7204505,0.00000916191,0.000012419994,0.00018656699,0.03877927,0.0005546924,0.012693279,0.013004809,0.00039319537,0.21378541],"study_design_scores_gemma":[0.00026400722,0.00049615855,0.9148722,0.000043925458,0.000056428846,0.007442265,0.030440563,0.0024755578,0.00027139575,0.042076096,0.0012951868,0.00026616355],"about_ca_topic_score_codex":0.025889924,"about_ca_topic_score_gemma":0.519587,"teacher_disagreement_score":0.49369705,"about_ca_system_score_codex":0.000651086,"about_ca_system_score_gemma":0.0030888687,"threshold_uncertainty_score":0.9990127},"labels":[],"label_agreement":null},{"id":"W2092942349","doi":"10.1016/j.jcps.2013.04.008","title":"Dual process theory and the context of choice: Comments on Dhar and Gorlin","year":2013,"lang":"en","type":"article","venue":"Journal of Consumer Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"John Templeton Foundation","keywords":"Heuristics; Normative; Psychology; Dual (grammatical number); Variety (cybernetics); Differential (mechanical device); Context (archaeology); Process (computing); Differential effects; Cognitive psychology; Dual process theory (moral psychology); Social psychology; Epistemology; Positive economics; Cognitive science; Computer science; Artificial intelligence; Economics; Moral reasoning; Philosophy; Linguistics","score_opus":0.09028027782625299,"score_gpt":0.4553739622883071,"score_spread":0.36509368446205415,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2092942349","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99264437,0.00087534403,0.000063690204,0.0046916986,0.0005965812,0.00013260153,0.0000053158633,0.0000021521175,0.0009882456],"genre_scores_gemma":[0.9963977,0.00017676945,0.00007945204,0.0031866236,0.000046622932,0.0000028654256,1.2168915e-7,0.0000063550556,0.00010352178],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9979022,0.0005028349,0.0009354666,0.00018809953,0.0003367505,0.00013461564],"domain_scores_gemma":[0.99325484,0.0050173686,0.00094079453,0.00028768528,0.00040225658,0.00009704382],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0042746575,0.000109820954,0.00047526817,0.00020559767,0.00007690061,0.000105092164,0.00040527072,0.000088210145,0.000425551],"category_scores_gemma":[0.0018207558,0.00005573827,0.00008250344,0.0001147626,0.00075993314,0.00020626972,0.000053963155,0.00027779565,0.000069734124],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011297079,0.00018412019,0.04075551,0.0000026761777,0.000067216366,0.00000831891,0.0009971452,0.0000015579776,0.00019718826,0.0018151545,0.023360532,0.9314809],"study_design_scores_gemma":[0.014557807,0.0012328133,0.25825033,0.0001306703,0.00014490866,0.00094143004,0.0058591575,0.000083931925,0.00029884474,0.6591561,0.059035733,0.00030832257],"about_ca_topic_score_codex":0.000008562821,"about_ca_topic_score_gemma":0.0000051542097,"teacher_disagreement_score":0.93117255,"about_ca_system_score_codex":0.000006426524,"about_ca_system_score_gemma":0.000031470758,"threshold_uncertainty_score":0.46594852},"labels":[],"label_agreement":null},{"id":"W2093001776","doi":"10.1177/1948550610375722","title":"Good Intentions, Optimistic Self-Predictions, and Missed Opportunities","year":2010,"lang":"en","type":"article","venue":"Social Psychological and Personality Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Psychology; Service (business); Social psychology; Control (management); Marketing; Computer science; Business","score_opus":0.3662162631969721,"score_gpt":0.46601707931043607,"score_spread":0.09980081611346397,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2093001776","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97902864,0.000032502332,0.00020981045,0.0068139737,0.00068592874,0.00008302489,0.000047286827,0.00006876789,0.013030081],"genre_scores_gemma":[0.9964104,0.00002692021,0.0020440477,0.0008381193,0.00014324258,0.0000057826137,0.0000013901976,0.0000031686054,0.0005268902],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99766606,0.00008938483,0.0003858095,0.00073044916,0.0008455814,0.00028272872],"domain_scores_gemma":[0.9985981,0.0004527991,0.00013535089,0.00024413297,0.00027595783,0.0002936532],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.004194524,0.00013250695,0.00022229587,0.00013589686,0.001361163,0.00074880687,0.0005835129,0.00013938163,0.00046297399],"category_scores_gemma":[0.0015347401,0.00009238975,0.000068645444,0.00046500383,0.0024378896,0.00040301803,0.00017805271,0.0003441641,0.00003120888],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000076373406,0.0007350691,0.04064169,0.0000071731133,0.000012705605,0.000027784245,0.0030561464,0.0000010615988,0.0076579456,0.06634985,0.007405821,0.8740284],"study_design_scores_gemma":[0.0004887344,0.0002617689,0.71836233,0.0000075541298,0.00002951327,0.00015355933,0.007566772,0.0013256486,0.000012469063,0.23302102,0.038362965,0.00040767336],"about_ca_topic_score_codex":0.000032575514,"about_ca_topic_score_gemma":0.00002557513,"teacher_disagreement_score":0.8736207,"about_ca_system_score_codex":0.000016517093,"about_ca_system_score_gemma":0.00007591221,"threshold_uncertainty_score":0.9999389},"labels":[],"label_agreement":null},{"id":"W2093195784","doi":"10.1016/j.tics.2012.01.009","title":"Environments for fast and slow thinking","year":2012,"lang":"en","type":"review","venue":"Trends in Cognitive Sciences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Psychology; Cognitive science; Cognitive psychology","score_opus":0.6635712376650964,"score_gpt":0.5627856902786511,"score_spread":0.1007855473864453,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2093195784","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00064259785,0.98858166,0.00050131103,0.000033809658,0.0009260715,0.00035987524,0.00032068614,0.000016070933,0.00861794],"genre_scores_gemma":[0.0046141185,0.98984593,0.0020135979,0.00008247133,0.00022487307,0.00014046908,0.000040544634,0.000030787945,0.0030071898],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99582106,0.0002444063,0.0011060998,0.0012697226,0.0009863935,0.00057232473],"domain_scores_gemma":[0.99357486,0.005199394,0.0007329607,0.00029920336,0.000042165208,0.0001514246],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0068645924,0.00041194964,0.0013777235,0.0015435106,0.00043960556,0.0006826788,0.0012542868,0.0002467051,0.00038905523],"category_scores_gemma":[0.0009988784,0.00026858944,0.00035081894,0.0013478678,0.00089453097,0.0006524389,0.00042553942,0.00027824444,0.00019148304],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000030480421,0.000046859943,0.00020530488,0.000028999084,0.0000067163037,0.0000023894,0.00018807637,5.4813324e-7,3.4573855e-8,0.00009655349,0.00013240914,0.99928904],"study_design_scores_gemma":[0.00024947023,0.0001394039,0.00025353674,0.002205239,0.00023739693,0.000026761712,0.0006330886,0.000057145306,6.7362527e-7,0.020330044,0.975364,0.00050323823],"about_ca_topic_score_codex":0.000010275906,"about_ca_topic_score_gemma":0.00004616526,"teacher_disagreement_score":0.9987858,"about_ca_system_score_codex":0.000074836564,"about_ca_system_score_gemma":0.000094677736,"threshold_uncertainty_score":0.99997663},"labels":[],"label_agreement":null},{"id":"W2094521969","doi":"10.1080/00036846.2014.889801","title":"Inducing risk preferences in multi-stage multi-agent laboratory experiments","year":2014,"lang":"en","type":"article","venue":"Applied Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Context (archaeology); Computer science; Binary number; Implementation; External validity; Outcome (game theory); Proof of concept; Range (aeronautics); Management science; Economics; Risk analysis (engineering); Microeconomics; Social psychology; Psychology; Mathematics; Software engineering; Business","score_opus":0.24982741796569363,"score_gpt":0.40417372918367966,"score_spread":0.15434631121798603,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2094521969","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99324656,0.00003395544,0.0029743272,0.000022138604,0.0009497546,0.00029522585,0.0000750315,0.00005430735,0.0023487208],"genre_scores_gemma":[0.9851617,0.000045909987,0.014122324,0.0002531516,0.000066637265,0.000062562925,0.0000075152625,0.00003367576,0.00024651107],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9969112,0.0001386726,0.0012598578,0.0010541506,0.00020789754,0.00042819572],"domain_scores_gemma":[0.9973127,0.0006968575,0.00068463455,0.0010392579,0.000064615975,0.00020191174],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0032603499,0.00030303645,0.0005794001,0.0004001734,0.0001876828,0.0004471582,0.0010807678,0.00022311395,0.00025944324],"category_scores_gemma":[0.0005136472,0.000275995,0.00010386188,0.00027891397,0.000109954955,0.00037637542,0.0003297145,0.00033837688,0.0018302288],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000093819355,0.00071694603,0.18280376,0.000005051059,0.000031155003,0.0000032062928,0.0026479443,0.03526927,0.0012382795,0.0022997044,0.00057159516,0.7743193],"study_design_scores_gemma":[0.016451864,0.0004035516,0.43005508,0.00011116613,0.00008731033,0.0000054805996,0.02317271,0.24218899,0.029094469,0.09892,0.15460372,0.004905643],"about_ca_topic_score_codex":0.00020032536,"about_ca_topic_score_gemma":0.001048829,"teacher_disagreement_score":0.7694136,"about_ca_system_score_codex":0.00021690982,"about_ca_system_score_gemma":0.0000995702,"threshold_uncertainty_score":0.99996924},"labels":[],"label_agreement":null},{"id":"W2095628489","doi":"10.1037/hea0000203","title":"Trust in deliberation: The consequences of deliberative decision strategies for medical decisions.","year":2015,"lang":"en","type":"article","venue":"Health Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":40,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"European Association of Social Psychology","keywords":"Deliberation; Decision aids; Debiasing; Psychology; Decision quality; Preference; Decision analysis; Quality (philosophy); Social psychology; Applied psychology; Medicine; Patient satisfaction; Political science; Epistemology; Nursing; Economics","score_opus":0.4095407242403531,"score_gpt":0.5695376546357794,"score_spread":0.15999693039542634,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2095628489","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.86254907,0.000693738,0.0903431,0.041916277,0.002046978,0.00063851813,0.000038931816,0.000022254742,0.001751109],"genre_scores_gemma":[0.97043383,0.00016996296,0.015452993,0.013649792,0.00011917245,0.00008284417,0.0000079122265,0.000013988621,0.0000694812],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9949969,0.0006708804,0.0021564865,0.00064291025,0.0011295119,0.00040329533],"domain_scores_gemma":[0.9879093,0.009619608,0.0006262194,0.00079797825,0.0007179386,0.0003289233],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.012925299,0.0001771773,0.0006343923,0.000385513,0.00018583264,0.00014196463,0.0011905303,0.00025161996,0.00028102405],"category_scores_gemma":[0.012934588,0.00010462199,0.000120152414,0.00076505763,0.0006339236,0.00031464547,0.00010300995,0.00029365803,0.000115039846],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00050577323,0.00017020646,0.0018451066,0.0000015382196,0.000004813679,0.000010145785,0.0022095467,0.00047578127,0.000008135464,0.0083545605,0.1089311,0.8774833],"study_design_scores_gemma":[0.0019333981,0.00082299876,0.0056573916,0.000097195814,0.0000037600926,0.00010974208,0.004154278,0.0018139426,0.000013134751,0.9301685,0.055075347,0.00015027208],"about_ca_topic_score_codex":0.00010162433,"about_ca_topic_score_gemma":0.0019452923,"teacher_disagreement_score":0.92181396,"about_ca_system_score_codex":0.0000829104,"about_ca_system_score_gemma":0.0021497204,"threshold_uncertainty_score":0.99537987},"labels":[],"label_agreement":null},{"id":"W2096285078","doi":"10.1016/j.obhdp.2007.10.002","title":"Willingness to pay for advice: The role of rational and experiential processing","year":2008,"lang":"en","type":"article","venue":"Organizational Behavior and Human Decision Processes","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta; Western University","funders":"","keywords":"Advice (programming); Willingness to pay; Experiential learning; Priming (agriculture); Information processing; Psychology; Social psychology; Marketing; Business; Economics; Cognitive psychology; Computer science; Microeconomics","score_opus":0.050387135522687684,"score_gpt":0.364274753712633,"score_spread":0.3138876181899453,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2096285078","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99137247,0.00035157413,0.007466214,0.00013797155,0.0001207014,0.0003817879,0.00006388236,0.000030011972,0.000075371165],"genre_scores_gemma":[0.994897,0.000023514942,0.0044158343,0.000105276886,0.00011772457,0.00007477432,0.000024892883,0.000025570345,0.0003154014],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9975791,0.000026490965,0.00078948674,0.00055800145,0.0008741308,0.00017277445],"domain_scores_gemma":[0.99640924,0.0008975208,0.000291183,0.00025365918,0.0020163727,0.0001320234],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00060064235,0.0001817695,0.00029557187,0.00020257916,0.001196905,0.00032875143,0.0004667656,0.00008755066,0.00030619832],"category_scores_gemma":[0.0017474955,0.00010870134,0.00004356458,0.00073532015,0.00021898292,0.0004662562,0.00018954497,0.00007943864,0.000011750893],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023710875,0.0005575326,0.53729326,0.000029233615,0.000010137771,0.000005347944,0.006848746,0.00012664298,0.007233542,0.0049273768,0.0024155022,0.44031557],"study_design_scores_gemma":[0.0024431169,0.00073520985,0.5869908,0.00024242523,0.00018849134,0.00039046173,0.006763878,0.000537579,0.02182993,0.3095554,0.06910328,0.0012194596],"about_ca_topic_score_codex":0.000005949762,"about_ca_topic_score_gemma":0.000023654891,"teacher_disagreement_score":0.43909612,"about_ca_system_score_codex":0.000016381575,"about_ca_system_score_gemma":0.00025419614,"threshold_uncertainty_score":0.92057467},"labels":[],"label_agreement":null},{"id":"W2096323387","doi":"10.1037/0096-3445.137.2.226","title":"The psychophysics of contingency assessment.","year":2008,"lang":"en","type":"article","venue":"Journal of Experimental Psychology General","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":48,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Contingency; Psychophysics; Psychology; Cognitive psychology; Contingency management; Perception; Epistemology","score_opus":0.19880600632582315,"score_gpt":0.5226753290690482,"score_spread":0.3238693227432251,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2096323387","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9844566,0.0011231765,0.00057118206,0.0005318888,0.004045388,0.00006320214,0.000003727955,0.0000043146906,0.009200524],"genre_scores_gemma":[0.9934061,0.00016759367,0.005066006,0.00038763828,0.00041083753,0.0000019446625,3.765366e-7,0.000011904846,0.0005475955],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99697536,0.00026864896,0.0015314409,0.0002433344,0.0007527789,0.00022844401],"domain_scores_gemma":[0.9970936,0.00045245493,0.0014404691,0.00053844,0.0003650481,0.000109977],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002025939,0.00014557969,0.0004403781,0.00016913084,0.00031964335,0.00005737708,0.0011566812,0.00009185843,0.0002074568],"category_scores_gemma":[0.00018271773,0.00008611685,0.00037843734,0.00027660606,0.00043861792,0.00026379625,0.000082422375,0.00033392088,0.000040987605],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007691107,0.0018403421,0.04215281,6.8604874e-7,0.0001435758,0.0001601615,0.0014804791,0.00014871467,0.47894183,0.0021099502,0.268534,0.20371832],"study_design_scores_gemma":[0.015248399,0.010088716,0.2912276,0.00008853114,0.00012387127,0.00747731,0.0069017345,0.0009693111,0.13544706,0.23154666,0.29936692,0.0015138818],"about_ca_topic_score_codex":0.000003824782,"about_ca_topic_score_gemma":0.0000011334284,"teacher_disagreement_score":0.34349477,"about_ca_system_score_codex":0.000040334973,"about_ca_system_score_gemma":0.000093399416,"threshold_uncertainty_score":0.35117432},"labels":[],"label_agreement":null},{"id":"W2097189960","doi":"10.1509/jmkr.46.6.764","title":"The Impact of Outcome Elaboration on Susceptibility to Contextual and Presentation Biases","year":2009,"lang":"en","type":"article","venue":"Journal of Marketing Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Elaboration; Presentation (obstetrics); Elaboration likelihood model; Framing (construction); Framing effect; Psychology; Outcome (game theory); Social psychology; Investment decisions; Business; Economics; Microeconomics; Behavioral economics; Finance; Medicine; Persuasion","score_opus":0.4183875299233983,"score_gpt":0.5932202538708223,"score_spread":0.17483272394742405,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2097189960","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99718064,0.000055768865,0.000047382273,0.0019187098,0.00009883098,0.00014651603,0.000006389647,0.0000022627498,0.0005434901],"genre_scores_gemma":[0.999525,0.000032489526,0.00016196753,0.00002193381,0.000087989334,5.214142e-7,2.1045054e-7,0.0000035919284,0.00016626915],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9948507,0.001963693,0.0011075635,0.00019067364,0.0016448915,0.00024251007],"domain_scores_gemma":[0.967648,0.029096853,0.00053632667,0.0003440498,0.0022209862,0.00015372623],"candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.07263652,0.00007474129,0.00024867835,0.00046717242,0.00025101917,0.0004634185,0.00050971005,0.00004732169,0.00006455683],"category_scores_gemma":[0.1337899,0.000038230068,0.00012910373,0.00063752325,0.00011807087,0.00026589466,0.000074790914,0.0003682421,0.000014131966],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0035525723,0.0001242241,0.16081326,0.0000011030418,0.000007953876,0.000005984609,0.0002954402,0.00072393165,0.0018858166,0.000035291807,0.010316681,0.82223773],"study_design_scores_gemma":[0.0003214122,0.0018562782,0.9858497,0.000068343055,0.0000031880506,0.000012171341,0.0018236383,0.00062889507,0.00019894096,0.008801878,0.00038570783,0.00004986671],"about_ca_topic_score_codex":0.000039906397,"about_ca_topic_score_gemma":0.00004177067,"teacher_disagreement_score":0.8250364,"about_ca_system_score_codex":0.00013432007,"about_ca_system_score_gemma":0.0001601374,"threshold_uncertainty_score":0.9549159},"labels":[],"label_agreement":null},{"id":"W2097216221","doi":"10.2139/ssrn.1597946","title":"Axiom of Monotonicity: An Experimental Test","year":2011,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Monotonic function; Axiom; Mathematical economics; Von Neumann architecture; Mathematics; Axiom independence; Test (biology); Expected utility hypothesis; Pure mathematics; Mathematical analysis; Geology","score_opus":0.11636289637144628,"score_gpt":0.39860079287675776,"score_spread":0.2822378965053115,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2097216221","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9915059,0.0023139592,0.0021538967,0.00008403801,0.001337913,0.00020692848,0.000034003453,0.000034018984,0.0023293376],"genre_scores_gemma":[0.9974917,0.000712193,0.00069322455,0.000043672502,0.00032320898,0.00000932906,0.000006453283,0.000049939845,0.0006702422],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9938979,0.00025823948,0.0017850907,0.0009034381,0.0012246167,0.001930715],"domain_scores_gemma":[0.9956213,0.000436574,0.0018175932,0.0014079412,0.00045621546,0.00026032917],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.008716791,0.0004322533,0.0009410646,0.00066480157,0.00022104876,0.00045231945,0.0032227268,0.00044922178,0.0005318709],"category_scores_gemma":[0.00082872465,0.00034132143,0.00060913415,0.0002582567,0.00019007771,0.0004621674,0.00094979274,0.004046299,0.00021167586],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032521755,0.002286617,0.008205599,0.0000054669513,0.00017665068,0.000035238696,0.002055412,0.00056511204,0.004272338,0.021279313,0.00047469125,0.9603183],"study_design_scores_gemma":[0.00042084107,0.0010300224,0.00041318004,0.000050791183,0.000051657098,0.00034481272,0.0040254085,0.00042473935,0.0039033282,0.98827434,0.00064634695,0.00041451398],"about_ca_topic_score_codex":0.00027496528,"about_ca_topic_score_gemma":0.00052506005,"teacher_disagreement_score":0.96699506,"about_ca_system_score_codex":0.0010822706,"about_ca_system_score_gemma":0.0046478654,"threshold_uncertainty_score":0.99990386},"labels":[],"label_agreement":null},{"id":"W2097949912","doi":"10.1086/656570","title":"The Locus of Choice: Personal Causality and Satisfaction with Hedonic and Utilitarian Decisions","year":2010,"lang":"en","type":"article","venue":"Journal of Consumer Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":378,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Booth University College","funders":"","keywords":"Pleasure; Outcome (game theory); Psychology; Causality (physics); Valence (chemistry); Social psychology; Consumption (sociology); Attribution; Economics; Microeconomics","score_opus":0.23888570809045664,"score_gpt":0.49747238384875897,"score_spread":0.2585866757583023,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2097949912","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99684197,0.0010798388,0.00006570192,0.0015047614,0.00024230774,0.00010202998,0.000009527274,0.0000018903347,0.00015198687],"genre_scores_gemma":[0.9990843,0.0002797467,0.00045325104,0.000010163691,0.000042457374,0.0000013194589,8.823945e-8,0.000006683183,0.00012200069],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99671,0.00035728997,0.0007384937,0.00022514783,0.0017191719,0.00024990394],"domain_scores_gemma":[0.98552907,0.011894525,0.00037443513,0.00037776635,0.0016140526,0.00021018347],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0132440785,0.000092127804,0.00029097617,0.00036111457,0.0006163836,0.0005664097,0.00040736044,0.00008963309,0.00012905449],"category_scores_gemma":[0.008827368,0.000046102898,0.00006637971,0.00039889145,0.0013943076,0.00035377682,0.00015642395,0.0010047,0.000011601392],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022254823,0.000027878308,0.31470743,0.000001194736,0.000018872848,0.00001116755,0.00023519881,7.4278637e-7,0.0007935179,0.0001784408,0.00072998524,0.68307304],"study_design_scores_gemma":[0.0008937492,0.00044569263,0.9213261,0.000060830633,0.000026472153,0.0005827603,0.0019949318,0.00021728981,0.000119195356,0.03165911,0.04257171,0.000102178354],"about_ca_topic_score_codex":0.00044192118,"about_ca_topic_score_gemma":0.004886888,"teacher_disagreement_score":0.6829709,"about_ca_system_score_codex":0.00002751429,"about_ca_system_score_gemma":0.000527083,"threshold_uncertainty_score":0.9995217},"labels":[],"label_agreement":null},{"id":"W2098440477","doi":"10.1257/0895330027274","title":"Evolution and Human Nature","year":2002,"lang":"en","type":"article","venue":"The Journal of Economic Perspectives","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":164,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Generalization; Rationality; Simple (philosophy); Economics; Mathematical economics; Consumption (sociology); Positive economics; Neoclassical economics; Basis (linear algebra); Bounded rationality; Microeconomics; Epistemology; Sociology; Mathematics; Philosophy; Social science","score_opus":0.08608143798576275,"score_gpt":0.38544158849260474,"score_spread":0.299360150506842,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2098440477","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9901041,0.0027447673,0.000108003645,0.0013016172,0.00038713563,0.000037897462,0.0000037048906,0.000005026558,0.0053077894],"genre_scores_gemma":[0.99877685,0.00012097149,0.00011575642,0.000048854294,0.00030872464,2.1854346e-7,3.30074e-8,0.0000062807367,0.000622306],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99888486,0.00012458906,0.0005357287,0.00015553094,0.00017997838,0.00011928864],"domain_scores_gemma":[0.9983528,0.0005821613,0.00057508907,0.00028544324,0.00013302774,0.00007145982],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022325364,0.0000940968,0.0002462653,0.00022832376,0.00022106191,0.00017489545,0.00058892707,0.000078139565,0.0007792713],"category_scores_gemma":[0.00030052167,0.000054568583,0.000115170136,0.00007822814,0.00019754663,0.0004796389,0.00007630493,0.0003607282,0.00014948721],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00059584976,0.00093565555,0.0695517,0.0000054043076,0.0003923521,0.00007112511,0.059533626,0.005036356,0.0069265794,0.18687002,0.20475908,0.46532226],"study_design_scores_gemma":[0.0011647445,0.00060168735,0.1047886,0.00003612624,0.00009375328,0.0011681524,0.05131704,0.0035835113,0.00009639722,0.8224711,0.014327421,0.00035148146],"about_ca_topic_score_codex":0.000015888594,"about_ca_topic_score_gemma":0.00003957297,"teacher_disagreement_score":0.63560104,"about_ca_system_score_codex":0.00020460192,"about_ca_system_score_gemma":0.00002144246,"threshold_uncertainty_score":0.8532474},"labels":[],"label_agreement":null},{"id":"W2098507972","doi":"10.1080/20445911.2015.1055274","title":"Rapid makes risky: Time pressure increases risk seeking in decisions from experience","year":2015,"lang":"en","type":"article","venue":"Journal of Cognitive Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":66,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Alberta Gambling Research Institute, University of Calgary; Natural Sciences and Engineering Research Council of Canada","keywords":"Risk-seeking; Outcome (game theory); Psychology; Value (mathematics); Social psychology; Actuarial science; Economics; Microeconomics; Computer science","score_opus":0.20014104285725035,"score_gpt":0.45779549500493255,"score_spread":0.25765445214768223,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2098507972","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98814327,0.0019045561,0.0049803774,0.00026755396,0.0011231625,0.00014806872,0.0001431773,0.000012290289,0.0032775428],"genre_scores_gemma":[0.99620795,0.00026624597,0.0025028612,0.00059062755,0.00029075873,0.000007196566,0.000003073501,0.000017867573,0.00011343554],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9953668,0.0010900147,0.001694077,0.00054092455,0.0009766304,0.00033155485],"domain_scores_gemma":[0.98672533,0.009531531,0.0016576863,0.00044773857,0.0012726993,0.00036500115],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0046610045,0.00022682238,0.0007919831,0.0008630839,0.00009964232,0.00020846206,0.0010910069,0.00021827646,0.0013978018],"category_scores_gemma":[0.031834483,0.00016672081,0.00024219639,0.0006554543,0.00028157936,0.0006916954,0.00017260334,0.00063178514,0.0007910408],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013022359,0.0005368212,0.121511735,1.8531792e-7,0.000049923558,0.00032201796,0.0027229167,0.00005945364,0.00018228628,0.0000054508137,0.00992213,0.86338484],"study_design_scores_gemma":[0.008395697,0.001797044,0.60274225,0.00056821905,0.00027482497,0.0008485516,0.012502459,0.0013391731,0.00022756767,0.28138375,0.089202896,0.0007175492],"about_ca_topic_score_codex":0.00011272681,"about_ca_topic_score_gemma":0.00006128622,"teacher_disagreement_score":0.8626673,"about_ca_system_score_codex":0.000041343425,"about_ca_system_score_gemma":0.00019298733,"threshold_uncertainty_score":0.99998695},"labels":[],"label_agreement":null},{"id":"W2098762910","doi":"10.1027/1618-3169/a000043","title":"Prime Proportion Affects Masked Priming of Fixed and Free-Choice Responses","year":2009,"lang":"en","type":"article","venue":"Experimental Psychology (formerly Zeitschrift für Experimentelle Psychologie)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Priming (agriculture); Psychology; Prime (order theory); Response priming; Cognitive psychology; Social psychology; Communication; Audiology; Neuroscience; Mathematics; Biology; Cognition; Lexical decision task; Medicine; Combinatorics","score_opus":0.14740292458741788,"score_gpt":0.49836681132233696,"score_spread":0.3509638867349191,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2098762910","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9637444,0.0041895243,0.0011160446,0.0012843625,0.0018905846,0.0010900573,0.00002993615,0.000242798,0.026412286],"genre_scores_gemma":[0.988991,0.00012331248,0.008117758,0.0016146088,0.00016796583,0.00008673034,0.000017948429,0.00006141302,0.0008192274],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99272615,0.00060928595,0.0021656128,0.0022080194,0.0012617894,0.001029116],"domain_scores_gemma":[0.99422896,0.0010838315,0.0013206664,0.0027035438,0.00023592668,0.00042708704],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0025934493,0.0007968867,0.0012959036,0.0010074547,0.00042738885,0.00026129908,0.0021012858,0.0006124274,0.00095937843],"category_scores_gemma":[0.0016478101,0.00066429714,0.00041049137,0.00088101934,0.0008829762,0.0009998208,0.0004030935,0.0005683109,0.00028265352],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0025134254,0.002440883,0.0062810807,0.0000043821065,0.000060966686,0.000053012292,0.0027220924,0.000004491075,0.714526,0.0010289478,0.017363407,0.25300133],"study_design_scores_gemma":[0.010037838,0.013304057,0.106001824,0.00020068201,0.000069746966,0.00048704923,0.008737031,0.00013081415,0.79543275,0.008507108,0.055073507,0.0020175814],"about_ca_topic_score_codex":0.00003473949,"about_ca_topic_score_gemma":0.0000033268127,"teacher_disagreement_score":0.25098374,"about_ca_system_score_codex":0.000051783027,"about_ca_system_score_gemma":0.000099690646,"threshold_uncertainty_score":0.99995387},"labels":[],"label_agreement":null},{"id":"W2099097516","doi":"10.1017/s0022109009990019","title":"Probability Judgment Error and Speculation in Laboratory Asset Market Bubbles","year":2009,"lang":"en","type":"article","venue":"Journal of Financial and Quantitative Analysis","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":46,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Irrationality; Speculation; Asset (computer security); Aggregate (composite); Economics; Econometrics; Stochastic game; Dimension (graph theory); Bubble; Financial economics; Rationality; Mathematics; Mathematical economics; Computer science; Finance; Political science","score_opus":0.12865268021857032,"score_gpt":0.39953894716552374,"score_spread":0.2708862669469534,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2099097516","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9967429,0.0003956913,0.0017323599,0.00083329045,0.00006390733,0.000051331288,0.000020098552,0.0000017941369,0.00015864294],"genre_scores_gemma":[0.9938297,0.00008132388,0.00590383,0.00012223331,0.000027464157,4.3213242e-7,7.456294e-7,0.0000017812216,0.000032440374],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9980902,0.00021130346,0.00091617706,0.0002379228,0.00042835693,0.0001160398],"domain_scores_gemma":[0.9981537,0.00051230745,0.0006414394,0.00013564492,0.00047291748,0.00008399662],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004104302,0.00010435837,0.0005378392,0.00076054427,0.0000768552,0.0001520653,0.00014182266,0.000062128136,0.00006850222],"category_scores_gemma":[0.0023291202,0.00007272758,0.00015319204,0.0013339642,0.000077302604,0.00047360922,0.00002588705,0.00014021345,0.0000028357358],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006542689,0.00047540452,0.65399015,0.000005466608,0.00010056663,0.00009203872,0.0015835998,0.0015166049,0.00064335,0.004596218,0.0024853447,0.33385697],"study_design_scores_gemma":[0.0002567844,0.00029900487,0.88941485,0.000018946022,0.00012787158,0.0000029940304,0.0003121031,0.0023888163,0.000024280507,0.10610678,0.00095980166,0.00008776212],"about_ca_topic_score_codex":0.000019295954,"about_ca_topic_score_gemma":0.00038335644,"teacher_disagreement_score":0.3337692,"about_ca_system_score_codex":0.000047244597,"about_ca_system_score_gemma":0.00009090012,"threshold_uncertainty_score":0.29657444},"labels":[],"label_agreement":null},{"id":"W2099195699","doi":"10.1287/deca.1100.0177","title":"The Role of Some Functional Equations in Decision Analysis","year":2010,"lang":"en","type":"article","venue":"Decision Analysis","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":65,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Differentiable function; Simple (philosophy); Mathematics; Applied mathematics; Decision theory; Functional equation; Expected utility hypothesis; Bayesian probability; Characterization (materials science); Mathematical economics; Mathematical optimization; Computer science; Differential equation; Mathematical analysis; Statistics","score_opus":0.055785507729414124,"score_gpt":0.37940877589865396,"score_spread":0.3236232681692398,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2099195699","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9159593,0.00019277938,0.082025684,0.00023207504,0.0005961224,0.00012016648,0.000051850206,0.00002323316,0.0007988088],"genre_scores_gemma":[0.9948319,0.000045189638,0.004581389,0.00007695349,0.00007480044,0.000016959555,0.000027095088,0.000014167655,0.00033154053],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9929253,0.0002262917,0.0026074192,0.0010182981,0.0028093182,0.0004133716],"domain_scores_gemma":[0.97634375,0.019078374,0.0009023088,0.002506206,0.00093277346,0.00023661157],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.008854282,0.00027916758,0.0010577545,0.0054932795,0.000512203,0.00065842335,0.0018974623,0.00025750793,0.0030898927],"category_scores_gemma":[0.012855247,0.00017425275,0.001778565,0.016622286,0.00024604137,0.000588943,0.00039194885,0.00049222517,0.0007012878],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013103498,0.00018317606,0.13992427,1.170195e-7,0.00045180673,0.0000036079095,0.000088954934,0.033642486,0.00049047393,0.0050590253,0.0003974429,0.8196276],"study_design_scores_gemma":[0.00037198237,0.00003054568,0.30820546,0.0000049631853,0.0014565387,0.0000015154505,0.00068892905,0.21849385,0.00017727246,0.45655847,0.013759494,0.00025101128],"about_ca_topic_score_codex":0.00026676868,"about_ca_topic_score_gemma":0.015082886,"teacher_disagreement_score":0.8193766,"about_ca_system_score_codex":0.00007279437,"about_ca_system_score_gemma":0.00014049688,"threshold_uncertainty_score":0.9978214},"labels":[],"label_agreement":null},{"id":"W2099443649","doi":"10.1111/ecin.12294","title":"THE DUAL‐PROCESS DRIFT DIFFUSION MODEL: EVIDENCE FROM RESPONSE TIMES","year":2015,"lang":"en","type":"article","venue":"Economic Inquiry","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":59,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Dual (grammatical number); Diffusion; Process (computing); Quality (philosophy); Econometrics; Decision process; Computer science; Key (lock); Economics; Simple (philosophy); Diffusion process; Operations research; Microeconomics; Mathematics; Innovation diffusion; Management science; Physics; Thermodynamics","score_opus":0.31888650802808277,"score_gpt":0.4526974124004771,"score_spread":0.13381090437239435,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2099443649","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9900486,0.0004104146,0.0011254376,0.0024338113,0.00492028,0.0001590179,0.000035520035,0.000072932125,0.0007939888],"genre_scores_gemma":[0.99479896,0.000048515274,0.0006540732,0.00034009787,0.00071234506,0.00002038222,0.0000034067907,0.000029383385,0.0033928298],"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9966854,0.000372164,0.0010993759,0.000902541,0.00053773343,0.0004027792],"domain_scores_gemma":[0.99142295,0.0060001207,0.0004947851,0.0015850122,0.00019702032,0.0003001002],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.008205101,0.00025258542,0.00041176108,0.00017517614,0.00043089825,0.0009989995,0.0016708075,0.0001693848,0.00033150648],"category_scores_gemma":[0.0048682867,0.0001655324,0.00017392782,0.00015261813,0.00038456538,0.001085367,0.00050063827,0.00023420517,0.0068836496],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.006126282,0.00017016695,0.012937488,0.0000018498253,0.000047068337,0.000056670488,0.022711953,0.099061295,0.00090318243,0.0007736171,0.47647685,0.38073358],"study_design_scores_gemma":[0.0011318111,0.00023270427,0.0052812365,0.00009930462,0.000036157868,0.00002244187,0.010291562,0.35165408,0.0011825908,0.5593371,0.069935575,0.000795459],"about_ca_topic_score_codex":0.000101684156,"about_ca_topic_score_gemma":0.00011420655,"teacher_disagreement_score":0.5585635,"about_ca_system_score_codex":0.0002717663,"about_ca_system_score_gemma":0.0006255636,"threshold_uncertainty_score":0.99388963},"labels":[],"label_agreement":null},{"id":"W2099604660","doi":"10.2139/ssrn.1623057","title":"Prospect Theory, Indifference Curves, and Hedging Risks","year":2010,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":53,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Prospect theory; Monotonic function; Mathematical economics; Function (biology); Expected utility hypothesis; Von Neumann–Morgenstern utility theorem; Simple (philosophy); Economics; Sign (mathematics); Decision theory; Cumulative prospect theory; Mathematics; Microeconomics","score_opus":0.07755965383883055,"score_gpt":0.39455548387154354,"score_spread":0.316995830032713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2099604660","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9921168,0.0018485544,0.0036417283,0.0007190089,0.0006499633,0.0001053797,0.0000035133726,0.000027238118,0.0008878],"genre_scores_gemma":[0.99656075,0.001848211,0.00022927951,0.00017831758,0.00020814923,0.0000029133066,5.972059e-7,0.000016125885,0.0009556425],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9968048,0.00015764902,0.0005792298,0.000423599,0.0006252649,0.0014094808],"domain_scores_gemma":[0.9981941,0.0006473758,0.00038480214,0.00043837685,0.00016571328,0.00016962398],"candidate_categories":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.012743333,0.00017886369,0.00030508856,0.00024068975,0.00041591816,0.00054988544,0.0009082978,0.00010628976,0.00027210073],"category_scores_gemma":[0.002023437,0.000121832214,0.000115939,0.00028380842,0.0001560369,0.00042628727,0.00014684864,0.0029812371,0.0001545626],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030006791,0.000039770173,0.030543031,0.0000011305187,0.000014807448,0.0000059252793,0.00014064842,0.0000010333262,0.00047749546,0.052789062,0.00022095811,0.91573614],"study_design_scores_gemma":[0.00026802116,0.00013457023,0.01238507,0.000029519351,0.000018351479,0.0009989562,0.00047186675,0.00008427213,0.000071576134,0.9838282,0.001540797,0.00016881089],"about_ca_topic_score_codex":0.000025042209,"about_ca_topic_score_gemma":0.0006946182,"teacher_disagreement_score":0.93103915,"about_ca_system_score_codex":0.00013599354,"about_ca_system_score_gemma":0.0009389785,"threshold_uncertainty_score":0.9993189},"labels":[],"label_agreement":null},{"id":"W2099612900","doi":"10.1086/677840","title":"The Categorization of Time and Its Impact on Task Initiation","year":2014,"lang":"en","type":"article","venue":"Journal of Consumer Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":97,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Booth University College","funders":"","keywords":"Categorization; Task (project management); Psychology; Library science; Computer science; Data science; Information retrieval; Artificial intelligence; Management; Economics","score_opus":0.2159407105635714,"score_gpt":0.5187064700277652,"score_spread":0.30276575946419376,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2099612900","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99785095,0.00025483785,0.00012842116,0.000601808,0.00013024239,0.00006827923,0.000004959382,0.0000014929634,0.00095903064],"genre_scores_gemma":[0.99949664,0.00018090513,0.000026525631,0.000014997413,0.000058732097,5.2225164e-7,4.0485753e-7,0.0000052634637,0.0002160369],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9970805,0.00063295197,0.0006600415,0.0001137777,0.0013531462,0.00015956612],"domain_scores_gemma":[0.99094486,0.0065287673,0.00047337174,0.000227348,0.0017184188,0.00010723465],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.014640056,0.000059963528,0.00020500676,0.00044503823,0.00019618844,0.00028992712,0.00044625415,0.0000517396,0.000106013074],"category_scores_gemma":[0.008823435,0.00002956641,0.00007925454,0.000391528,0.00012245605,0.00027259887,0.000066554305,0.0002890843,0.00019697218],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005188432,0.000102439626,0.014777138,0.000002414633,0.000029160245,0.0000059167774,0.0003323594,0.00043041797,0.007370515,0.00084176013,0.010785406,0.96480364],"study_design_scores_gemma":[0.004392795,0.0075709727,0.29140088,0.00040275426,0.00008058073,0.0003835817,0.0011737454,0.054131113,0.019429367,0.50742817,0.11300004,0.00060597854],"about_ca_topic_score_codex":0.000007853344,"about_ca_topic_score_gemma":0.000005385505,"teacher_disagreement_score":0.96419764,"about_ca_system_score_codex":0.00004310574,"about_ca_system_score_gemma":0.00017128754,"threshold_uncertainty_score":0.99952567},"labels":[],"label_agreement":null},{"id":"W2099624208","doi":"10.3389/fpsyg.2014.01232","title":"Visual representation of rational belief revision: another look at the Sleeping Beauty problem","year":2014,"lang":"en","type":"article","venue":"Frontiers in Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Psychology; Beauty; Cognition; Representation (politics); Cognitive psychology; Cognitive science; Social psychology; Aesthetics; Art; Neuroscience","score_opus":0.07546069025137843,"score_gpt":0.4222605587468244,"score_spread":0.346799868495446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2099624208","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.74443895,0.00041477845,0.2318774,0.004177231,0.0039927927,0.00039898345,0.000009697434,0.000023691144,0.014666489],"genre_scores_gemma":[0.9569329,0.0000790499,0.03837195,0.0026480348,0.0002640538,0.0000247493,0.000016281749,0.000026172904,0.0016367743],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9972769,0.0004772474,0.00094043906,0.0005916401,0.00048480876,0.00022898552],"domain_scores_gemma":[0.9980102,0.0006412352,0.0004690615,0.00070680387,0.00013238158,0.000040300227],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003326149,0.00012138006,0.00037175862,0.000298894,0.00012280364,0.00005162527,0.0006378007,0.00014309134,0.0005768069],"category_scores_gemma":[0.00086155895,0.00008237725,0.00012018272,0.0005536157,0.00027961546,0.00018074052,0.00013369252,0.00015957728,0.00017455718],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010817486,0.00007559539,0.089060694,0.0000011520362,0.0000066520797,0.000001317298,0.00027701355,0.00024025947,0.00023217425,0.00019160645,0.15369734,0.75610805],"study_design_scores_gemma":[0.0019505129,0.00039122015,0.09224375,0.000069835056,0.000024814984,0.00003724717,0.0006228472,0.00841819,0.000564897,0.49475855,0.400556,0.00036215168],"about_ca_topic_score_codex":0.000011430627,"about_ca_topic_score_gemma":0.000029627847,"teacher_disagreement_score":0.7557459,"about_ca_system_score_codex":0.000054947726,"about_ca_system_score_gemma":0.000026569516,"threshold_uncertainty_score":0.6315631},"labels":[],"label_agreement":null},{"id":"W2101259449","doi":"10.1017/s0140525x0700177x","title":"Frequency formats are a small part of the base rate story","year":2007,"lang":"en","type":"article","venue":"Behavioral and Brain Sciences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; University of British Columbia","funders":"","keywords":"Base (topology); Neglect; Set (abstract data type); Extensional definition; Computer science; Psychology; Cognitive psychology; Mathematics; Programming language; Mathematical analysis; Geology","score_opus":0.23596867891259238,"score_gpt":0.4007649844225061,"score_spread":0.1647963055099137,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2101259449","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99604124,0.0001365051,0.000111425536,0.001742038,0.00088040746,0.00016220719,0.000045088756,0.00002106921,0.00085999444],"genre_scores_gemma":[0.99772763,0.0000051404327,0.0008948776,0.000580498,0.00005503193,0.000003875744,6.026251e-7,0.0000052918167,0.0007270693],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99738765,0.00019228867,0.0007203102,0.00052780606,0.00078549806,0.00038645527],"domain_scores_gemma":[0.9974904,0.0011022834,0.0005628652,0.00049352815,0.0001890242,0.0001619211],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010725115,0.00016895302,0.00029973342,0.00023490583,0.000660126,0.00027464185,0.0012446992,0.000092106086,0.00013637717],"category_scores_gemma":[0.0009076168,0.000090581656,0.00015986346,0.0009529823,0.0011784981,0.0004945172,0.000287291,0.00018227135,0.00003419485],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020063386,0.00019000367,0.354441,0.0000032009816,0.0000017673813,0.000019242272,0.00076492043,0.00001314252,0.0051812986,0.0007857628,0.0044384403,0.63414115],"study_design_scores_gemma":[0.00067143,0.00049125677,0.87826985,0.0001564126,0.00004266942,0.00007349233,0.010365946,0.00016449601,0.006751074,0.078080416,0.024313483,0.0006194754],"about_ca_topic_score_codex":0.00015495319,"about_ca_topic_score_gemma":0.0011968828,"teacher_disagreement_score":0.6335217,"about_ca_system_score_codex":0.000026060754,"about_ca_system_score_gemma":0.0001263874,"threshold_uncertainty_score":0.5077222},"labels":[],"label_agreement":null},{"id":"W2102140188","doi":"10.1177/154193120504900344","title":"An Empirical Study of Calibration in Air Traffic Control Expert Judgment","year":2005,"lang":"en","type":"article","venue":"Proceedings of the Human Factors and Ergonomics Society Annual Meeting","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Air traffic control; Probabilistic logic; Calibration; Control (management); Task (project management); Computer science; Aggregate (composite); Differential (mechanical device); Separation (statistics); Traffic conflict; Dempster–Shafer theory; Point (geometry); Mathematics; Statistics; Engineering; Artificial intelligence; Machine learning; Transport engineering; Traffic congestion","score_opus":0.06756849667941899,"score_gpt":0.3613776112737702,"score_spread":0.2938091145943512,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2102140188","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993318,0.0000301718,0.0000051668394,0.00017049674,0.000092187554,0.0002825434,0.000016587761,0.000015988537,0.000055057855],"genre_scores_gemma":[0.99943393,0.0000062393515,0.00032334714,0.00011891893,0.000081057675,0.000006947088,6.6600296e-7,0.000013563201,0.000015311258],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99789715,0.000032607142,0.0010396856,0.00043775322,0.00037887233,0.00021393741],"domain_scores_gemma":[0.9986644,0.00025737204,0.00064757944,0.00017147131,0.00017708023,0.000082137776],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018562261,0.00018380456,0.00046408945,0.0000888006,0.00025927048,0.000098501216,0.0006283064,0.00011781073,0.000008336465],"category_scores_gemma":[0.0001889333,0.0001220551,0.00018965818,0.00021518052,0.00013128242,0.00070435466,0.00015694121,0.00019004614,4.7062846e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001257659,0.0013592291,0.8553245,0.000009609453,0.000031689127,7.9601726e-8,0.1130929,0.010504787,0.0049396027,0.00006622018,0.0009703467,0.013575267],"study_design_scores_gemma":[0.0032208492,0.001202031,0.56312317,0.0001265287,0.00006305335,0.0000021663138,0.3731248,0.05194792,0.0044207308,0.0014614073,0.00069998344,0.00060738594],"about_ca_topic_score_codex":0.00009160682,"about_ca_topic_score_gemma":0.00011076082,"teacher_disagreement_score":0.29220137,"about_ca_system_score_codex":0.000090951566,"about_ca_system_score_gemma":0.000026719355,"threshold_uncertainty_score":0.49772623},"labels":[],"label_agreement":null},{"id":"W2102173652","doi":"10.1037//1076-898x.6.3.171","title":"People focus on optimistic scenarios and disregard pessimistic scenarios while predicting task completion times.","year":2000,"lang":"en","type":"article","venue":"Journal of Experimental Psychology Applied","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":124,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Pessimism; Debiasing; Optimism; Task (project management); Psychology; Optimism bias; Hindsight bias; Social psychology; Computer science; Economics","score_opus":0.07007589911618983,"score_gpt":0.3848782485121402,"score_spread":0.31480234939595036,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2102173652","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9726229,0.00024009323,0.0006305891,0.0005559877,0.0006498666,0.00021416115,0.000016679958,0.000024658248,0.02504509],"genre_scores_gemma":[0.99723125,0.000027598715,0.0016614053,0.0006094453,0.00023725827,0.000010067845,0.000003615565,0.000026389194,0.00019300208],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99689966,0.00012816333,0.0013044635,0.0005870077,0.0007335287,0.00034718754],"domain_scores_gemma":[0.9977331,0.0007260987,0.00068286434,0.00047893715,0.000105327956,0.0002736688],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0013648883,0.00028022978,0.0007122953,0.00030585087,0.00031274822,0.0002405351,0.00064040447,0.0001884999,0.004201863],"category_scores_gemma":[0.00018089177,0.00021723582,0.00017068804,0.00025816157,0.00023087971,0.0002014322,0.000075530195,0.00046761995,0.0004247511],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.009993287,0.0054185763,0.011700405,0.000011106046,0.0002445588,0.00037280953,0.0072398647,0.009878704,0.08525406,0.0015293438,0.08506162,0.7832957],"study_design_scores_gemma":[0.0857994,0.031508226,0.30523646,0.00185518,0.0014507208,0.018096633,0.04094363,0.06483086,0.031801503,0.29719636,0.11176673,0.009514281],"about_ca_topic_score_codex":0.000006654936,"about_ca_topic_score_gemma":0.0000052315963,"teacher_disagreement_score":0.7737814,"about_ca_system_score_codex":0.00010729761,"about_ca_system_score_gemma":0.000044692042,"threshold_uncertainty_score":0.99670845},"labels":[],"label_agreement":null},{"id":"W2103448616","doi":"10.4284/0038-4038-78.3.878","title":"Nosy Preferences, Benevolence, and Efficiency","year":2012,"lang":"en","type":"article","venue":"Southern Economic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Impossibility; Externality; Consumption (sociology); Economics; Microeconomics; Preference; Social preferences; Intervention (counseling); Revealed preference; Dynamic inconsistency; Mathematical economics; Positive economics; Public economics; Psychology; Sociology","score_opus":0.1050548393513444,"score_gpt":0.3656873631541224,"score_spread":0.260632523802778,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2103448616","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99058396,0.00065654906,0.0005856932,0.00016448632,0.0020813972,0.000063453175,0.00004276548,0.00001939502,0.0058022966],"genre_scores_gemma":[0.9978958,0.000057186906,0.0006252982,0.00009791608,0.00062666816,0.0000016287411,6.112132e-7,0.000016044452,0.00067887374],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99791336,0.00011036152,0.0008595927,0.0003294921,0.0002937409,0.0004934482],"domain_scores_gemma":[0.99820685,0.00041119408,0.0005100483,0.00038374634,0.000068030386,0.00042013358],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.003794961,0.0001816527,0.00033177214,0.0002779267,0.00034070632,0.00071141525,0.00074761023,0.0001041247,0.0023578696],"category_scores_gemma":[0.00031120837,0.00012999975,0.00013958242,0.000095971314,0.00014138763,0.0007444786,0.00016486805,0.0003049109,0.005599245],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002086701,0.00005993104,0.20224248,6.2253827e-7,0.0000116137435,0.0000028956015,0.0019064941,0.00015567253,0.00003350573,0.00032808757,0.0016211887,0.79361665],"study_design_scores_gemma":[0.0025467507,0.00044613265,0.103860885,0.000114268856,0.000117056,0.0032710203,0.03070884,0.0042825677,0.00018882674,0.687676,0.16505842,0.0017292341],"about_ca_topic_score_codex":0.00002395053,"about_ca_topic_score_gemma":0.00003166172,"teacher_disagreement_score":0.7918874,"about_ca_system_score_codex":0.000104211606,"about_ca_system_score_gemma":0.00012767769,"threshold_uncertainty_score":0.9985541},"labels":[],"label_agreement":null},{"id":"W2104262895","doi":"10.1017/s0963180108080067","title":"Affective Forecasting and Its Implications for Medical Ethics","year":2007,"lang":"en","type":"article","venue":"Cambridge Quarterly of Healthcare Ethics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Bioethics; Mental health; Medical ethics; Variety (cybernetics); Psychology; Medical humanities; Sociology; Law; Medicine; Psychiatry; Political science; Medical education; Computer science","score_opus":0.33309999016335373,"score_gpt":0.5106748121936675,"score_spread":0.17757482203031377,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2104262895","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89022756,0.0006491799,0.058028847,0.049057882,0.00088325894,0.0006157119,0.00022287795,0.00005191858,0.00026278896],"genre_scores_gemma":[0.99596125,0.00005243718,0.0023367682,0.001295698,0.00021675647,0.00002463775,0.00001315977,0.000026550655,0.00007275558],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.995474,0.00043865046,0.0014949171,0.00072187633,0.0013444967,0.0005260942],"domain_scores_gemma":[0.94767046,0.047701754,0.00067395146,0.0005975957,0.002816041,0.00054022274],"candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.031848572,0.0002134313,0.0005430335,0.00034228893,0.00065377855,0.00011630166,0.000658119,0.0011235031,0.000009036809],"category_scores_gemma":[0.029095711,0.00018526835,0.00017933898,0.0004712102,0.00030636124,0.00025449728,0.00007201365,0.0019484845,0.000016805872],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007741853,0.000057204714,0.0019800083,0.00012078662,0.0000091296,0.000005713304,0.0057723504,0.0000017625042,0.00007543832,0.057506345,0.0006558043,0.93373805],"study_design_scores_gemma":[0.004973946,0.014333211,0.14887145,0.0021604968,0.00018020607,0.0014689146,0.04777426,0.012872691,0.0015259044,0.73160094,0.031747542,0.0024904313],"about_ca_topic_score_codex":0.00022563463,"about_ca_topic_score_gemma":0.002554553,"teacher_disagreement_score":0.9312476,"about_ca_system_score_codex":0.000096405885,"about_ca_system_score_gemma":0.0014263196,"threshold_uncertainty_score":0.99691564},"labels":[],"label_agreement":null},{"id":"W2104463177","doi":"10.1016/j.cognition.2009.07.003","title":"Probability matching in choice under uncertainty: Intuition versus deliberation","year":2009,"lang":"en","type":"article","venue":"Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":96,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Intuition; Deliberation; Psychology; Exploit; Matching (statistics); Cognitive psychology; Cognition; Computer science; Cognitive science; Statistics; Mathematics","score_opus":0.2730349298543821,"score_gpt":0.42630204457183013,"score_spread":0.15326711471744803,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2104463177","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9850752,0.000013800045,0.008728667,0.0008674422,0.00047976643,0.0002257799,0.000008686669,0.000057369136,0.0045433077],"genre_scores_gemma":[0.9985702,0.0000041517164,0.0007580426,0.0004744713,0.00009356395,0.0000117265945,0.00005042704,0.000005500817,0.000031896467],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99815565,0.00015119983,0.0005958801,0.0004547759,0.0004563814,0.00018613193],"domain_scores_gemma":[0.99839395,0.0008306153,0.00017552664,0.00028877574,0.00024999023,0.00006116412],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015461857,0.00011904876,0.00018112842,0.00024705008,0.00012534927,0.00032628188,0.00020294456,0.00011203213,0.00021357244],"category_scores_gemma":[0.0013315452,0.000105477724,0.00007048994,0.00048129575,0.00003627969,0.00076494913,0.000030004843,0.00017027574,0.00036711295],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001922273,0.00016105038,0.00021020893,0.0000010978113,0.0000016476846,0.000002445419,0.00016898972,0.008236245,0.00084943225,0.00059527124,0.0004813147,0.9891001],"study_design_scores_gemma":[0.001033617,0.00016404064,0.03135002,0.000040286155,0.0000116887095,0.0000029350417,0.0002812636,0.0033685865,0.00027166549,0.962648,0.00065790757,0.00017002551],"about_ca_topic_score_codex":0.000025553552,"about_ca_topic_score_gemma":0.00056836585,"teacher_disagreement_score":0.98893005,"about_ca_system_score_codex":0.00019479806,"about_ca_system_score_gemma":0.000053527732,"threshold_uncertainty_score":0.47186166},"labels":[],"label_agreement":null},{"id":"W2104694716","doi":"10.1017/s193029750000214x","title":"Bracketing effects on risk tolerance: Generalizability and underlying mechanisms","year":2010,"lang":"en","type":"article","venue":"Judgment and Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Bracketing (phenomenology); Generalizability theory; Outcome (game theory); Psychology; Econometrics; Statistics; Mathematics; Mathematical economics; Epistemology","score_opus":0.0798934455622458,"score_gpt":0.39101243165103944,"score_spread":0.3111189860887936,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2104694716","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9708344,0.000105727326,0.026083441,0.00010862545,0.0017614563,0.00028470802,0.00000883625,0.00006640147,0.0007464323],"genre_scores_gemma":[0.94434184,0.00003471665,0.05478079,0.00064317585,0.00012800997,0.000011949219,7.0066125e-7,0.000023353923,0.000035487526],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9963462,0.00017019658,0.0008794408,0.0011248273,0.0010901708,0.00038917686],"domain_scores_gemma":[0.99048007,0.007886162,0.00045772849,0.00082538906,0.0001377685,0.00021289468],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0054302793,0.00031086468,0.00050286297,0.0003667251,0.0007699994,0.0011776491,0.00045374405,0.00021952133,0.00019431874],"category_scores_gemma":[0.0039023764,0.00022845971,0.00013602307,0.00034903098,0.00009954481,0.00039083662,0.00041918317,0.00053418364,0.00012833084],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000110467605,0.00004096181,0.012262595,0.000004131752,0.0000039543766,0.0000099045055,0.00013826106,0.00012999709,0.0020434593,0.00153794,0.0004823625,0.98323596],"study_design_scores_gemma":[0.0008534519,0.00022274932,0.055693846,0.00015375052,0.000027465154,0.00001932409,0.00021660476,0.019178132,0.00075013045,0.9199986,0.0024742929,0.00041164662],"about_ca_topic_score_codex":0.0000138903415,"about_ca_topic_score_gemma":0.00006934354,"teacher_disagreement_score":0.9828243,"about_ca_system_score_codex":0.00003702902,"about_ca_system_score_gemma":0.000027006647,"threshold_uncertainty_score":0.9998592},"labels":[],"label_agreement":null},{"id":"W2105153401","doi":"10.1111/j.1936-4490.2002.tb00665.x","title":"The Neglect of Base Rate Data by Human Resources Managers in Employee Selection","year":2002,"lang":"en","type":"article","venue":"Canadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l Administration","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Manitoba; University of Toronto","funders":"","keywords":"Selection (genetic algorithm); Base (topology); Neglect; Factorial analysis; Computer science; Operations research; Welfare economics; Statistics; Psychology; Mathematics; Artificial intelligence; Economics","score_opus":0.3194110214112298,"score_gpt":0.408064228159764,"score_spread":0.08865320674853422,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2105153401","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99275696,0.00048999046,0.00023576622,0.0019195767,0.00044601623,0.00018675579,0.00012708474,0.0000056262093,0.0038322438],"genre_scores_gemma":[0.9977876,0.000046570076,0.001491854,0.00010803662,0.00009359406,0.0000036920046,0.0000038582402,0.000009854812,0.0004549567],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99516356,0.00075174647,0.0017581816,0.0007843928,0.000605478,0.00093661406],"domain_scores_gemma":[0.99462885,0.0017641569,0.0014861624,0.0005928039,0.00057375187,0.0009542919],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":["sts"],"category_scores_codex":[0.014581481,0.00026253253,0.00046651036,0.0010701258,0.0024968735,0.001615549,0.0042186226,0.00012263913,0.00027055148],"category_scores_gemma":[0.00651293,0.0001938344,0.00013353275,0.003550738,0.0060465117,0.0019245028,0.00006419643,0.00037824272,0.000009343493],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030228775,0.00053662853,0.5497555,0.000076178825,0.00012864689,0.001603712,0.049740393,0.008991051,0.014530112,0.018428639,0.06614303,0.28976384],"study_design_scores_gemma":[0.0030554316,0.03391544,0.19746563,0.0015783877,0.0002834705,0.0056128176,0.15279931,0.08878982,0.009962566,0.4233995,0.07970168,0.0034359402],"about_ca_topic_score_codex":0.008758009,"about_ca_topic_score_gemma":0.70047057,"teacher_disagreement_score":0.69171256,"about_ca_system_score_codex":0.00061469706,"about_ca_system_score_gemma":0.0026339632,"threshold_uncertainty_score":0.9994209},"labels":[],"label_agreement":null},{"id":"W2106603618","doi":"10.1509/jmkr.44.3.379","title":"Mental Simulation and Preference Consistency over Time: The Role of Process- versus Outcome-Focused Thoughts","year":2007,"lang":"en","type":"article","venue":"Journal of Marketing Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Outcome (game theory); Consistency (knowledge bases); Preference; Focus (optics); Process (computing); Psychology; Mental model; Computer science; Social psychology; Economics; Artificial intelligence; Microeconomics","score_opus":0.3375896713148078,"score_gpt":0.526534674367092,"score_spread":0.18894500305228418,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2106603618","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99514997,0.0002758855,0.000035322315,0.00016564863,0.00020510097,0.00013094056,0.0000040463433,0.0000032989458,0.0040297597],"genre_scores_gemma":[0.9992395,0.000017230059,0.0003428177,0.000008130725,0.000115929055,4.6977527e-7,1.8699879e-7,0.000007571055,0.00026817172],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9953554,0.0007936781,0.001150943,0.0002076222,0.0021935708,0.0002987828],"domain_scores_gemma":[0.9712451,0.026256893,0.000735549,0.00029761836,0.0013475473,0.00011726114],"candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.058449138,0.00008995095,0.0002745427,0.000413798,0.00026239222,0.00022230188,0.0006769306,0.0000768246,0.00022344047],"category_scores_gemma":[0.025508283,0.000050779625,0.00009936413,0.0005404761,0.0002597913,0.00031908887,0.00018799306,0.00049206964,0.000018814546],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0061468803,0.00012985824,0.18316627,0.000008302503,0.000024274847,0.000012344969,0.0009675184,0.00036838738,0.00090924127,0.000030406572,0.0006198122,0.8076167],"study_design_scores_gemma":[0.0046918667,0.00140072,0.85663956,0.0004509536,0.0000657678,0.000078543155,0.012576859,0.0334412,0.0024507344,0.06304086,0.024757607,0.0004053154],"about_ca_topic_score_codex":0.0000060609614,"about_ca_topic_score_gemma":0.000014054719,"teacher_disagreement_score":0.8072114,"about_ca_system_score_codex":0.00007635414,"about_ca_system_score_gemma":0.0001610119,"threshold_uncertainty_score":0.9827003},"labels":[],"label_agreement":null},{"id":"W2106910765","doi":"10.1037/e527312012-437","title":"Examination of the Belief Bias Effect Across Two Domains of Reasoning","year":2008,"lang":"en","type":"dataset","venue":"PsycEXTRA Dataset","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Blackberry (Canada)","funders":"University of Waterloo","keywords":"Confirmation bias; Psychology; Cognitive psychology; Computer science; Social psychology","score_opus":0.1452255819973375,"score_gpt":0.4483448199623918,"score_spread":0.30311923796505424,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2106910765","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15322977,0.00012447737,0.000021121474,0.000024134442,0.0011669517,0.0003576791,0.8450265,0.000009456711,0.000039947474],"genre_scores_gemma":[0.019964702,0.00014195606,0.0002496179,0.00007745831,0.00013716747,0.000018227169,0.9793554,0.000022430386,0.000033051023],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9936095,0.0009119294,0.0019350564,0.0010073873,0.0020945263,0.0004415942],"domain_scores_gemma":[0.9888851,0.0038359875,0.0024983827,0.0044000098,0.00025269104,0.00012784253],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0075381054,0.00046796032,0.0011342929,0.000346234,0.00031936847,0.00019759868,0.004247038,0.00036570287,0.00039912033],"category_scores_gemma":[0.0059276633,0.00029120184,0.0004069867,0.0010612557,0.0006211661,0.00036412902,0.0010349704,0.0005834839,0.00040777648],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005097621,0.00016396059,0.00032659862,0.000024811512,0.000024527726,0.000015867146,0.000057797308,0.0000449557,0.000032791944,0.000004691007,0.93240464,0.066848405],"study_design_scores_gemma":[0.00074227236,0.00019379711,0.00437526,0.00024974474,0.00010235944,0.00008010291,0.000068092035,0.00004303767,0.00035336416,0.00037716216,0.99309087,0.0003239284],"about_ca_topic_score_codex":0.00064979604,"about_ca_topic_score_gemma":0.0007541259,"teacher_disagreement_score":0.13432893,"about_ca_system_score_codex":0.00006979973,"about_ca_system_score_gemma":0.0001404784,"threshold_uncertainty_score":0.999954},"labels":[],"label_agreement":null},{"id":"W2106984223","doi":"10.1016/s0010-0277(00)00098-6","title":"Frequency versus probability formats in statistical word problems","year":2000,"lang":"en","type":"article","venue":"Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":215,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Frequency; Psychology; Weighting; Set (abstract data type); Word lists by frequency; Bayesian probability; Judgement; Bayesian inference; Cognitive psychology; Cognition; Bayes' theorem; Base (topology); Posterior probability; Word (group theory); Selection (genetic algorithm); Bayesian statistics; Natural language processing; Artificial intelligence; Statistics; Computer science; Linguistics; Mathematics; Epistemology","score_opus":0.20417059624771422,"score_gpt":0.40108066347240307,"score_spread":0.19691006722468885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2106984223","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9615769,0.000014052473,0.00072597805,0.00013742529,0.00025175908,0.00027119546,0.0000630385,0.00004007419,0.036919586],"genre_scores_gemma":[0.9968811,0.000012376317,0.002819007,0.000067951005,0.00002985863,0.00003561396,0.00003351874,0.0000067606525,0.00011379567],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9981314,0.00011310245,0.0006628262,0.00040382275,0.00045146365,0.00023736904],"domain_scores_gemma":[0.9985744,0.00080396177,0.00009035213,0.00030974302,0.00013159821,0.00008996746],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0013313533,0.00010866736,0.00019598096,0.00013715349,0.00008134612,0.00019998291,0.00026211716,0.000089567446,0.0049259905],"category_scores_gemma":[0.0011320319,0.00008891749,0.000051269773,0.00039572787,0.00009717231,0.0005221995,0.000030058703,0.00015621229,0.0033868274],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011394227,0.000133599,0.0013529932,0.000002349059,0.0000012418137,0.000007780204,0.00011018523,0.000059374164,0.000030373403,0.0002829365,0.00046338278,0.9974418],"study_design_scores_gemma":[0.0010444173,0.00012782468,0.026136339,0.00003610561,0.0000095833775,0.0000062185372,0.00009209764,0.00088470744,0.00006420233,0.96795726,0.0034692052,0.00017203901],"about_ca_topic_score_codex":0.000021164995,"about_ca_topic_score_gemma":0.0002862416,"teacher_disagreement_score":0.9972698,"about_ca_system_score_codex":0.000080777674,"about_ca_system_score_gemma":0.000056923243,"threshold_uncertainty_score":0.99738914},"labels":[],"label_agreement":null},{"id":"W2107140099","doi":"10.2139/ssrn.1708662","title":"Conditioning and Updating Under Cumulative Prospect Theory","year":2010,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Cumulative prospect theory; Conditioning; Prospect theory; Econometrics; Economics; Mathematical economics; Mathematics; Statistics; Microeconomics","score_opus":0.04169701125775222,"score_gpt":0.37357937343413244,"score_spread":0.33188236217638023,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2107140099","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9846382,0.00016217782,0.010910497,0.00044896663,0.0004802984,0.000075376935,0.0000030873139,0.000023708593,0.003257653],"genre_scores_gemma":[0.9978523,0.000054261192,0.0006237953,0.00013539087,0.00023098776,0.0000020045688,0.0000011857884,0.000015683423,0.0010843652],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99742407,0.0001458994,0.000545164,0.0003405394,0.0004812578,0.0010630887],"domain_scores_gemma":[0.99804187,0.0009865634,0.00040018125,0.00025760377,0.00020197341,0.00011181276],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0102882115,0.00014163996,0.00022587285,0.00021248711,0.00058509636,0.000618753,0.0004239979,0.00009200713,0.0004082712],"category_scores_gemma":[0.001444706,0.000101922735,0.00009664104,0.00022685893,0.00015264051,0.000584953,0.00009304242,0.0021454885,0.00013666294],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028537168,0.000026372989,0.005045467,2.2204307e-7,0.00002339015,0.0000031241182,0.00021796522,0.00007489932,0.0009171939,0.60051656,0.00007267859,0.3930736],"study_design_scores_gemma":[0.00032542818,0.00010287303,0.0031865186,0.000007330891,0.0000143954085,0.0006160842,0.004848571,0.00034445754,0.00009232908,0.98968977,0.00063375523,0.00013848516],"about_ca_topic_score_codex":0.000009124792,"about_ca_topic_score_gemma":0.0003961515,"teacher_disagreement_score":0.3929351,"about_ca_system_score_codex":0.00017274747,"about_ca_system_score_gemma":0.00073096587,"threshold_uncertainty_score":0.9321199},"labels":[],"label_agreement":null},{"id":"W2107461833","doi":"10.1086/513048","title":"Explaining Cognitive Lock-In: The Role of Skill-Based Habits of Use in Consumer Choice","year":2007,"lang":"en","type":"article","venue":"Journal of Consumer Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Product (mathematics); Consumption (sociology); Preference; Consumer choice; Cognition; Cognitive psychology; New product development; Psychology; Computer science; Microeconomics; Marketing; Economics; Business; Mathematics","score_opus":0.31521481904714405,"score_gpt":0.5151390014624746,"score_spread":0.19992418241533055,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2107461833","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9974309,0.0009557178,0.00015458779,0.00015895056,0.00012325584,0.00020933792,0.000015030599,0.0000015484554,0.0009506241],"genre_scores_gemma":[0.99935955,0.00004555664,0.0004518996,0.000060571772,0.000029120467,0.0000024068984,5.018888e-7,0.000011094969,0.000039297884],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99355525,0.0010402845,0.002020489,0.00025980314,0.0026565234,0.00046763645],"domain_scores_gemma":[0.9565215,0.03949733,0.00089384365,0.0004257496,0.0025188318,0.00014275662],"candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.03249536,0.00013084104,0.0005874437,0.002144964,0.00008356365,0.00015279176,0.0011478328,0.00012685923,0.00017124473],"category_scores_gemma":[0.022857675,0.00008321519,0.00019218627,0.0017068739,0.00059594464,0.0004797,0.00012135438,0.0009920488,0.000039240676],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00056491786,0.0003857026,0.8022018,0.0000041584626,0.000014813517,0.00013191951,0.001172433,0.0000701325,0.0008161205,0.00006752509,0.00032643598,0.19424401],"study_design_scores_gemma":[0.0043705525,0.00075264875,0.92985374,0.0011078322,0.000036263216,0.00011926301,0.02588172,0.0005825573,0.015046156,0.008725362,0.013258027,0.00026588808],"about_ca_topic_score_codex":0.00035239753,"about_ca_topic_score_gemma":0.0010319287,"teacher_disagreement_score":0.19397813,"about_ca_system_score_codex":0.00007494781,"about_ca_system_score_gemma":0.0005636399,"threshold_uncertainty_score":0.9962496},"labels":[],"label_agreement":null},{"id":"W2107488010","doi":"10.1086/322896","title":"Affect Monitoring and the Primacy of Feelings in Judgment","year":2001,"lang":"en","type":"article","venue":"Journal of Consumer Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":39,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Feeling; Psychology; Valence (chemistry); Affect (linguistics); Social psychology; Context (archaeology); Cognition; Cognitive psychology; Communication","score_opus":0.39898533093959654,"score_gpt":0.5488671100228116,"score_spread":0.1498817790832151,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2107488010","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99547994,0.002043677,0.00003633079,0.001471408,0.00023227584,0.000120756864,6.130927e-7,0.0000011672403,0.00061380694],"genre_scores_gemma":[0.9983608,0.0010349283,0.0003475857,0.000010053194,0.000062844454,0.0000017998407,1.8415097e-8,0.000005189981,0.00017676741],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9965126,0.00057553645,0.00092902646,0.00014991128,0.0016042267,0.00022871437],"domain_scores_gemma":[0.9924793,0.00601185,0.0003620593,0.00028916288,0.0007588503,0.000098736076],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.024767261,0.000067651665,0.0003630798,0.00070389744,0.00009424985,0.00023336704,0.0006937124,0.00004462225,0.00006748774],"category_scores_gemma":[0.004860659,0.000035718123,0.00010523551,0.00064313185,0.00038414623,0.00024302039,0.00019993649,0.0005476162,0.000024144449],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007845327,0.000093477815,0.34186518,0.0000031516734,0.00001449001,0.0000781912,0.00082522264,0.000048133043,0.0011640644,0.00013157188,0.0007522225,0.6542398],"study_design_scores_gemma":[0.016719786,0.0012253078,0.6004403,0.0012957219,0.000073914765,0.0012329856,0.013261234,0.0015279809,0.010466852,0.26359472,0.08967562,0.00048552337],"about_ca_topic_score_codex":0.00008374648,"about_ca_topic_score_gemma":0.000013964127,"teacher_disagreement_score":0.65375423,"about_ca_system_score_codex":0.00006055075,"about_ca_system_score_gemma":0.0001645748,"threshold_uncertainty_score":0.8583887},"labels":[],"label_agreement":null},{"id":"W2108109108","doi":"10.7202/602099ar","title":"Prenons-nous assez de risque dans les théories du risque?","year":2009,"lang":"fr","type":"article","venue":"L Actualité économique","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Philosophy; Humanities","score_opus":0.08868676796405378,"score_gpt":0.34401250803978073,"score_spread":0.25532574007572695,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2108109108","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9314161,0.001509315,0.010836936,0.013710268,0.0024654686,0.00048040051,0.000288181,0.00022915553,0.0390642],"genre_scores_gemma":[0.97245586,0.0010484793,0.0073300027,0.0020152282,0.0010785809,0.000037474598,0.000019832762,0.00007286185,0.015941698],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9938694,0.0008911623,0.0020718179,0.0015290909,0.00034643296,0.0012920747],"domain_scores_gemma":[0.9925627,0.0037303634,0.000871023,0.0017470168,0.0003674037,0.0007214797],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0041165147,0.00081196084,0.001257096,0.00043410767,0.0007315872,0.0017970281,0.0021703327,0.0010449837,0.0021347064],"category_scores_gemma":[0.003316162,0.00076634774,0.0006910966,0.0005714538,0.0006174975,0.0015073556,0.00033069335,0.00090197386,0.0017806352],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015771833,0.0007779715,0.014975409,0.0000150309925,0.000063104475,0.00019404406,0.008752336,0.0030224952,0.0005424308,0.049011458,0.01028671,0.9122013],"study_design_scores_gemma":[0.0008610871,0.00073898665,0.018746,0.00022734294,0.00015832306,0.00038409242,0.0032414286,0.0061986907,0.0041647744,0.533794,0.43021446,0.0012708576],"about_ca_topic_score_codex":0.0029586896,"about_ca_topic_score_gemma":0.0020523346,"teacher_disagreement_score":0.91093045,"about_ca_system_score_codex":0.0013944298,"about_ca_system_score_gemma":0.0011636714,"threshold_uncertainty_score":0.99947876},"labels":[],"label_agreement":null},{"id":"W2109177972","doi":"10.1287/deca.1030.0003","title":"Elicitation of Probabilities Using Competitive Scoring Rules","year":2004,"lang":"en","type":"article","venue":"Decision Analysis","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":55,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Scoring rule; Payment; Event (particle physics); Competition (biology); Construct (python library); Computer science; Econometrics; Subsidy; Economics; Actuarial science; Mathematical economics; Machine learning; Finance","score_opus":0.1691811700026969,"score_gpt":0.433281247962438,"score_spread":0.2641000779597411,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2109177972","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8634527,0.000057964528,0.13507387,0.000058847425,0.00018221147,0.0000974921,0.00003707735,0.000023859982,0.0010159815],"genre_scores_gemma":[0.9407312,0.000010737215,0.05911305,0.000044620065,0.000030071005,0.00000288903,0.000007850669,0.000010496593,0.00004908118],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9961495,0.000115801646,0.0014531052,0.0006418279,0.0014145798,0.00022518919],"domain_scores_gemma":[0.99547565,0.0019770649,0.0006477038,0.0008695318,0.0009135565,0.00011646451],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025837389,0.0001848482,0.00075074105,0.001882415,0.00018829656,0.0002799726,0.0006884198,0.000097488984,0.0005041181],"category_scores_gemma":[0.003457534,0.00014222221,0.0006479155,0.0030904294,0.00017825013,0.00047577167,0.00017523182,0.00010834375,0.00024025717],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013226671,0.00030486914,0.03372315,0.000003873521,0.00027806786,0.00001433941,0.0017970181,0.30207866,0.0017436888,0.01683476,0.000045035176,0.64304423],"study_design_scores_gemma":[0.00082492776,0.00012121506,0.04816379,0.00012860342,0.0007302411,0.000008284595,0.006186638,0.024455445,0.0027472945,0.9152657,0.0009422741,0.00042563124],"about_ca_topic_score_codex":0.0002502551,"about_ca_topic_score_gemma":0.00033144886,"teacher_disagreement_score":0.8984309,"about_ca_system_score_codex":0.00016904638,"about_ca_system_score_gemma":0.00011076634,"threshold_uncertainty_score":0.5799653},"labels":[],"label_agreement":null},{"id":"W2109631530","doi":"10.1093/imaman/dps024","title":"Integration-segregation decisions under general value functions: 'Create your own bundle--choose 1, 2 or all 3!'","year":2012,"lang":"en","type":"article","venue":"IMA Journal of Management Mathematics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Portfolio; Product (mathematics); Value (mathematics); Sign (mathematics); Microeconomics; Cover (algebra); Capital (architecture); Business; Economics; Computer science; Financial economics; Mathematics","score_opus":0.2693601958006623,"score_gpt":0.43260511778220817,"score_spread":0.1632449219815459,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2109631530","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6753675,0.00018571333,0.3166797,0.00076817663,0.0018192703,0.00027127826,0.000011840787,0.000029363084,0.00486717],"genre_scores_gemma":[0.7231683,0.00034023862,0.2607928,0.0006600629,0.0005330941,0.000014433882,0.000008009932,0.000055555676,0.014427478],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9952919,0.00016820052,0.0021880555,0.0002761384,0.0016566262,0.00041910255],"domain_scores_gemma":[0.99507475,0.0015703486,0.0016544152,0.00078991277,0.0006017147,0.00030888777],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0054918085,0.00029456808,0.00056671235,0.00091962004,0.00024378781,0.00073290325,0.0010086263,0.0001157692,0.0010844468],"category_scores_gemma":[0.0020952711,0.00017895381,0.0003754345,0.00060514413,0.000076245575,0.0015826549,0.00025466338,0.00029478635,0.0010760529],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002964079,0.0024894231,0.00068288716,0.000019409146,0.00037028585,0.000058422098,0.0019635945,0.007002669,0.00020765518,0.051253602,0.07026668,0.865389],"study_design_scores_gemma":[0.0021918542,0.00048826006,0.0077702994,0.0005241334,0.0008972081,0.00078605994,0.0123813525,0.013720778,0.00028611353,0.8721514,0.088059165,0.0007433791],"about_ca_topic_score_codex":0.0000046765404,"about_ca_topic_score_gemma":0.000006274224,"teacher_disagreement_score":0.8646456,"about_ca_system_score_codex":0.0002264852,"about_ca_system_score_gemma":0.000064012915,"threshold_uncertainty_score":0.9998287},"labels":[],"label_agreement":null},{"id":"W2110163890","doi":"10.1371/journal.pcbi.1003894","title":"Some Work and Some Play: Microscopic and Macroscopic Approaches to Labor and Leisure","year":2014,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Concordia University; Gatsby Charitable Foundation","keywords":"Work (physics); Process (computing); Imperfect; Computation; Computer science; Markov process; Stochastic process; Statistical physics; Mathematical economics; Economics; Mathematics; Physics; Algorithm; Statistics","score_opus":0.17146928710499973,"score_gpt":0.35081374640989366,"score_spread":0.17934445930489393,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2110163890","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9942552,0.0005592473,0.0008967052,0.0038265986,0.00021194837,0.00015360466,0.000050750037,0.00002465365,0.000021330898],"genre_scores_gemma":[0.98864096,0.00001276411,0.010029305,0.0010770367,0.00013479189,0.000010987142,0.000014749309,0.000009289664,0.0000700837],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9985349,0.00013766796,0.00036786983,0.0006014617,0.00015333072,0.00020474115],"domain_scores_gemma":[0.99786705,0.0016438944,0.00011076183,0.0001663704,0.00006134393,0.00015059653],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057833747,0.0001510892,0.0003547502,0.00019187707,0.00017279749,0.00022879029,0.0001974182,0.00012046834,0.000015752461],"category_scores_gemma":[0.00038547826,0.00011630726,0.00002173719,0.00016174516,0.00024292755,0.00016042042,0.0002528202,0.000106462525,0.00006734139],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009186446,0.00012588028,0.6503628,0.000015141651,0.000036936854,0.0000034084103,0.00070626126,0.0010197364,0.0012904097,0.07631981,0.00077600445,0.26925176],"study_design_scores_gemma":[0.00055297895,0.0002532929,0.34561348,0.000024256658,0.000013451111,0.000013303392,0.00005708025,0.0030797096,0.00013117888,0.64614797,0.0038788763,0.00023444231],"about_ca_topic_score_codex":0.0000046033347,"about_ca_topic_score_gemma":0.0000053930826,"teacher_disagreement_score":0.56982815,"about_ca_system_score_codex":0.000012572319,"about_ca_system_score_gemma":0.000029513518,"threshold_uncertainty_score":0.4742872},"labels":[],"label_agreement":null},{"id":"W2110284785","doi":"10.2139/ssrn.925223","title":"Inventor Perseverance After Being Told to Quit: The Role of Cognitive Biases","year":2006,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":53,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Cognition; Psychology; Cognitive psychology; Social psychology","score_opus":0.032761845232533504,"score_gpt":0.33494089573646146,"score_spread":0.30217905050392796,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2110284785","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99479777,0.0015005036,0.00089453236,0.00060625403,0.00022587832,0.00011664604,0.000013596434,0.000009476723,0.001835356],"genre_scores_gemma":[0.99826187,0.000080828424,0.00005894831,0.00023051031,0.00026873167,0.000007994659,7.523975e-7,0.000013873552,0.0010764658],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99708676,0.00013878066,0.00066764,0.0002925495,0.0007191045,0.0010951618],"domain_scores_gemma":[0.99785984,0.0011594743,0.00031921992,0.00026759013,0.00031525016,0.00007864632],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035648558,0.00014624186,0.0002642495,0.00022929373,0.000220622,0.00023708025,0.0006929185,0.00005674943,0.00018090286],"category_scores_gemma":[0.0015420154,0.00009042003,0.00022286564,0.00044831965,0.00008583045,0.00028434646,0.00010081955,0.00066733523,0.0002006931],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003416774,0.00016917787,0.036632184,4.759004e-7,0.000039254406,0.000010528142,0.0010738674,0.00037765547,0.00057938363,0.011600961,0.00047912713,0.9486957],"study_design_scores_gemma":[0.0003432181,0.00028835124,0.007566415,0.000106500534,0.000037567774,0.0001651877,0.008289131,0.00015119085,0.00084004604,0.97785944,0.004170792,0.00018215961],"about_ca_topic_score_codex":0.00018240881,"about_ca_topic_score_gemma":0.001960203,"teacher_disagreement_score":0.96625847,"about_ca_system_score_codex":0.00026220197,"about_ca_system_score_gemma":0.00066053774,"threshold_uncertainty_score":0.36872217},"labels":[],"label_agreement":null},{"id":"W2110669621","doi":"10.1177/1948550611415694","title":"This is Your Portfolio on Winter","year":2011,"lang":"en","type":"article","venue":"Social Psychological and Personality Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":95,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Psychology; Affect (linguistics); Depression (economics); Risk aversion (psychology); Portfolio; Social psychology; Developmental psychology; Finance; Economics; Expected utility hypothesis; Financial economics","score_opus":0.5698122209072847,"score_gpt":0.5101614510538217,"score_spread":0.05965076985346296,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2110669621","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.832373,0.000011933191,0.000029105939,0.0015463824,0.0004340003,0.000059604383,0.000023789995,0.000027721955,0.16549441],"genre_scores_gemma":[0.9908797,0.000004278529,0.00034110507,0.005524393,0.00013057285,0.0000027818348,3.1635497e-7,0.0000035013652,0.0031133408],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99713993,0.000085146574,0.0003950435,0.000986697,0.0010280295,0.0003651598],"domain_scores_gemma":[0.9989406,0.00016403018,0.0001570923,0.00033570308,0.00017934058,0.00022322338],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0035096821,0.00015013535,0.0002539734,0.00013787091,0.0007027497,0.0003162393,0.0010443587,0.00013020146,0.012934402],"category_scores_gemma":[0.00058999535,0.00009285022,0.00013463522,0.00073402905,0.0017678456,0.00033799524,0.00017360481,0.00023873184,0.001375842],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019689604,0.0005114836,0.063453436,9.4952907e-7,0.0000045997685,0.00002655654,0.00979597,4.1849628e-8,0.00039812335,0.007101144,0.05175963,0.8667512],"study_design_scores_gemma":[0.00025724564,0.00045606744,0.7655466,0.0000059351546,0.0000068081113,0.000021649243,0.0015931971,0.00002789048,0.00006058818,0.2117539,0.01997873,0.00029136444],"about_ca_topic_score_codex":0.000058913618,"about_ca_topic_score_gemma":0.000004571198,"teacher_disagreement_score":0.8664598,"about_ca_system_score_codex":0.000029972489,"about_ca_system_score_gemma":0.000031847085,"threshold_uncertainty_score":0.9994017},"labels":[],"label_agreement":null},{"id":"W2110691199","doi":"10.2139/ssrn.338280","title":"How Should a Behavioral Economist Do Welfare Economics?","year":2002,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Economics; Welfare; Behavioral economics; Behavioural economics; Public economics; Neoclassical economics; Microeconomics; Market economy","score_opus":0.13637239068503698,"score_gpt":0.3550400299084867,"score_spread":0.21866763922344973,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2110691199","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9793677,0.0013862364,0.000981647,0.013139165,0.0012097394,0.00014727515,0.000025920372,0.00005248797,0.003689872],"genre_scores_gemma":[0.98747355,0.00134567,0.0002511712,0.00020606244,0.000501418,0.000007803344,0.0000023353077,0.000049966977,0.01016205],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99482244,0.00014534853,0.0010704115,0.0008061239,0.0004934687,0.0026621756],"domain_scores_gemma":[0.9975895,0.00020392443,0.0007508818,0.00089449127,0.0002203802,0.00034080294],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.004304574,0.0003795358,0.00062461983,0.00052757503,0.0007097466,0.002937471,0.0018524211,0.00024257805,0.0018534347],"category_scores_gemma":[0.00031923642,0.00030903524,0.00056593784,0.00030918475,0.00014384504,0.001382321,0.00018126595,0.002103385,0.0010473221],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029023317,0.00016169739,0.0025958668,3.8744977e-7,0.000031147254,0.000014413431,0.00011848368,0.00007299739,0.000009217539,0.029855888,0.0016985615,0.9654123],"study_design_scores_gemma":[0.0010124485,0.00050668675,0.00038543745,0.000008608342,0.00005315436,0.0013932188,0.005298938,0.0007879011,0.000022861468,0.7061794,0.28379303,0.00055832224],"about_ca_topic_score_codex":0.000036374357,"about_ca_topic_score_gemma":0.0008181774,"teacher_disagreement_score":0.964854,"about_ca_system_score_codex":0.0015740134,"about_ca_system_score_gemma":0.0004764741,"threshold_uncertainty_score":0.99993616},"labels":[],"label_agreement":null},{"id":"W2111046244","doi":"10.1111/ecin.12287","title":"THE EVOLUTIONARY LOGIC OF HONORING SUNK COSTS","year":2015,"lang":"en","type":"article","venue":"Economic Inquiry","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Sunk costs; Cognitive dissonance; Economics; Phenomenon; Function (biology); Positive economics; Microeconomics; Neoclassical economics; Psychology; Social psychology; Epistemology","score_opus":0.3533139611296619,"score_gpt":0.4440464302118628,"score_spread":0.0907324690822009,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2111046244","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97923785,0.00039819838,0.00024340776,0.00054064795,0.008004828,0.00010534054,0.0000146534485,0.000026532816,0.011428558],"genre_scores_gemma":[0.99768955,0.000024308496,0.0005632307,0.000106719344,0.00063314685,0.000007776881,0.000002276159,0.000011200871,0.00096181297],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9980562,0.00011505047,0.0008958742,0.00040171697,0.0002685289,0.00026265712],"domain_scores_gemma":[0.9970417,0.0013613321,0.00043164004,0.00086430076,0.00015654162,0.00014446539],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0036446285,0.00012928093,0.000291588,0.00014697459,0.00017768395,0.00018452978,0.0010770479,0.00008818825,0.00016077198],"category_scores_gemma":[0.0011016041,0.0000865312,0.00014319323,0.00012429146,0.00037511755,0.00037584864,0.00030423226,0.00012419652,0.0029785612],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019245967,0.00008858361,0.05332612,0.000001376451,0.000028455745,0.000010652261,0.0012686631,0.006773937,0.00005486174,0.020985816,0.3394085,0.5778606],"study_design_scores_gemma":[0.0009943969,0.00025916068,0.024289971,0.00002653941,0.000019285953,0.00006230025,0.008364631,0.008019893,0.00028212427,0.59969836,0.35751122,0.00047208933],"about_ca_topic_score_codex":0.00006980948,"about_ca_topic_score_gemma":0.000050602113,"teacher_disagreement_score":0.5787126,"about_ca_system_score_codex":0.00040465945,"about_ca_system_score_gemma":0.00027036064,"threshold_uncertainty_score":0.9977977},"labels":[],"label_agreement":null},{"id":"W2111552019","doi":"10.1017/s0140525x07001835","title":"Nested sets theory, full stop: Explaining performance on Bayesian inference tasks without dual-systems assumptions","year":2007,"lang":"en","type":"article","venue":"Behavioral and Brain Sciences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Dual (grammatical number); Inference; Bayesian inference; Computer science; Core (optical fiber); Bayesian probability; Series (stratigraphy); Artificial intelligence; Econometrics; Mathematics; Linguistics","score_opus":0.19633574027412745,"score_gpt":0.44454411877298433,"score_spread":0.24820837849885688,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2111552019","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9934692,0.000070186274,0.0024909426,0.0003839192,0.0010926988,0.00028075537,0.000036761245,0.00010119048,0.0020743525],"genre_scores_gemma":[0.9975637,0.000010146795,0.0011196008,0.0002693844,0.00010679856,0.00001778085,0.0000057679144,0.000014233196,0.0008925757],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9954203,0.00026099628,0.0010201181,0.0010799776,0.0015099867,0.0007086344],"domain_scores_gemma":[0.9960346,0.0023484793,0.00046161874,0.00058379583,0.00021403238,0.00035742705],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.011769507,0.00034130376,0.00047934148,0.0006815123,0.0013256189,0.0014131474,0.00095107016,0.00018213059,0.000187765],"category_scores_gemma":[0.0007978555,0.00023119117,0.00010840644,0.0011468484,0.0009359603,0.0011265058,0.00023628048,0.00031855193,0.00020511595],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011880907,0.00022171818,0.22896443,0.0000034798438,0.0000032268701,0.00003851552,0.0015974735,0.00042195688,0.0012693894,0.002885019,0.0007416161,0.76373434],"study_design_scores_gemma":[0.0021971539,0.005966846,0.8739373,0.00065963325,0.000110225745,0.00065498974,0.031828307,0.024461845,0.0009985429,0.034013536,0.022386678,0.0027849427],"about_ca_topic_score_codex":0.000112009875,"about_ca_topic_score_gemma":0.00019398321,"teacher_disagreement_score":0.76094943,"about_ca_system_score_codex":0.000056447294,"about_ca_system_score_gemma":0.00014091635,"threshold_uncertainty_score":0.99997455},"labels":[],"label_agreement":null},{"id":"W2112678505","doi":"10.1111/j.1559-1816.2001.tb01415.x","title":"The Empathy‐Prospect Model and the Choice to Help<sup>1</sup>","year":2001,"lang":"en","type":"article","venue":"Journal of Applied Social Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Empathy; Prosocial behavior; Feeling; Psychology; Perception; Social psychology; Altruism (biology); Helping behavior; Cognition","score_opus":0.11608720858065628,"score_gpt":0.43788287877377774,"score_spread":0.32179567019312144,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2112678505","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9598949,0.00010391071,0.0017650457,0.020697404,0.00048558105,0.00018861108,0.0000034829536,0.000008786947,0.01685226],"genre_scores_gemma":[0.9929597,0.0001161517,0.00056642864,0.005081958,0.0008303674,0.000007925483,1.1977173e-7,0.000014872477,0.00042252743],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9975097,0.0001412003,0.0010424852,0.00031201297,0.00066607393,0.000328535],"domain_scores_gemma":[0.9968639,0.0016844453,0.00064763176,0.0003955377,0.00026455766,0.00014394335],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005754045,0.00015808054,0.0005010632,0.00015400017,0.00075493957,0.0003911408,0.0012619819,0.00015804205,0.00005464272],"category_scores_gemma":[0.0006554742,0.00007801668,0.00022221668,0.00043887406,0.0004679702,0.00011507779,0.00014776536,0.00049834227,0.00014175657],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0026497091,0.00013376429,0.00078007404,4.6449566e-7,0.000048408307,0.000019798907,0.009676795,0.004462707,0.00014915095,0.015098943,0.08788536,0.87909484],"study_design_scores_gemma":[0.0029060422,0.00016649878,0.007861196,0.000004797117,0.00004400199,0.00016259917,0.005496213,0.0021509263,0.000005131231,0.8637902,0.11722025,0.00019210335],"about_ca_topic_score_codex":0.000005385149,"about_ca_topic_score_gemma":0.000030932497,"teacher_disagreement_score":0.87890273,"about_ca_system_score_codex":0.00004560756,"about_ca_system_score_gemma":0.00006690393,"threshold_uncertainty_score":0.5806461},"labels":[],"label_agreement":null},{"id":"W2112727590","doi":"10.1002/bdm.513","title":"Illusion of confirmation from exposure to another's hypothesis","year":2006,"lang":"en","type":"article","venue":"Journal of Behavioral Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; University of Waterloo","keywords":"Confidence interval; Point (geometry); Illusion; Psychology; Econometrics; Statistics; Social psychology; Mathematics; Cognitive psychology","score_opus":0.11590702150322214,"score_gpt":0.389568273463285,"score_spread":0.27366125196006286,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2112727590","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9671181,0.00018618842,0.030592723,0.00015197397,0.0014102267,0.0001661992,0.00006901558,0.000016385946,0.00028920788],"genre_scores_gemma":[0.93169063,0.0000075395915,0.067763485,0.00014419432,0.0002807183,0.0000017112778,0.0000012146629,0.000031714208,0.00007878085],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99301183,0.0002171278,0.003439423,0.0004536738,0.002574579,0.0003033851],"domain_scores_gemma":[0.9919792,0.0029595504,0.0026959265,0.0007984669,0.0014185345,0.0001483693],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0031948083,0.0002878992,0.00096349674,0.001301699,0.00016341837,0.00042062168,0.0013874213,0.00023167039,0.0012744907],"category_scores_gemma":[0.001366269,0.00021215892,0.00056923943,0.0009445983,0.00008034022,0.0008299098,0.00025501015,0.0002863942,0.0002230292],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045731093,0.00031782826,0.011554822,9.73052e-7,0.000006376143,0.00007064388,0.00032430008,0.0036687688,0.020927642,0.00003375002,0.006035322,0.9566023],"study_design_scores_gemma":[0.0034382779,0.0026434162,0.54421014,0.0017054195,0.00034912524,0.00030194293,0.0031626427,0.00093683397,0.013360791,0.39645076,0.032237515,0.001203135],"about_ca_topic_score_codex":0.00013825056,"about_ca_topic_score_gemma":0.00012002694,"teacher_disagreement_score":0.95539916,"about_ca_system_score_codex":0.0001577884,"about_ca_system_score_gemma":0.00011560004,"threshold_uncertainty_score":0.9996385},"labels":[],"label_agreement":null},{"id":"W2113250844","doi":"10.1016/j.cognition.2007.01.001","title":"Violations of coherence in subjective probability: A representational and assessment processes account","year":2007,"lang":"en","type":"article","venue":"Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":54,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada; University of Toronto","funders":"","keywords":"Psychology; Coherence (philosophical gambling strategy); Pessimism; Cognitive psychology; Cognition; Probability estimation; Social psychology; Statistics; Artificial intelligence; Mathematics; Computer science","score_opus":0.19095526049685368,"score_gpt":0.4616539005071716,"score_spread":0.2706986400103179,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2113250844","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9873157,0.000026416914,0.005811828,0.000088746434,0.00005644892,0.0002583781,0.000025861935,0.000009588547,0.0064070206],"genre_scores_gemma":[0.9962607,0.0000060515067,0.0036395963,0.000027319384,0.000014015742,0.000019439523,0.000011209957,0.0000030081412,0.000018683102],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986274,0.000048172355,0.0005202166,0.00030313426,0.0004028623,0.00009817396],"domain_scores_gemma":[0.99719846,0.0016998363,0.00022633128,0.0001454295,0.0006939935,0.000035957553],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002061501,0.00006306678,0.0001416349,0.00023625208,0.00005582205,0.00007966002,0.0001096939,0.000047260568,0.00009868801],"category_scores_gemma":[0.0023916464,0.000053343818,0.000022365468,0.0005868104,0.00010338415,0.00040516708,0.000047777583,0.00008478582,0.000011472017],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000094324394,0.00030389708,0.50484526,0.000014065522,0.0000044232793,0.000004286204,0.00061327923,0.000066416476,0.0012675156,0.00052248355,0.00004237914,0.49222168],"study_design_scores_gemma":[0.00019608541,0.00004718484,0.6121703,0.00004103208,0.0000066026964,0.0000047468707,0.0009280905,0.00022723075,0.0015823402,0.3846514,0.00008504303,0.000059988903],"about_ca_topic_score_codex":0.000025473957,"about_ca_topic_score_gemma":0.00060456624,"teacher_disagreement_score":0.4921617,"about_ca_system_score_codex":0.000048493464,"about_ca_system_score_gemma":0.00017519806,"threshold_uncertainty_score":0.28631967},"labels":[],"label_agreement":null},{"id":"W2113496801","doi":"10.2139/ssrn.2638669","title":"Measuring Economic Inequality and Risk: A Unifying Approach Based on Personal Gambles, Societal Preferences and References","year":2015,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Inequality; Economic inequality; Economics; Econometrics; Actuarial science; Mathematical economics; Mathematics","score_opus":0.2664098658438554,"score_gpt":0.3701803614205095,"score_spread":0.10377049557665408,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2113496801","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99476194,0.0011965992,0.0022253257,0.00020168608,0.00019680565,0.00009297173,0.000016160946,0.000023000415,0.0012855156],"genre_scores_gemma":[0.9978018,0.00081100716,0.0010624868,0.000047083715,0.0001559305,0.00000402672,0.0000022380834,0.000013904758,0.00010153119],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99634105,0.00046095406,0.0006891245,0.00062987034,0.0007700338,0.001108982],"domain_scores_gemma":[0.9981443,0.00057832117,0.0005552229,0.00024775788,0.00018500838,0.00028934397],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.016157553,0.00024735634,0.00042344205,0.00026267662,0.00045880434,0.0007747535,0.00050895754,0.00013411972,0.000023182047],"category_scores_gemma":[0.00102971,0.00017650037,0.0001098761,0.00015325041,0.00017459695,0.0005169593,0.000110271416,0.0014519595,0.00002912244],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002728802,0.00011425929,0.22744392,0.000003986271,0.00006580268,0.0000024505603,0.0011180568,0.0010953404,0.00001032262,0.0029103225,0.00022567323,0.766737],"study_design_scores_gemma":[0.0022619504,0.0012173163,0.026094176,0.00005715355,0.00009491882,0.00036305183,0.02853174,0.053874593,0.0000201045,0.8860409,0.0007920795,0.00065196515],"about_ca_topic_score_codex":0.00026385352,"about_ca_topic_score_gemma":0.0010977711,"teacher_disagreement_score":0.8831306,"about_ca_system_score_codex":0.0006328471,"about_ca_system_score_gemma":0.002371132,"threshold_uncertainty_score":0.7470966},"labels":[],"label_agreement":null},{"id":"W2113560343","doi":"10.1080/00048402.2010.510529","title":"Representation Theorems and the Foundations of Decision Theory","year":2010,"lang":"en","type":"article","venue":"Australasian Journal of Philosophy","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":113,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Representation (politics); Rationality; Decision theory; Probabilistic logic; Mathematical economics; Epistemology; Expected utility hypothesis; Subjective expected utility; Representation theorem; Computer science; Mathematics; Philosophy; Discrete mathematics; Political science; Law","score_opus":0.0836085933280365,"score_gpt":0.40021478422964296,"score_spread":0.31660619090160647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2113560343","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98625433,0.000040534298,0.004005253,0.0035192939,0.0011158223,0.00010606859,0.0000067648293,0.000004025857,0.0049479045],"genre_scores_gemma":[0.9960957,0.000018301515,0.0034380401,0.00006720929,0.00030179514,9.891867e-7,4.6502169e-7,0.000008595047,0.00006888172],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9974814,0.0002643683,0.0012165568,0.0001930964,0.00072673266,0.00011782532],"domain_scores_gemma":[0.99321836,0.0044161878,0.0011911144,0.0005301613,0.00053229736,0.000111865775],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006447591,0.00011355959,0.0003837645,0.0003432472,0.00015370005,0.00021665591,0.0007879222,0.00008504723,0.00037425893],"category_scores_gemma":[0.00489012,0.000059938127,0.00027198787,0.00041814047,0.00079186814,0.0005532976,0.000083235864,0.00040877017,0.00003223158],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006703148,0.000089754954,0.005519615,0.0000014100242,0.000034731627,0.000016699907,0.0009373213,0.00008888049,0.0017603944,0.37855205,0.0007289393,0.61159986],"study_design_scores_gemma":[0.0010072094,0.000098252836,0.007454076,0.00002638797,0.00004249744,0.0002622072,0.0004883289,0.000047926776,0.00047369665,0.9892653,0.00077261595,0.0000614714],"about_ca_topic_score_codex":0.0000029935043,"about_ca_topic_score_gemma":0.0000057828024,"teacher_disagreement_score":0.6115384,"about_ca_system_score_codex":0.0000086558075,"about_ca_system_score_gemma":0.00006474552,"threshold_uncertainty_score":0.58542836},"labels":[],"label_agreement":null},{"id":"W2114216861","doi":"10.3982/te1004","title":"Scale-invariant uncertainty-averse preferences and source-dependent constant relative risk aversion","year":2013,"lang":"en","type":"article","venue":"Theoretical Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Ambiguity aversion; Axiom; Expected utility hypothesis; Ambiguity; Mathematical economics; Roulette; Risk aversion (psychology); Econometrics; Mathematics; Axiom independence; Von Neumann–Morgenstern utility theorem; Invariant (physics); Independence (probability theory); Economics; Statistics; Computer science","score_opus":0.03511651380158333,"score_gpt":0.29478637426369403,"score_spread":0.2596698604621107,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2114216861","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9782707,0.000025905993,0.003859646,0.0008380441,0.00039807978,0.00036528517,0.00009496313,0.00006124247,0.016086124],"genre_scores_gemma":[0.9973393,0.00021735646,0.0016199187,0.00026943992,0.00006796124,0.000015227341,0.0000049849045,0.000023784376,0.00044200415],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99685824,0.00037580132,0.0010484299,0.00093641103,0.00032038192,0.0004607641],"domain_scores_gemma":[0.9945338,0.0035766433,0.000485743,0.00076052087,0.00019831971,0.00044501355],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002749435,0.00031106267,0.0006095966,0.00022166599,0.00034355666,0.0007413714,0.0007257551,0.0002576203,0.0058640824],"category_scores_gemma":[0.001620045,0.00020313288,0.000169865,0.00014448736,0.0017001416,0.00067846617,0.0005183905,0.00042489698,0.0037229343],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000216298,0.00012896355,0.007561045,0.0000024744631,0.00004744737,0.0000057362213,0.0012582765,0.0016794394,0.000052686006,0.34163162,0.00078007655,0.64663595],"study_design_scores_gemma":[0.00062237016,0.00018242194,0.0013428,0.00002082951,0.00005271941,0.000024154095,0.0028807682,0.039515592,0.000100800025,0.953011,0.0019041034,0.00034248605],"about_ca_topic_score_codex":0.00019820925,"about_ca_topic_score_gemma":0.000072291106,"teacher_disagreement_score":0.64629346,"about_ca_system_score_codex":0.0001481928,"about_ca_system_score_gemma":0.00010693646,"threshold_uncertainty_score":0.9970528},"labels":[],"label_agreement":null},{"id":"W2114305661","doi":"10.1017/s0140525x0700266x","title":"Differential focus in causal and counterfactual thinking: Different possibilities or different functions?","year":2007,"lang":"en","type":"article","venue":"Behavioral and Brain Sciences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Counterfactual thinking; Focus (optics); Psychology; Epistemology; Cognitive psychology; Regulatory focus theory; Causal model; Counterfactual conditional; Cognition; Dissociation (chemistry); Social psychology; Mathematics; Philosophy","score_opus":0.1656313752524876,"score_gpt":0.41395941221895094,"score_spread":0.24832803696646333,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2114305661","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99705315,0.00013450373,0.0006330801,0.00074969477,0.00091033144,0.00024587804,0.000049556496,0.000049419134,0.00017441108],"genre_scores_gemma":[0.998266,0.0000159481,0.00013315778,0.00012733586,0.00009957937,0.000009732915,0.0000034226932,0.000010879068,0.0013339524],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9958346,0.0001379172,0.0010249132,0.0010818059,0.0012840054,0.00063674623],"domain_scores_gemma":[0.99710906,0.0019270371,0.00024297519,0.00034866083,0.00009241387,0.00027982937],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.002389088,0.0003614889,0.0005761079,0.0006356111,0.00070765364,0.0013990712,0.00067472254,0.00016524618,0.00058380386],"category_scores_gemma":[0.00040500012,0.0001973863,0.00009818036,0.0005262268,0.0011826872,0.0006620577,0.00045900772,0.00027792095,0.000018675277],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027721524,0.00049055676,0.46698248,0.0000038293692,0.0000036782753,0.000046163615,0.003090185,0.000002944166,0.0014642336,0.00053517084,0.0006027839,0.52650076],"study_design_scores_gemma":[0.0012606883,0.001605109,0.9238066,0.00008236315,0.00003366056,0.00011524165,0.016490605,0.0003854457,0.0011197304,0.053619675,0.00082063396,0.0006602206],"about_ca_topic_score_codex":0.00060289056,"about_ca_topic_score_gemma":0.00785126,"teacher_disagreement_score":0.5258405,"about_ca_system_score_codex":0.00007959515,"about_ca_system_score_gemma":0.00007240796,"threshold_uncertainty_score":0.99963754},"labels":[],"label_agreement":null},{"id":"W2114531238","doi":"10.1016/j.obhdp.2012.02.002","title":"Self-selection bias in hypothesis comparison","year":2012,"lang":"en","type":"article","venue":"Organizational Behavior and Human Decision Processes","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Psychology; Cognition; Selection (genetic algorithm); Task (project management); Cognitive psychology; Statistical hypothesis testing; Probabilistic logic; Social psychology; Confirmation bias; Cognitive bias; Statistics; Artificial intelligence; Computer science; Mathematics; Neuroscience","score_opus":0.17833366672650422,"score_gpt":0.40100230785089935,"score_spread":0.22266864112439513,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2114531238","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99759275,0.0003294004,0.00077763246,0.00005049941,0.0002726814,0.00021921897,0.000014294565,0.00009357627,0.0006499374],"genre_scores_gemma":[0.9933667,0.000039933173,0.006011667,0.000081409584,0.00014544718,0.000026474716,0.00001353626,0.00003690089,0.0002778931],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99670225,0.000095376956,0.0011512267,0.00058288546,0.0011035987,0.0003646855],"domain_scores_gemma":[0.9964789,0.0018606393,0.00035947745,0.00030442106,0.0007680825,0.00022847048],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0016514505,0.00025380673,0.0004426626,0.0007781737,0.0004603325,0.000572198,0.0004979537,0.00017952647,0.0019699344],"category_scores_gemma":[0.003513597,0.00020681591,0.0000537152,0.0018875906,0.000078347555,0.0010877762,0.00017604645,0.00019297756,0.00047935566],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015550953,0.0007006108,0.9210647,0.0000056917984,0.0000026086454,0.0000017658134,0.00047485478,0.000014880421,0.00019147119,0.0009405036,0.0010462686,0.07554109],"study_design_scores_gemma":[0.000594734,0.000098521654,0.94825315,0.000044674838,0.000055448145,0.000059399965,0.00053047115,0.00005724119,0.0015846543,0.03659551,0.011687463,0.0004387557],"about_ca_topic_score_codex":0.000014272645,"about_ca_topic_score_gemma":0.00014884728,"teacher_disagreement_score":0.07510234,"about_ca_system_score_codex":0.00010707804,"about_ca_system_score_gemma":0.00013068756,"threshold_uncertainty_score":0.9989424},"labels":[],"label_agreement":null},{"id":"W2114806482","doi":"10.1037/0278-7393.33.3.461","title":"Aspects of endowment: A query theory of value construction.","year":2007,"lang":"en","type":"article","venue":"Journal of Experimental Psychology Learning Memory and Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":121,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Endowment effect; Order (exchange); Endowment; Value (mathematics); Loss aversion; Economics; Prospect theory; Microeconomics; Construct (python library); Object (grammar); Weighting; Computer science; Mathematics; Finance; Statistics","score_opus":0.08478900968525906,"score_gpt":0.41962833663782756,"score_spread":0.3348393269525685,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2114806482","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9678485,0.0008384246,0.003045728,0.00004409066,0.0006935399,0.000059115504,0.0000020658972,0.000005079571,0.027463472],"genre_scores_gemma":[0.99829,0.00004074499,0.0014242436,0.000114396746,0.00007838116,5.874084e-7,8.634723e-7,0.0000068731692,0.00004390681],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9978941,0.00031488316,0.0010830153,0.0001940476,0.00038408564,0.00012983163],"domain_scores_gemma":[0.99726874,0.0008808574,0.0013703846,0.00012954576,0.000268287,0.00008221472],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0041851737,0.00010428816,0.0003670827,0.0004360309,0.00008865349,0.000023110753,0.00017748032,0.000108453205,0.0003683525],"category_scores_gemma":[0.0005694794,0.000083595514,0.00015104192,0.00018949283,0.00041411887,0.00026475437,0.0000380275,0.000284868,0.000010321329],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024107369,0.0006525355,0.0036412943,0.000005366036,0.000083364335,0.00010060992,0.0018673337,0.00007395341,0.432116,0.0063624713,0.0001318993,0.5525544],"study_design_scores_gemma":[0.0044920403,0.0037153086,0.01869211,0.00024760482,0.00012382078,0.0044915224,0.043924488,0.00002321702,0.540952,0.38221064,0.00083967834,0.0002875625],"about_ca_topic_score_codex":0.0000017368699,"about_ca_topic_score_gemma":4.966328e-7,"teacher_disagreement_score":0.5522669,"about_ca_system_score_codex":0.000019224246,"about_ca_system_score_gemma":0.000032774416,"threshold_uncertainty_score":0.4033202},"labels":[],"label_agreement":null},{"id":"W2115168001","doi":"10.2139/ssrn.624221","title":"Subjective Recursive Expected Utility","year":2004,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Computer science; Mathematics; Econometrics; Psychology","score_opus":0.06567386177020151,"score_gpt":0.37031190815135184,"score_spread":0.30463804638115033,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2115168001","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97464436,0.0006289174,0.020010613,0.0009128729,0.00075623457,0.00011494858,0.0000061861074,0.00004240054,0.0028834473],"genre_scores_gemma":[0.9984157,0.00026101703,0.0003980198,0.00010463958,0.00022764958,0.0000033067327,0.0000012862994,0.000017864697,0.00057051016],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9955599,0.00019563989,0.0007993418,0.0005415145,0.00092821004,0.0019754027],"domain_scores_gemma":[0.9978724,0.00039252624,0.00047230776,0.0005361371,0.0005405568,0.00018607416],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0061637843,0.00020985796,0.0003685345,0.0003441431,0.00043532875,0.000359833,0.001064043,0.00013400463,0.0002623714],"category_scores_gemma":[0.0021600253,0.00015673359,0.00030533056,0.0007207273,0.00012638913,0.00057533634,0.00009937473,0.0018783879,0.00076108903],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026535933,0.0002759559,0.005953936,3.2938414e-7,0.00006834829,0.000034546094,0.0010135886,0.00022277149,0.00015312008,0.05701287,0.00032990857,0.93466926],"study_design_scores_gemma":[0.000754083,0.00032828347,0.0046754368,0.00001093164,0.000016132228,0.0006187728,0.006605059,0.000013702493,0.00022586738,0.98456025,0.0020013456,0.00019015226],"about_ca_topic_score_codex":0.00010398854,"about_ca_topic_score_gemma":0.0013578647,"teacher_disagreement_score":0.9344791,"about_ca_system_score_codex":0.0017442992,"about_ca_system_score_gemma":0.0033393123,"threshold_uncertainty_score":0.9782514},"labels":[],"label_agreement":null},{"id":"W2115836035","doi":"10.1111/j.1469-8986.2007.00567.x","title":"It's worse than you thought: The feedback negativity and violations of reward prediction in gambling tasks","year":2007,"lang":"en","type":"article","venue":"Psychophysiology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":523,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"National Institute of Mental Health","keywords":"Psychology; Negativity effect; Task (project management); Outcome (game theory); Reinforcement; Cognitive psychology; Developmental psychology; Social psychology","score_opus":0.12466451589500914,"score_gpt":0.42014955670084964,"score_spread":0.2954850408058405,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2115836035","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9939319,0.000057454283,0.0016241451,0.000994407,0.0008898188,0.00016861211,0.000024360881,0.000016593065,0.0022927066],"genre_scores_gemma":[0.9986014,0.0000359206,0.000822071,0.00020886355,0.00013866623,0.0000061390647,0.0000039222236,0.000008039321,0.0001750073],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.998078,0.00019141728,0.00077636604,0.00045159433,0.00025733397,0.00024530603],"domain_scores_gemma":[0.9971576,0.0017494682,0.00033088587,0.0005763714,0.0001233613,0.00006232592],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028647766,0.0001264284,0.00030846614,0.00029427253,0.00013236552,0.000049737628,0.000396872,0.00014233895,0.00008002455],"category_scores_gemma":[0.00083465345,0.00008144098,0.00008883203,0.00072865264,0.0002547654,0.00024018377,0.00010238846,0.00024148013,0.00007016622],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00078650296,0.00039269374,0.1950803,0.0000055997566,0.00002187041,0.000006307307,0.0031139962,0.0012971909,0.054603297,0.00047646422,0.0051103677,0.7391054],"study_design_scores_gemma":[0.00060487865,0.00017724131,0.86410457,0.000035396235,0.000012572978,0.000009749425,0.0016147662,0.0016919544,0.0005783781,0.124311335,0.0067143603,0.0001448273],"about_ca_topic_score_codex":0.00009400675,"about_ca_topic_score_gemma":0.0004181046,"teacher_disagreement_score":0.7389606,"about_ca_system_score_codex":0.000024698697,"about_ca_system_score_gemma":0.00003179233,"threshold_uncertainty_score":0.33210668},"labels":[],"label_agreement":null},{"id":"W2115857808","doi":"10.1037/a0030174","title":"Risk preferences and aging: The “certainty effect” in older adults' decision making.","year":2012,"lang":"en","type":"article","venue":"Psychology and Aging","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"National Institute on Aging; National Institutes of Health","keywords":"Certainty; Risk-seeking; Loss aversion; Risk aversion (psychology); Psychology; Prospect theory; Stereotype threat; Health and Retirement Study; Demography; Social psychology; Gerontology; Expected utility hypothesis; Economics; Medicine; Microeconomics; Financial economics","score_opus":0.05324072154479669,"score_gpt":0.4166853287893815,"score_spread":0.3634446072445848,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2115857808","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99354774,0.0027471487,0.00070882344,0.0010140052,0.00087180553,0.00017776307,0.0000041277403,0.000022259335,0.00090633903],"genre_scores_gemma":[0.99820733,0.00023119831,0.00053727854,0.0008501039,0.00012063019,0.000013971138,5.853796e-7,0.000008917976,0.000030003019],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9978924,0.00043038238,0.000484601,0.00055361004,0.00025004853,0.00038898148],"domain_scores_gemma":[0.99507296,0.00411167,0.00022283205,0.00045823152,0.00003840668,0.00009589649],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0050432193,0.00018049925,0.00030500922,0.00025388636,0.00030505485,0.00019755475,0.0004232446,0.00013410058,0.00013040434],"category_scores_gemma":[0.0010057619,0.00010110489,0.00005503267,0.0002907447,0.000221813,0.00032988592,0.00019961897,0.00038268502,0.00007920117],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004680246,0.000027331696,0.41268188,0.0000010721631,0.0000023522923,0.000002033375,0.0010500641,0.000003187748,0.0000045495685,0.000026593438,0.00038575366,0.5857684],"study_design_scores_gemma":[0.0007283098,0.000060719067,0.9419218,0.00012804609,0.000016290549,0.0000436439,0.00067873264,0.0003874322,0.000008404279,0.052871272,0.0029927948,0.00016257109],"about_ca_topic_score_codex":0.000048136004,"about_ca_topic_score_gemma":0.00010395705,"teacher_disagreement_score":0.5856058,"about_ca_system_score_codex":0.000010639451,"about_ca_system_score_gemma":0.0000069968896,"threshold_uncertainty_score":0.4122938},"labels":[],"label_agreement":null},{"id":"W2115917877","doi":"10.3389/fpsyg.2014.00901","title":"Reason and less","year":2014,"lang":"en","type":"article","venue":"Frontiers in Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; Wellcome Trust","keywords":"Rationality; Psychology; White (mutation); Voting; Presidential system; Population; Politics; Bounded rationality; Positive economics; Social psychology; Epistemology; Cognitive psychology; Sociology; Political science; Artificial intelligence; Economics; Computer science; Law","score_opus":0.10416157246143126,"score_gpt":0.42068676993338167,"score_spread":0.3165251974719504,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2115917877","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9099489,0.0003195155,0.06496321,0.0013003366,0.004191281,0.00005922928,0.000002618093,0.000019397467,0.019195516],"genre_scores_gemma":[0.9746833,0.000069187474,0.023706332,0.0011213445,0.000079294754,0.000005108632,9.837763e-7,0.000009644957,0.00032480867],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9984962,0.00018241892,0.00040262777,0.0005267077,0.0001832527,0.00020880572],"domain_scores_gemma":[0.998971,0.00025436882,0.00011346556,0.00054826814,0.000036345675,0.00007657501],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020516666,0.000093732975,0.00029683366,0.00035752857,0.000046831407,0.00007817964,0.0004764756,0.0001404238,0.00006412784],"category_scores_gemma":[0.0007338598,0.00007563574,0.000039492556,0.00027427645,0.00016075319,0.00011579747,0.000068758476,0.00014769362,0.000121154175],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024461731,0.000021250593,0.14170183,2.1509803e-7,0.0000010317112,0.0000031855716,0.000058672736,0.000002179012,0.0000075041003,0.0002186853,0.08144759,0.7765134],"study_design_scores_gemma":[0.00050783204,0.00007425766,0.083498456,0.000006419694,0.000002716193,0.00002150528,0.0002768379,0.0009948681,0.0000051876964,0.61819834,0.29629713,0.00011643407],"about_ca_topic_score_codex":0.000010572755,"about_ca_topic_score_gemma":0.00002574749,"teacher_disagreement_score":0.776397,"about_ca_system_score_codex":0.000015147969,"about_ca_system_score_gemma":0.0000082708275,"threshold_uncertainty_score":0.3084336},"labels":[],"label_agreement":null},{"id":"W2118335134","doi":"10.1007/s10797-006-6665-4","title":"Estimates of Own Lethal Risks and Anchoring Effects","year":2006,"lang":"en","type":"article","venue":"Journal of Risk and Uncertainty","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Anchoring; Cohort; Population; Psychology; Cohort effect; Actuarial science; Demography; Social psychology; Economics; Medicine; Sociology","score_opus":0.06492304748172943,"score_gpt":0.3714043440293516,"score_spread":0.30648129654762213,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2118335134","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99627554,0.0013756347,0.0016435743,0.000059962164,0.00034543627,0.000040115214,0.000010356948,0.000004066561,0.00024533743],"genre_scores_gemma":[0.99572116,0.00022985456,0.0038449029,0.000009609956,0.00016898621,3.193668e-7,2.4332618e-7,0.000005425237,0.000019492183],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99842995,0.000087788816,0.00075155,0.00017447786,0.0004135186,0.00014270129],"domain_scores_gemma":[0.9960296,0.002593836,0.00087617,0.00015993648,0.00024271416,0.000097728305],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022013956,0.00011425962,0.00044666804,0.0002311762,0.00011136637,0.00015444194,0.00020949231,0.000070110545,0.000018785722],"category_scores_gemma":[0.0016627093,0.000070621645,0.0001141969,0.00016084836,0.00013474951,0.0002462281,0.00006749804,0.00020608798,0.000002748667],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000082886974,0.00004853988,0.27205133,0.000005010724,0.000008880962,0.000031076688,0.0001391453,0.0022382925,0.0004277062,0.00012309178,0.0009078568,0.7239362],"study_design_scores_gemma":[0.0015816868,0.00055909675,0.6213027,0.00018827817,0.00013737274,0.00026912952,0.0005106009,0.004547395,0.0018214257,0.3638815,0.0049676867,0.00023306996],"about_ca_topic_score_codex":0.0003457972,"about_ca_topic_score_gemma":0.000046917252,"teacher_disagreement_score":0.72370315,"about_ca_system_score_codex":0.000020047843,"about_ca_system_score_gemma":0.000035523964,"threshold_uncertainty_score":0.2879867},"labels":[],"label_agreement":null},{"id":"W2118465430","doi":"10.1002/0471264385.wei0423","title":"Reasoning and Problem Solving","year":2003,"lang":"en","type":"other","venue":"Handbook of Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Frame problem; Adaptive reasoning; Task (project management); Frame (networking); Action (physics); Cognitive science; Computer science; Connectionism; Qualitative reasoning; Psychology of reasoning; Process (computing); Analytic reasoning; Artificial intelligence; Model-based reasoning; Selection (genetic algorithm); Reasoning system; Multitude; Knowledge representation and reasoning; Epistemology; Management science; Psychology; Artificial neural network","score_opus":0.10651294004741624,"score_gpt":0.4301755355521594,"score_spread":0.3236625955047432,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2118465430","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0015571772,0.009471175,0.004450768,0.000089069006,0.001149582,0.0002083518,0.000026236756,0.000054362477,0.9829933],"genre_scores_gemma":[0.001691664,0.0025605035,0.10354445,0.00086720905,0.00029055268,0.000018103867,0.000007457591,0.00043274733,0.89058733],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9978859,0.0001381645,0.0006649964,0.0007422512,0.00031573008,0.0002529683],"domain_scores_gemma":[0.9980561,0.00027245985,0.0007338263,0.0007748309,0.00006764221,0.00009509759],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0011649183,0.0002264256,0.0006712161,0.00059545005,0.000046389825,0.00007165431,0.00050941703,0.0004453444,0.0058173505],"category_scores_gemma":[0.0003510803,0.00018058687,0.0001094743,0.00017240173,0.0002588067,0.00004640676,0.00009856925,0.0002092396,0.00048244672],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010522961,0.000030961815,0.0006420275,0.0000047909566,0.000012773296,0.000009265875,0.000060442264,4.3578143e-7,0.00010304625,0.00019058096,0.732739,0.26619616],"study_design_scores_gemma":[0.00041066582,0.00010128963,0.0001286983,0.00044530895,0.00002208045,0.00007011094,0.000036231406,0.000006002404,0.000033137465,0.035208024,0.9633199,0.00021855203],"about_ca_topic_score_codex":0.000027574082,"about_ca_topic_score_gemma":0.00007367038,"teacher_disagreement_score":0.26597762,"about_ca_system_score_codex":0.000010982861,"about_ca_system_score_gemma":0.00004247783,"threshold_uncertainty_score":0.99509144},"labels":[],"label_agreement":null},{"id":"W2121642162","doi":"10.1521/soco.2015.33.2.104","title":"When Mona Lisa Smiled and Love was in the Air: On the Cognitive Energetics of Motivated Judgments","year":2015,"lang":"en","type":"article","venue":"Social Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Psychology; Task (project management); Wishful thinking; Cognition; Cognitive psychology; Cognitive bias; Social psychology; Cognitive resource theory","score_opus":0.25258708067792485,"score_gpt":0.3935508150183149,"score_spread":0.14096373434039006,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121642162","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9824578,0.000025345682,0.0000545789,0.0020464489,0.0001501473,0.0002509947,0.00007309672,0.0000076521665,0.014933939],"genre_scores_gemma":[0.9989675,0.000007808911,0.000024197596,0.000780267,0.00006771976,0.000009398473,0.000014820701,0.000007336709,0.00012092861],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99809104,0.000420981,0.00040106365,0.00023708766,0.0007054991,0.00014429943],"domain_scores_gemma":[0.9974076,0.0017988323,0.0002398214,0.0001325941,0.00038086114,0.000040292864],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002242679,0.000110026485,0.00019565874,0.00011004211,0.00011269027,0.0001047225,0.0002738989,0.00008332823,0.00010320183],"category_scores_gemma":[0.0023619542,0.000062392675,0.0000613184,0.0003071053,0.00020696889,0.00013948418,0.00007421037,0.00016819262,0.0001496953],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002754544,0.0026431498,0.018669754,0.000011495372,0.00013111571,0.000052604868,0.10465726,0.00008412789,0.0018111928,0.0070260037,0.064303085,0.7978557],"study_design_scores_gemma":[0.0026275066,0.00074496807,0.03414004,0.00012452045,0.00010339519,0.000003958117,0.064723425,0.00042928703,0.0030496076,0.8921589,0.0015948857,0.00029949224],"about_ca_topic_score_codex":0.000052689305,"about_ca_topic_score_gemma":0.00007113719,"teacher_disagreement_score":0.8851329,"about_ca_system_score_codex":0.000033803564,"about_ca_system_score_gemma":0.000051358624,"threshold_uncertainty_score":0.28276503},"labels":[],"label_agreement":null},{"id":"W2122152276","doi":"10.1016/j.jet.2011.06.015","title":"Nonmanipulable Bayesian testing","year":2011,"lang":"en","type":"article","venue":"Journal of Economic Theory","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Contrast (vision); Probabilistic logic; Bayesian probability; Computer science; Set (abstract data type); Process (computing); Test (biology); Machine learning; Econometrics; Artificial intelligence; Mathematics","score_opus":0.338175378747531,"score_gpt":0.3873039713669915,"score_spread":0.04912859261946051,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2122152276","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9315288,0.00009106947,0.0039266706,0.00004897862,0.0017540548,0.00004057412,0.000003925957,0.000010891292,0.062595055],"genre_scores_gemma":[0.9878981,0.000005067508,0.010642753,0.00014074787,0.00029009787,4.8928575e-7,9.092932e-8,0.0000166175,0.0010060308],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99777937,0.00015771508,0.0014166391,0.0002321458,0.00019268338,0.00022143367],"domain_scores_gemma":[0.99616086,0.0016701809,0.0013476154,0.00045716955,0.00018743587,0.00017670823],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.007860591,0.00013300768,0.00043252003,0.00038696206,0.00010166915,0.00017879203,0.0011042355,0.00007785771,0.0039470717],"category_scores_gemma":[0.0018207998,0.0000978184,0.00023705629,0.000120504956,0.00008930123,0.00072733656,0.00011263423,0.00021945949,0.0012606299],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022970262,0.00014516196,0.033114195,0.0000015782883,0.000047298032,0.0001201657,0.0010418025,0.0006831456,0.0002740514,0.02241729,0.0064292876,0.93549633],"study_design_scores_gemma":[0.00034488644,0.00019193174,0.0046882615,0.000026830527,0.00002530345,0.00037166933,0.0009836335,0.00063268194,0.00045771012,0.9867374,0.0053780284,0.00016167696],"about_ca_topic_score_codex":0.000014679106,"about_ca_topic_score_gemma":0.000010492422,"teacher_disagreement_score":0.9643201,"about_ca_system_score_codex":0.00011928883,"about_ca_system_score_gemma":0.00018322778,"threshold_uncertainty_score":0.999517},"labels":[],"label_agreement":null},{"id":"W2122638098","doi":"10.1901/jeab.2009.92-1","title":"PROBABILITY DISCOUNTING OF GAINS AND LOSSES: IMPLICATIONS FOR RISK ATTITUDES AND IMPULSIVITY","year":2009,"lang":"en","type":"article","venue":"Journal of the Experimental Analysis of Behavior","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":110,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Discounting; Impulsivity; Delay discounting; Outcome (game theory); Psychology; Lottery; Econometrics; Social psychology; Economics; Statistics; Mathematics; Developmental psychology; Microeconomics","score_opus":0.14131423609438767,"score_gpt":0.45455641499429633,"score_spread":0.3132421788999087,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2122638098","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9987078,0.00034122053,0.00034171485,0.0002680312,0.0000618182,0.00017114583,0.00009565659,0.0000017658498,0.000010878291],"genre_scores_gemma":[0.9971453,0.000019050221,0.0027796915,0.000016820757,0.000019065023,0.000003906495,7.150279e-7,0.0000035356984,0.000011900177],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99805856,0.00009113695,0.0011498008,0.0002229262,0.00036840292,0.00010916074],"domain_scores_gemma":[0.99688727,0.00045956057,0.0018129924,0.00041812714,0.00034754738,0.00007453318],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018717289,0.00011118465,0.0006095442,0.00029348573,0.00016795417,0.000100088204,0.00048692833,0.000046169775,0.000017904455],"category_scores_gemma":[0.00053224445,0.00006455777,0.00055090047,0.0005117468,0.00023452331,0.00031908424,0.0001247432,0.000103548424,1.4973251e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000059683225,0.0008105731,0.88445663,0.000002045824,0.00011281036,2.7700688e-7,0.00044657997,0.00016386072,0.05455911,0.000098392775,0.000040300463,0.059249755],"study_design_scores_gemma":[0.00027195213,0.00024900888,0.97979975,0.000017515425,0.001120156,0.0000096043295,0.0008223043,0.00018732165,0.011698142,0.005735765,0.000012809953,0.00007566309],"about_ca_topic_score_codex":0.000044657798,"about_ca_topic_score_gemma":0.000047661746,"teacher_disagreement_score":0.09534315,"about_ca_system_score_codex":0.000047172867,"about_ca_system_score_gemma":0.000038906997,"threshold_uncertainty_score":0.26325893},"labels":[],"label_agreement":null},{"id":"W2123099414","doi":"10.3758/s13421-012-0268-3","title":"Probability matching in risky choice: The interplay of feedback and strategy availability","year":2012,"lang":"en","type":"article","venue":"Memory & Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":31,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Matching (statistics); Outcome (game theory); Task (project management); Psychology; Identification (biology); Cognitive psychology; Computer science; Microeconomics; Statistics; Economics; Mathematics","score_opus":0.13777961351072648,"score_gpt":0.39391203129597024,"score_spread":0.25613241778524376,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2123099414","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9948543,0.00009105331,0.00011165723,0.000135016,0.00024754586,0.0002949306,0.00002400841,0.000014424441,0.0042271004],"genre_scores_gemma":[0.99957734,0.0000056019335,0.00020679376,0.00006356086,0.000052751526,0.000013918679,0.0000035460578,0.0000061025075,0.000070404734],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99799424,0.0003534989,0.00072987407,0.00033158442,0.00037471615,0.00021609249],"domain_scores_gemma":[0.9973863,0.0016616745,0.0002769856,0.00044137126,0.00016079262,0.000072902796],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0060225,0.00011933851,0.00025586647,0.000109607245,0.0000973907,0.00012317534,0.00028634394,0.00008233168,0.00046396],"category_scores_gemma":[0.001655504,0.00007601436,0.00007015568,0.0002810156,0.00022831552,0.0006286483,0.0001371967,0.0002178846,0.00013846038],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010069156,0.0003890074,0.15908489,0.000017362721,0.000005464486,7.940251e-7,0.0018121322,0.0000869645,0.0016225909,0.000050936866,0.00038624255,0.83644295],"study_design_scores_gemma":[0.00044758376,0.000073089985,0.86357725,0.000057772082,0.000024340627,0.000011532452,0.0028409928,0.0002498597,0.0013660855,0.13063347,0.0005563692,0.00016165512],"about_ca_topic_score_codex":0.00016356974,"about_ca_topic_score_gemma":0.00042339633,"teacher_disagreement_score":0.83628124,"about_ca_system_score_codex":0.00004610285,"about_ca_system_score_gemma":0.000035275538,"threshold_uncertainty_score":0.50800365},"labels":[],"label_agreement":null},{"id":"W2124287106","doi":"10.1027/1618-3169.56.2.112","title":"An Inverse Belief–Bias Effect","year":2009,"lang":"en","type":"article","venue":"Experimental Psychology (formerly Zeitschrift für Experimentelle Psychologie)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Modus ponens; Premises; Inference; Rule of inference; Psychology; Causal inference; Social psychology; Cognitive psychology; Artificial intelligence; Computer science; Mathematics; Econometrics; Law","score_opus":0.1725170874408676,"score_gpt":0.5215509119877515,"score_spread":0.3490338245468839,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2124287106","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8798895,0.0016888415,0.0009659577,0.0010469571,0.004878951,0.0010054661,0.000028931556,0.0006063664,0.109889016],"genre_scores_gemma":[0.98368955,0.00007127117,0.004711408,0.009918322,0.00049583893,0.00015095477,0.000060856757,0.000104288665,0.000797515],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.98924714,0.001172483,0.0026129193,0.0035005747,0.0017090255,0.0017578515],"domain_scores_gemma":[0.9927248,0.00076567184,0.0009468882,0.0043322043,0.00023599969,0.0009944511],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0040863757,0.0012721268,0.0015993868,0.0011559802,0.0007993312,0.000768403,0.004246558,0.0009064236,0.006196365],"category_scores_gemma":[0.00057672174,0.0010177009,0.00083043554,0.0013234757,0.00080822647,0.0019251953,0.00025844853,0.0009889624,0.0090165045],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002785333,0.006024515,0.005549073,0.000001897573,0.00008456341,0.0002542911,0.0037155838,0.000061732426,0.3308718,0.0018194926,0.11903689,0.5297949],"study_design_scores_gemma":[0.018406166,0.056874335,0.026872143,0.00011217855,0.00010446889,0.0012308663,0.014249568,0.0007774138,0.4172343,0.016559899,0.44229788,0.0052807773],"about_ca_topic_score_codex":0.000038446844,"about_ca_topic_score_gemma":0.000007212783,"teacher_disagreement_score":0.5245141,"about_ca_system_score_codex":0.00009297793,"about_ca_system_score_gemma":0.000078786084,"threshold_uncertainty_score":0.99922734},"labels":[],"label_agreement":null},{"id":"W2126221177","doi":"10.1080/14622200412331320743","title":"The near-universal experience of regret among smokers in four countries: Findings from the International Tobacco Control Policy Evaluation Survey","year":2004,"lang":"en","type":"article","venue":"Nicotine & Tobacco Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":228,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Waterloo","funders":"Cancer Council Victoria; University of Illinois at Chicago; Centers for Disease Control and Prevention","keywords":"Regret; Tobacco control; Smoking cessation; Cohort; Survey data collection; Medicine; Psychology; Environmental health; Demography; Public health","score_opus":0.25058390600835545,"score_gpt":0.4783369772387701,"score_spread":0.22775307123041466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2126221177","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9893024,0.0000921359,0.000062822975,0.008557697,0.0005086857,0.0005768941,0.00013232962,0.000012736419,0.000754277],"genre_scores_gemma":[0.99920756,0.00006883622,0.00007427062,0.00019102824,0.00014140246,0.00003850898,0.000013478305,0.000015715092,0.00024920655],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99229556,0.0012181215,0.00094095274,0.00067329285,0.0042864447,0.00058561534],"domain_scores_gemma":[0.9831975,0.012943314,0.00034200193,0.0011660189,0.0022265273,0.00012465191],"candidate_categories":["metaresearch","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.027819347,0.00018000358,0.0003292797,0.00036460257,0.00062242325,0.0012767556,0.0035312565,0.00014809117,0.00057616015],"category_scores_gemma":[0.03231444,0.00010780256,0.00013555687,0.0016888718,0.0011174602,0.0006694012,0.0005509445,0.0006137933,0.00023216146],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029863996,0.000050981223,0.9474791,2.2307137e-7,0.000014586884,0.0000037623913,0.0017519639,0.0020521823,0.00006985849,0.0005151931,0.0031269193,0.044636536],"study_design_scores_gemma":[0.0019446039,0.00009499065,0.9746216,0.00005644885,0.0000057328793,0.0000020011696,0.004901096,0.0028240723,0.00022284375,0.0101384735,0.005049184,0.00013898613],"about_ca_topic_score_codex":0.030751523,"about_ca_topic_score_gemma":0.031584665,"teacher_disagreement_score":0.04449755,"about_ca_system_score_codex":0.00083543296,"about_ca_system_score_gemma":0.0015647179,"threshold_uncertainty_score":0.99976003},"labels":[],"label_agreement":null},{"id":"W2126496917","doi":"10.1257/aer.101.2.724","title":"Procedural Analysis of Choice Rules with Applications to Bounded Rationality","year":2011,"lang":"en","type":"article","venue":"American Economic Review","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":89,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Satisficing; Bounded rationality; Maximization; Rationality; Economics; Mathematical economics; Computer science; Framing (construction); Framing effect; Utility maximization; Automaton; Microeconomics; Artificial intelligence; Psychology; Social psychology","score_opus":0.18135908695859318,"score_gpt":0.43494911405233255,"score_spread":0.25359002709373935,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2126496917","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9848652,0.00090609386,0.0042622443,0.00086323224,0.00004427354,0.0007347213,0.00011789923,0.000027201766,0.00817915],"genre_scores_gemma":[0.97413754,0.0010137422,0.021235237,0.0030218526,0.000037501468,0.00028487793,0.000028571458,0.000016202872,0.00022445201],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9979104,0.00008437806,0.001082516,0.00055257324,0.00020793699,0.00016219578],"domain_scores_gemma":[0.9972826,0.00044505982,0.0009725809,0.0009677062,0.0001848229,0.00014722544],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0011944775,0.00014573868,0.00094170345,0.0003119896,0.00006956742,0.00006113306,0.00077517115,0.000017491411,0.0010864208],"category_scores_gemma":[0.00028840426,0.0001040128,0.00025247975,0.0012039719,0.00024187255,0.00021996758,0.000078213816,0.000054071403,0.00090522814],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020941417,0.000094656934,0.053942338,0.000023596049,0.0002228971,3.5246288e-7,0.00013745482,0.00008555958,0.0000048106103,0.0031780617,0.0023006788,0.9399887],"study_design_scores_gemma":[0.00023683456,0.00033099507,0.54759437,0.00025299896,0.0017550705,0.000010575457,0.00040087855,0.00051150564,0.000057848058,0.016522557,0.43161803,0.0007083606],"about_ca_topic_score_codex":0.0006312482,"about_ca_topic_score_gemma":0.0010240994,"teacher_disagreement_score":0.9392803,"about_ca_system_score_codex":0.0001038572,"about_ca_system_score_gemma":0.00017221132,"threshold_uncertainty_score":0.9998727},"labels":[],"label_agreement":null},{"id":"W2128221441","doi":"10.1177/1088868314530517","title":"Decision-Making Under Risk","year":2014,"lang":"en","type":"article","venue":"Personality and Social Psychology Review","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":238,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Prospect theory; Situational ethics; Management science; Causal decision theory; Decision theory; Empirical research; Psychology; Expected utility hypothesis; Heuristic; Social psychology; Decision engineering; Risk analysis (engineering); Business decision mapping; Computer science; Epistemology; Decision support system; Economics; Artificial intelligence; Microeconomics","score_opus":0.22179285854040645,"score_gpt":0.5086566347586318,"score_spread":0.28686377621822534,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2128221441","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9433041,0.0180537,0.014051207,0.011137633,0.0011422351,0.00025786064,0.000041232288,0.00006116692,0.011950847],"genre_scores_gemma":[0.97147775,0.0061440496,0.0014488026,0.020531883,0.00027226613,0.000010391983,0.000002583217,0.000013991548,0.000098290984],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99665296,0.000895018,0.00085637404,0.0007760047,0.00052737194,0.000292281],"domain_scores_gemma":[0.9962059,0.0025569864,0.0004624726,0.00050638575,0.00017052938,0.00009772188],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.008715402,0.00019674387,0.00075531076,0.000092498834,0.0005966387,0.00015770133,0.0005936688,0.00020082857,0.0014033989],"category_scores_gemma":[0.0027577917,0.00014796662,0.0003140509,0.00035075386,0.00034611434,0.00017359265,0.00013137772,0.00034832006,0.00077690295],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016666925,0.000045089404,0.0049667275,0.000019919227,0.000010002678,0.0000013323183,0.00019177789,6.3880833e-7,9.670002e-7,0.0024595675,0.018149685,0.9741376],"study_design_scores_gemma":[0.00025969994,0.00004686244,0.124861345,0.00027730467,0.00007036931,0.000038432136,0.00012564997,0.000046524343,7.044724e-8,0.5610886,0.31295243,0.00023270224],"about_ca_topic_score_codex":0.000013374783,"about_ca_topic_score_gemma":0.000043837797,"teacher_disagreement_score":0.9739049,"about_ca_system_score_codex":0.00002396146,"about_ca_system_score_gemma":0.000026072576,"threshold_uncertainty_score":0.99950945},"labels":[],"label_agreement":null},{"id":"W2128582813","doi":"10.1506/ckx0-8fbf-9ngf-ccrq","title":"Undetected Deviations in Tests of Controls: Experimental Evidence of Nonsampling Risk*","year":2003,"lang":"en","type":"article","venue":"Canadian Accounting Perspectives","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Saskatchewan; Brandon University","funders":"","keywords":"Accountability; Audit; Accounting; Payment; Ceiling (cloud); Audit substantive test; Control (management); Speculation; Econometrics; Business; Actuarial science; Economics; Finance; Political science; Internal audit; External auditor; Engineering","score_opus":0.13124267411517063,"score_gpt":0.4117447231844899,"score_spread":0.2805020490693193,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2128582813","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99584466,0.0014533639,0.00028724436,0.000075229014,0.0001641319,0.00016818332,0.000031641004,0.000010013687,0.0019655356],"genre_scores_gemma":[0.99783665,0.000013871661,0.0020517004,0.000026242062,0.000018058427,0.000007670875,3.6451885e-7,0.000011633652,0.000033789525],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99801064,0.0001650411,0.00073975814,0.00042630086,0.00036981681,0.000288422],"domain_scores_gemma":[0.99601465,0.002273684,0.00052023766,0.00044284633,0.0006130173,0.0001355308],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0021028023,0.00013268061,0.00037001722,0.0009304889,0.00013791362,0.0001247605,0.0004634393,0.000085055995,0.0003192225],"category_scores_gemma":[0.02282477,0.00012541136,0.000101274,0.0012370469,0.00017764454,0.0004658735,0.000027572005,0.00016788358,0.000029208417],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000071706534,0.00029083024,0.9179051,0.000009531122,0.000040512696,0.000017966362,0.016603969,0.0040568616,0.024970813,0.009364628,0.0002727191,0.026395394],"study_design_scores_gemma":[0.0018006364,0.00033767577,0.7513975,0.00074531167,0.00005958213,0.000025321957,0.18538162,0.0032630654,0.013526729,0.041031912,0.0015159845,0.0009146526],"about_ca_topic_score_codex":0.030390738,"about_ca_topic_score_gemma":0.13032582,"teacher_disagreement_score":0.16877764,"about_ca_system_score_codex":0.00045118175,"about_ca_system_score_gemma":0.0008194459,"threshold_uncertainty_score":0.9854064},"labels":[],"label_agreement":null},{"id":"W2128997249","doi":"10.1348/014466506x129862","title":"Under what circumstances do patients with schizophrenia jump to conclusions? A liberal acceptance account","year":2006,"lang":"en","type":"article","venue":"British Journal of Clinical Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":104,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Riverview Hospital; Simon Fraser University","funders":"","keywords":"Schizophrenia (object-oriented programming); Psychology; Task (project management); Ambiguity; Jump; Cognitive psychology; Convergence (economics); Contrast (vision); Psychosis; Psychiatry; Artificial intelligence; Computer science","score_opus":0.1462335675466719,"score_gpt":0.485616779488072,"score_spread":0.3393832119414001,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2128997249","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9877394,0.0010751332,0.0022336338,0.002209185,0.005326127,0.00018577799,0.000028092738,0.000016280826,0.0011863613],"genre_scores_gemma":[0.987391,0.0003450943,0.005505198,0.0056267967,0.00088071177,0.000003084247,0.0000025194774,0.000027239348,0.00021833321],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9934089,0.00048054094,0.003627446,0.0007601163,0.0012884927,0.00043446542],"domain_scores_gemma":[0.9934672,0.0022374485,0.0018962717,0.0005945943,0.0014137839,0.00039068374],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004719485,0.00022330908,0.0011568639,0.00030291633,0.00021614185,0.0013422165,0.0016201013,0.00029441706,0.0009550323],"category_scores_gemma":[0.0020732146,0.00017826736,0.00042914433,0.0006533027,0.00039398394,0.0015669027,0.00018579216,0.00081180123,0.00032808355],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011806325,0.0006951888,0.07260318,5.6126606e-7,0.00002069599,0.00019560366,0.000016481816,0.000169174,0.0000043274754,0.000069754744,0.06546062,0.8595838],"study_design_scores_gemma":[0.004675196,0.0010347309,0.84690183,0.00029220025,0.000029628332,0.00053815625,0.000152145,0.0000056609824,0.0000017163433,0.10895707,0.037124015,0.0002876472],"about_ca_topic_score_codex":0.000017918006,"about_ca_topic_score_gemma":0.00027802688,"teacher_disagreement_score":0.85929614,"about_ca_system_score_codex":0.000048609978,"about_ca_system_score_gemma":0.00019114379,"threshold_uncertainty_score":0.9999582},"labels":[],"label_agreement":null},{"id":"W2129320919","doi":"10.1111/j.1467-9280.2008.02113.x","title":"Smarter Than We Think","year":2008,"lang":"en","type":"article","venue":"Psychological Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":233,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Vlaamse regering","keywords":"Psychology; Normative; Anterior cingulate cortex; Heuristic; Cued speech; Prefrontal cortex; Social psychology; Cognitive psychology; Functional magnetic resonance imaging; Lie detection; Cognition; Deception; Neuroscience; Epistemology","score_opus":0.37175879998603656,"score_gpt":0.49329278767700585,"score_spread":0.12153398769096929,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2129320919","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9478122,0.000040178424,0.001022681,0.0026137398,0.001286828,0.00008953097,0.0000036101999,0.00008676223,0.047044456],"genre_scores_gemma":[0.9939805,0.000038747505,0.003317341,0.0011237027,0.00009396239,0.000004209295,2.1607224e-7,0.0000043355535,0.0014369529],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99610335,0.00008328993,0.0005548153,0.0011487065,0.0015911586,0.0005186607],"domain_scores_gemma":[0.9976751,0.00056903856,0.00016726936,0.0010537647,0.00020338669,0.00033143265],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0037396085,0.00015166064,0.00025649872,0.00024670098,0.0007119776,0.00036055886,0.0028477178,0.000100574514,0.0018166295],"category_scores_gemma":[0.0020648113,0.00008559165,0.00014106558,0.0018166137,0.0017862833,0.00063298154,0.0003084818,0.00022704962,0.0063821496],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003814388,0.0003749954,0.040328167,2.1404448e-7,0.0000011850366,0.0001160628,0.00074428605,0.00002548818,0.002155682,0.0015472051,0.027485954,0.9271826],"study_design_scores_gemma":[0.00033777335,0.00037328567,0.59497607,0.000009093388,0.0000029387952,0.00039201125,0.0002567626,0.00052330125,0.00025801727,0.33683598,0.06565337,0.0003814098],"about_ca_topic_score_codex":0.000007666604,"about_ca_topic_score_gemma":0.00000421847,"teacher_disagreement_score":0.9268012,"about_ca_system_score_codex":0.00004388858,"about_ca_system_score_gemma":0.000047239148,"threshold_uncertainty_score":0.99909586},"labels":[],"label_agreement":null},{"id":"W2129925846","doi":"10.1017/s0007123412000117","title":"Why Do Citizens Discount the Future? Public Opinion and the Timing of Policy Consequences","year":2012,"lang":"en","type":"article","venue":"British Journal of Political Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":264,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Discounting; Economics; Public economics; Public opinion; Term (time); Consumption (sociology); Public policy; Politics; Causation; Time preference; Political science; Microeconomics; Sociology","score_opus":0.10372752853824548,"score_gpt":0.40588853933641783,"score_spread":0.30216101079817237,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2129925846","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94791824,0.0019701386,0.0004580531,0.04568646,0.001333264,0.000089549714,0.000021387317,0.0000039297543,0.0025190006],"genre_scores_gemma":[0.9966817,0.00018985472,0.00041011118,0.0017511103,0.0009450452,0.0000010953589,7.983901e-8,0.000004088051,0.000016898199],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9962253,0.0002961828,0.00092279114,0.00020252407,0.001620139,0.00073306327],"domain_scores_gemma":[0.9954079,0.0025647047,0.0005339175,0.00029134442,0.0006560173,0.0005461446],"candidate_categories":["metaresearch","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.014651026,0.00009995684,0.00032837837,0.00023414359,0.00060987315,0.0015251916,0.0016517482,0.000048442842,0.00011850291],"category_scores_gemma":[0.012818487,0.000050240145,0.00015316615,0.00088769273,0.007094469,0.0012968607,0.00030814222,0.00028842894,0.000008563823],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022341226,0.000064664695,0.0033133647,0.00000197345,0.000005711116,0.0000096263575,0.00046683694,0.0000025682064,0.00016553674,0.7222499,0.0033323672,0.27036506],"study_design_scores_gemma":[0.00094020035,0.00013401119,0.13938676,0.00020048607,0.000028670185,0.009431452,0.011626733,0.00017735273,0.00025821425,0.8100639,0.027511057,0.0002411445],"about_ca_topic_score_codex":0.0005351756,"about_ca_topic_score_gemma":0.000043074193,"teacher_disagreement_score":0.27012393,"about_ca_system_score_codex":0.00010548699,"about_ca_system_score_gemma":0.00058517157,"threshold_uncertainty_score":0.9995113},"labels":[],"label_agreement":null},{"id":"W2130195989","doi":"10.7202/601409ar","title":"Espérance morale avec risque moral","year":2009,"lang":"fr","type":"article","venue":"L Actualité économique","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Humanities; Philosophy","score_opus":0.16344087390082487,"score_gpt":0.3698712586025557,"score_spread":0.20643038470173083,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2130195989","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94040555,0.0021400484,0.0034524286,0.025957085,0.004913914,0.00050161063,0.0002478099,0.0001700052,0.022211561],"genre_scores_gemma":[0.9425931,0.00039617126,0.0052521876,0.0073925587,0.0010220812,0.000020631007,0.000016992866,0.000055172433,0.043251127],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99402803,0.0005156452,0.0022446648,0.0016542781,0.0003679759,0.001189422],"domain_scores_gemma":[0.9948941,0.0015337284,0.00084511883,0.0016925992,0.00033084146,0.00070362806],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0029048386,0.0007394907,0.001320289,0.000436893,0.00035398404,0.0013948819,0.0018650248,0.000789659,0.005095832],"category_scores_gemma":[0.0013973176,0.000718926,0.00074027607,0.0007008548,0.0005133435,0.0019287555,0.00025291007,0.00080105005,0.009033894],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001287517,0.00043798963,0.001340639,0.000008114155,0.000023505616,0.00012856173,0.0011049962,0.0016516472,0.00014132062,0.04411629,0.017145663,0.9337725],"study_design_scores_gemma":[0.0008459476,0.00044938832,0.005775782,0.00015899827,0.000055383684,0.00014690074,0.0003008517,0.01115809,0.0013148016,0.58179826,0.39704856,0.0009470484],"about_ca_topic_score_codex":0.0005716373,"about_ca_topic_score_gemma":0.00028943113,"teacher_disagreement_score":0.93282545,"about_ca_system_score_codex":0.0005308885,"about_ca_system_score_gemma":0.0004919495,"threshold_uncertainty_score":0.9996418},"labels":[],"label_agreement":null},{"id":"W2130478903","doi":"10.1177/0956797614563958","title":"Scarcity Frames Value","year":2015,"lang":"en","type":"article","venue":"Psychological Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":410,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; Canadian Institute for Advanced Research; National Science Foundation","keywords":"Psychology; Scarcity; Value (mathematics); Social psychology; Statistics; Microeconomics; Economics","score_opus":0.47363376291587195,"score_gpt":0.5508557516161008,"score_spread":0.07722198870022884,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2130478903","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9398131,0.00003267081,0.0021166254,0.0014548644,0.0015850519,0.000084509054,0.000003865297,0.000078945945,0.0548304],"genre_scores_gemma":[0.9905776,0.0000025425757,0.0077010454,0.0012480959,0.00008960229,0.000004553773,2.1187803e-7,0.0000036009728,0.00037274777],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9957492,0.00012128284,0.000517156,0.0010905428,0.0020455455,0.00047627807],"domain_scores_gemma":[0.9972407,0.00055196125,0.00016648043,0.0009932406,0.000418131,0.0006294722],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.010058998,0.00013460114,0.0002511811,0.00022543444,0.00027754204,0.00079489674,0.0029788085,0.00010251689,0.00049329747],"category_scores_gemma":[0.010850628,0.000078441255,0.00009989263,0.0020848268,0.0014063639,0.00064391724,0.00043717035,0.0002168336,0.0041574696],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003390973,0.0002551224,0.0421444,1.2422701e-7,6.647806e-7,0.00002055703,0.0001992495,0.00020661723,0.00053464144,0.00607249,0.016652744,0.9338795],"study_design_scores_gemma":[0.00026542533,0.00028235148,0.13283734,0.0000045298834,0.0000025104252,0.000045117667,0.0003066013,0.0011866906,0.00021110273,0.82925385,0.035376254,0.00022823413],"about_ca_topic_score_codex":0.000020290569,"about_ca_topic_score_gemma":0.0000025280485,"teacher_disagreement_score":0.93365127,"about_ca_system_score_codex":0.00008613313,"about_ca_system_score_gemma":0.00009064498,"threshold_uncertainty_score":0.9974814},"labels":[],"label_agreement":null},{"id":"W2130852452","doi":"10.1017/s0140525x01413914","title":"Objectivity, intentionality, and levels of explanation","year":2001,"lang":"en","type":"article","venue":"Behavioral and Brain Sciences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; University of Toronto","funders":"","keywords":"Intentionality; Objectivity (philosophy); Epistemology; Constructivism (international relations); Psychology; Philosophy; Cognitive psychology","score_opus":0.3858575790832613,"score_gpt":0.47798897324155076,"score_spread":0.09213139415828947,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2130852452","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99665326,0.000105162115,0.00034651347,0.0016185279,0.00020728154,0.00008317487,0.00003659285,0.000015109784,0.00093439606],"genre_scores_gemma":[0.9985285,0.000014905893,0.00086953037,0.00009563959,0.00002532181,0.000003073309,8.515318e-7,0.0000028366264,0.00045937026],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99802494,0.00010141905,0.00047581884,0.0004778254,0.00074686535,0.00017311182],"domain_scores_gemma":[0.998676,0.000676269,0.00021952095,0.00017082818,0.00016358132,0.00009379586],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034753755,0.00010808881,0.00023608,0.0002958823,0.0002654967,0.00033346924,0.00036699336,0.00006014581,0.00022677818],"category_scores_gemma":[0.00052817137,0.00007450133,0.00005728125,0.00060947216,0.0007977866,0.0007235277,0.00022875922,0.00006707796,0.000012756397],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009536362,0.00008830337,0.28860545,9.641299e-7,9.4107975e-7,0.0000041381327,0.00021868183,0.000004207902,0.0020125543,0.0017382558,0.0003774794,0.7069395],"study_design_scores_gemma":[0.00030388884,0.00035688822,0.7855496,0.00002837421,0.000012560733,0.00011655882,0.0020549367,0.00047733396,0.0004772086,0.20731445,0.0030978844,0.00021033266],"about_ca_topic_score_codex":0.00022473624,"about_ca_topic_score_gemma":0.00027211243,"teacher_disagreement_score":0.7067292,"about_ca_system_score_codex":0.0000118181715,"about_ca_system_score_gemma":0.000047932812,"threshold_uncertainty_score":0.32156515},"labels":[],"label_agreement":null},{"id":"W2131123655","doi":"10.1093/qje/qju033","title":"The Psychological Effect of Weather on Car Purchases*","year":2014,"lang":"en","type":"article","venue":"The Quarterly Journal of Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":255,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Salience (neuroscience); Purchasing; Consumption (sociology); Economics; Intertemporal choice; Consumer behaviour; Mental accounting; Variety (cybernetics); Durable good; Econometrics; Advertising; Microeconomics; Computer science; Psychology; Business; Cognitive psychology; Operations management","score_opus":0.07184151106119721,"score_gpt":0.38489941000867356,"score_spread":0.3130578989474764,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2131123655","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.994878,0.00006137977,0.00022751809,0.001312863,0.0013911538,0.000096159165,0.000005379667,0.0000040124983,0.0020235614],"genre_scores_gemma":[0.9992681,0.000028195083,0.00008187557,0.00017835396,0.00029738972,0.0000016136906,1.2621442e-7,0.000011935146,0.00013240265],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9974641,0.0005785561,0.0012921826,0.00020876083,0.00024133147,0.00021504743],"domain_scores_gemma":[0.9900516,0.007494285,0.0013514182,0.000859356,0.00014266167,0.00010062834],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010629051,0.00016199928,0.00052189076,0.00012856224,0.0002037037,0.0002732596,0.0017909136,0.00008730979,0.000108363725],"category_scores_gemma":[0.0007727825,0.00006617371,0.0004388818,0.00010369386,0.00026799156,0.00016372351,0.000031618012,0.0003265768,0.00025806553],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004979776,0.000056126722,0.00059686834,4.9111e-7,0.000022867302,0.0000021259414,0.00030624025,0.0006660399,0.000063556145,0.002473436,0.002041431,0.99327284],"study_design_scores_gemma":[0.0036977849,0.035018772,0.008399332,0.00009003073,0.0001553432,0.00057278137,0.0020865025,0.006139438,0.0011642043,0.84049994,0.10165907,0.0005167757],"about_ca_topic_score_codex":0.0000037793197,"about_ca_topic_score_gemma":0.000011375588,"teacher_disagreement_score":0.99275607,"about_ca_system_score_codex":0.000041902847,"about_ca_system_score_gemma":0.000023963834,"threshold_uncertainty_score":0.36838382},"labels":[],"label_agreement":null},{"id":"W2131258498","doi":"10.1016/j.jmateco.2006.04.010","title":"Inter-temporal preference for flexibility and risky choice","year":2006,"lang":"en","type":"article","venue":"Journal of Mathematical Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Flexibility (engineering); Preference; Mathematical economics; Normative; Consistency (knowledge bases); Ex-ante; Representation (politics); Key (lock); Subjective expected utility; Time consistency; Econometrics; Economics; Revealed preference; Expected utility hypothesis; Computer science; Microeconomics; Artificial intelligence; Actuarial science","score_opus":0.22270796674666915,"score_gpt":0.4046448403129322,"score_spread":0.18193687356626304,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2131258498","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.963925,0.000046447196,0.033699386,0.0005060142,0.00031319686,0.00014495192,0.000025537382,0.000007762309,0.001331711],"genre_scores_gemma":[0.9709014,0.000009232002,0.028419446,0.00008020574,0.00023973816,0.0000030763372,7.8312553e-7,0.000012845164,0.00033323493],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99737984,0.000046481815,0.0018978694,0.00028760592,0.00018740221,0.0002008093],"domain_scores_gemma":[0.99458444,0.003468842,0.0011147263,0.00037987425,0.00029898563,0.00015312278],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0040291166,0.00015391027,0.0006462622,0.00017470028,0.000079857826,0.0004091416,0.0005903127,0.000111527945,0.00018819654],"category_scores_gemma":[0.0029279564,0.00010848272,0.0002603086,0.00007282127,0.00014665931,0.000521702,0.00011996538,0.00018429803,0.000060561615],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00065650523,0.0014268133,0.042052858,0.000093100396,0.000080614256,0.000012079194,0.00043184232,0.001587615,0.00017358852,0.051241487,0.020135896,0.8821076],"study_design_scores_gemma":[0.00059211324,0.00020606344,0.0028441756,0.000035363748,0.000027838772,0.00007762848,0.00013142046,0.00873534,0.00010818047,0.97253615,0.014568325,0.00013739476],"about_ca_topic_score_codex":0.000008544344,"about_ca_topic_score_gemma":0.00004051556,"teacher_disagreement_score":0.9212947,"about_ca_system_score_codex":0.00008540214,"about_ca_system_score_gemma":0.00009226452,"threshold_uncertainty_score":0.4423797},"labels":[],"label_agreement":null},{"id":"W2131540949","doi":"10.1111/j.1467-9280.2006.01817.x","title":"Are Juvenile Offenders Extreme Future Discounters?","year":2006,"lang":"en","type":"article","venue":"Psychological Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":76,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Psychology; Juvenile delinquency; Sensation seeking; Developmental psychology; Personality; Task (project management); Scale (ratio); Big Five personality traits; Social psychology","score_opus":0.24216982227378017,"score_gpt":0.4470223768588267,"score_spread":0.2048525545850465,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2131540949","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.961556,0.000068855894,0.0013004958,0.0031074453,0.0022941176,0.00010814343,0.000014517644,0.00008228867,0.031468093],"genre_scores_gemma":[0.9961762,0.0000039808046,0.0014060248,0.0010160357,0.00037466967,0.000007202645,8.936161e-7,0.000006148691,0.0010088709],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9957395,0.000075723074,0.00067060825,0.0013035281,0.0016266153,0.0005840305],"domain_scores_gemma":[0.9978503,0.0003013422,0.00046115968,0.0009655288,0.00020622552,0.0002154486],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0032327755,0.00019347144,0.0003172623,0.0002601401,0.00049493375,0.0008854937,0.0025174755,0.00011950084,0.0015631813],"category_scores_gemma":[0.0008837231,0.000114610215,0.00016491259,0.001837147,0.0011602328,0.00070255896,0.00025255632,0.00022967874,0.0016108546],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007451293,0.0008303816,0.09035571,9.792176e-7,0.0000018313325,0.00013515865,0.00012795857,0.00024766894,0.004349609,0.005453383,0.1309145,0.7675083],"study_design_scores_gemma":[0.0003206782,0.0001100746,0.66762805,0.000011150484,0.0000045034867,0.000050803916,0.0011531381,0.00037506138,0.00010302507,0.23664412,0.09324698,0.00035242952],"about_ca_topic_score_codex":0.000021665715,"about_ca_topic_score_gemma":0.00005662979,"teacher_disagreement_score":0.7671559,"about_ca_system_score_codex":0.00009029321,"about_ca_system_score_gemma":0.000028701017,"threshold_uncertainty_score":0.99934953},"labels":[],"label_agreement":null},{"id":"W2131762860","doi":"10.2139/ssrn.1077708","title":"Procrastination and Impatience","year":2008,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Procrastination; Psychology; Economics; Social psychology","score_opus":0.07745090180996358,"score_gpt":0.35895283263990735,"score_spread":0.2815019308299438,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2131762860","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9902717,0.0004078786,0.00798566,0.00037713547,0.00018679338,0.00005213457,8.6567286e-7,0.0000144414535,0.00070340914],"genre_scores_gemma":[0.9978605,0.00070284243,0.0003069061,0.000057850782,0.00009187662,0.0000014678027,2.8195745e-7,0.0000068963577,0.00097140286],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9978056,0.00006356448,0.0004300122,0.0002492093,0.0005539605,0.00089765585],"domain_scores_gemma":[0.999046,0.00022699553,0.0002553119,0.00016676172,0.00021387667,0.00009100424],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032327622,0.000093815834,0.0001543,0.00020396995,0.0004258857,0.00014817026,0.00038074676,0.000045906323,0.000044762066],"category_scores_gemma":[0.001034271,0.0000664998,0.00005930224,0.0002775182,0.00009321863,0.0005157226,0.000057877845,0.00066657393,0.00011965879],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021148353,0.000033699096,0.021749057,1.8685434e-7,0.0000044579842,0.000007068892,0.00023617574,0.000029947441,0.00010262175,0.0042296085,0.0002625861,0.97332346],"study_design_scores_gemma":[0.00030132648,0.0003153128,0.013397681,0.000005642356,0.000005343771,0.0033577364,0.00096276647,0.00062785024,0.00004972209,0.9787233,0.002128743,0.00012459353],"about_ca_topic_score_codex":0.000011574881,"about_ca_topic_score_gemma":0.00009070223,"teacher_disagreement_score":0.9744937,"about_ca_system_score_codex":0.0002487844,"about_ca_system_score_gemma":0.00094802346,"threshold_uncertainty_score":0.32756114},"labels":[],"label_agreement":null},{"id":"W2134645122","doi":"10.1002/bdm.1763","title":"The Effect of Temporal Distance on Attitudes toward Imprecise Probabilities and Imprecise Outcomes","year":2012,"lang":"en","type":"article","venue":"Journal of Behavioral Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":48,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Ambiguity; Salience (neuroscience); Construal level theory; Outcome (game theory); Ambiguity aversion; Dimension (graph theory); Psychology; Subjective expected utility; Social psychology; Econometrics; Computer science; Expected utility hypothesis; Cognitive psychology; Mathematics; Statistics; Mathematical economics","score_opus":0.08945839551006228,"score_gpt":0.43622934465415264,"score_spread":0.34677094914409035,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2134645122","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99440676,0.0012105748,0.0012887437,0.000118407486,0.002509537,0.0003286038,0.000028475835,0.00001570602,0.00009321957],"genre_scores_gemma":[0.9956418,0.00006130911,0.0039629927,0.000028937508,0.00016666515,0.000008916002,3.4995963e-7,0.000032888933,0.00009611803],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9933597,0.0004732071,0.002755813,0.00042148307,0.0024237947,0.0005660182],"domain_scores_gemma":[0.9833494,0.012530829,0.00228768,0.00092560065,0.00059507036,0.00031144693],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010653427,0.0004240856,0.0012479265,0.0005319155,0.00038948565,0.00065642135,0.0014339885,0.00019448531,0.00008562748],"category_scores_gemma":[0.004419752,0.00021329007,0.0007019969,0.00047904564,0.00039963477,0.0012303726,0.000414658,0.00056067895,0.000033004166],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00077738427,0.00012772054,0.4586644,0.000004707054,0.0000108203585,0.000011060711,0.00030240737,0.00004944053,0.00008088354,0.00006757002,0.00049825467,0.53940535],"study_design_scores_gemma":[0.002969097,0.0052557588,0.93788,0.0011373785,0.00032038213,0.0003606432,0.0019222985,0.0001758932,0.0014874036,0.039293103,0.008373215,0.0008248264],"about_ca_topic_score_codex":0.000012175873,"about_ca_topic_score_gemma":0.000027044027,"teacher_disagreement_score":0.53858054,"about_ca_system_score_codex":0.0001719588,"about_ca_system_score_gemma":0.000076367636,"threshold_uncertainty_score":0.86977166},"labels":[],"label_agreement":null},{"id":"W2135643459","doi":"10.22004/ag.econ.273724","title":"Iterated Expectations under Rank-Dependent Expected Utility and Model Consistency","year":2015,"lang":"en","type":"preprint","venue":"AgEcon Search (University of Minnesota, USA)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Lottery; Expected utility hypothesis; Mathematical economics; Subjective expected utility; Valuation (finance); Impossibility; Econometrics; Economics; Mathematics; Microeconomics","score_opus":0.25498415820604586,"score_gpt":0.3805275900424586,"score_spread":0.12554343183641276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2135643459","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9843696,0.00026188663,0.008355637,0.00094705645,0.00032947166,0.0004632197,0.0006437123,0.00005705393,0.0045724045],"genre_scores_gemma":[0.9912991,0.00010499584,0.0042520678,0.00004074941,0.000024161125,0.0000015651631,0.00008008419,0.000020718418,0.0041765417],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.995445,0.0005329867,0.0007607356,0.0014043979,0.0014126836,0.00044420615],"domain_scores_gemma":[0.9944695,0.0010291121,0.00058595964,0.0014686049,0.0019694173,0.00047738463],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002519481,0.00037798297,0.0009921166,0.0009321174,0.00042404758,0.00033672486,0.0015295341,0.0004996023,0.00143507],"category_scores_gemma":[0.0006173511,0.00040590137,0.00030641007,0.0005126879,0.0007631853,0.0006328012,0.0020824056,0.000744225,0.00035043893],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0029615692,0.003431011,0.033599436,0.00031451427,0.0011483509,0.0010489938,0.11976876,0.05830683,0.002824179,0.00489222,0.092822455,0.6788817],"study_design_scores_gemma":[0.005774185,0.0004018428,0.033371337,0.0003434837,0.0004372191,0.000082970975,0.17708255,0.55503166,0.00027740895,0.22302668,0.0019602664,0.0022104091],"about_ca_topic_score_codex":0.0010142546,"about_ca_topic_score_gemma":0.0015112115,"teacher_disagreement_score":0.67667127,"about_ca_system_score_codex":0.0002071629,"about_ca_system_score_gemma":0.0009687383,"threshold_uncertainty_score":0.9998393},"labels":[],"label_agreement":null},{"id":"W2135727220","doi":"10.1371/journal.pone.0092160","title":"The Child as Econometrician: A Rational Model of Preference Understanding in Children","year":2014,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":106,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Air Force Office of Scientific Research; Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; James S. McDonnell Foundation; National Science Foundation","keywords":"Preference; Simple (philosophy); Revealed preference; Cognitive psychology; Psychology; Computer science; Econometrics; Economics; Microeconomics; Epistemology","score_opus":0.40889698204856734,"score_gpt":0.3385720280620146,"score_spread":0.07032495398655275,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2135727220","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9839989,0.000033722223,0.0027471066,0.00055980624,0.000031703526,0.00014751249,0.000015043376,0.000009804844,0.0124563975],"genre_scores_gemma":[0.9987078,0.000026380721,0.00091055536,0.00008815698,0.000030893272,0.0000072126177,0.0000022470656,0.000006521305,0.00022027094],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9983009,0.000069191396,0.0005799003,0.00029270185,0.0005944166,0.00016290916],"domain_scores_gemma":[0.9979546,0.001223591,0.0002556564,0.00042948656,0.00008415178,0.000052529005],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018854107,0.00008599542,0.00024731923,0.0003394215,0.00016233379,0.00017838205,0.0006545035,0.000055110355,0.00008616212],"category_scores_gemma":[0.0022767058,0.000058424754,0.000056637742,0.0004911052,0.000085738066,0.00021968862,0.000112903705,0.00013414312,0.00014484623],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022537904,0.002889722,0.54480004,0.000007598143,0.00015421749,6.16668e-7,0.0010172518,0.029214751,0.0006265505,0.24937077,0.000671681,0.1710214],"study_design_scores_gemma":[0.00043168035,0.00010385441,0.03295423,0.00006753927,0.00001863069,0.000001507665,0.00017704362,0.1779003,0.00060002814,0.78755623,0.00003211701,0.00015682651],"about_ca_topic_score_codex":0.000017727321,"about_ca_topic_score_gemma":0.000073088064,"teacher_disagreement_score":0.5381855,"about_ca_system_score_codex":0.00008372072,"about_ca_system_score_gemma":0.00005864503,"threshold_uncertainty_score":0.2725594},"labels":[],"label_agreement":null},{"id":"W2136623844","doi":"10.1016/j.cognition.2012.04.004","title":"Are we good at detecting conflict during reasoning?","year":2012,"lang":"en","type":"article","venue":"Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":115,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Psychology; Neglect; Social psychology; Base (topology); Cognitive psychology; Personality","score_opus":0.21907394691581433,"score_gpt":0.40171507044023874,"score_spread":0.1826411235244244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2136623844","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9889344,0.0002480631,0.00023603991,0.00011850992,0.00066678424,0.000098243945,0.000017505592,0.000087692024,0.009592736],"genre_scores_gemma":[0.99831903,0.000017357275,0.00030082432,0.000109593006,0.000258366,0.000011094415,0.000003928585,0.000016557273,0.0009632224],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.998327,0.00008849839,0.00044414942,0.00033450942,0.00046334293,0.00034248448],"domain_scores_gemma":[0.9982755,0.0005456706,0.00049686513,0.00033593772,0.00017875546,0.00016724375],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0012861066,0.00013218635,0.00021121392,0.00018314362,0.00040006422,0.0002086016,0.00023521773,0.00010517412,0.00083509844],"category_scores_gemma":[0.0020092537,0.00011244861,0.00011395166,0.00027650694,0.00004608391,0.0005654581,0.00017372388,0.00014141577,0.002860922],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016884024,0.00022284001,0.2847674,0.000013451566,0.000021991673,0.000037202943,0.001499817,0.000040535215,0.013670014,0.000085822845,0.0026842232,0.6967879],"study_design_scores_gemma":[0.002508748,0.0001322311,0.6734147,0.00067356235,0.00017571347,0.0006293098,0.007326601,0.0009004547,0.14581716,0.02153809,0.14547372,0.0014097332],"about_ca_topic_score_codex":0.0000023657442,"about_ca_topic_score_gemma":0.000021136979,"teacher_disagreement_score":0.6953781,"about_ca_system_score_codex":0.00009581472,"about_ca_system_score_gemma":0.000009922288,"threshold_uncertainty_score":0.99791545},"labels":[],"label_agreement":null},{"id":"W2136762929","doi":"10.1111/1467-9280.01438","title":"Psychological Models of Professional Decision Making","year":2003,"lang":"en","type":"article","venue":"Psychological Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":252,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Heuristic; Psychology; Process (computing); Ideal (ethics); Simple (philosophy); Social psychology; Computer science; Law; Artificial intelligence; Epistemology; Political science","score_opus":0.3179719015263955,"score_gpt":0.5405903908261886,"score_spread":0.22261848929979317,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2136762929","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91680217,0.00005485876,0.028761819,0.00015492059,0.002036081,0.00019212197,0.000007343672,0.000048788388,0.051941898],"genre_scores_gemma":[0.9571099,0.000010228379,0.0421316,0.00052660354,0.00003100787,0.000011453174,2.4305888e-7,0.0000073036626,0.00017163389],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99352205,0.00027497712,0.0013176742,0.0016261908,0.0026006722,0.0006584397],"domain_scores_gemma":[0.9953251,0.0020463583,0.000504518,0.0013042118,0.0005208668,0.000298932],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.010608118,0.00023748266,0.00049880217,0.00045130524,0.00044176425,0.00027674646,0.0029288712,0.00022782612,0.0023412977],"category_scores_gemma":[0.008984349,0.00013617365,0.00022834567,0.0028532075,0.0015706739,0.00077180815,0.0003317227,0.00036325963,0.0005412249],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014368807,0.0011709284,0.0054975194,6.898396e-7,0.0000014470336,0.00001927767,0.000117279604,0.0008854974,0.0026822803,0.04148307,0.0028481642,0.94515014],"study_design_scores_gemma":[0.00035049615,0.00032597722,0.048636746,0.000042284857,0.0000036198492,0.00008367477,0.00017472955,0.0015996492,0.00019436651,0.9463657,0.0019812186,0.00024151556],"about_ca_topic_score_codex":0.000001171901,"about_ca_topic_score_gemma":0.0000014555366,"teacher_disagreement_score":0.9449086,"about_ca_system_score_codex":0.0000633877,"about_ca_system_score_gemma":0.00006458187,"threshold_uncertainty_score":0.9993634},"labels":[],"label_agreement":null},{"id":"W2136793642","doi":"10.1111/j.1529-1006.2006.00025.x","title":"Rationality and the Adolescent Mind","year":2006,"lang":"en","type":"editorial","venue":"Gothic.net","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Rationality; Psychology; Cognitive science; Cognitive psychology; Psychotherapist; Social psychology; Epistemology; Philosophy","score_opus":0.07371184409555227,"score_gpt":0.391485847503846,"score_spread":0.31777400340829376,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2136793642","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013594134,0.00086135475,0.00049646886,0.002007967,0.9750538,0.00046718176,0.0009019359,0.000031395004,0.006585792],"genre_scores_gemma":[0.022784155,0.00012096957,0.00072650384,0.0005105218,0.95590293,0.00003929128,0.00034206288,0.00005557383,0.019517966],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99466556,0.00049272564,0.0011959801,0.00095571013,0.002389491,0.00030053445],"domain_scores_gemma":[0.98876244,0.008657177,0.00074477127,0.0011294662,0.0005935356,0.00011260344],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.007920536,0.00033683568,0.00072717783,0.00016414415,0.00031678108,0.0012890286,0.0012475455,0.0008252873,0.0005019122],"category_scores_gemma":[0.007874598,0.00019569085,0.00025393002,0.0002460174,0.00059773406,0.00017043944,0.00035923658,0.0010326514,0.0007802366],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009425092,0.000043970915,0.00013395144,0.0000039441315,0.0000072188477,0.000005560394,0.000068783105,0.0000249799,5.851024e-7,0.00015223237,0.9309346,0.06852989],"study_design_scores_gemma":[0.0008552475,0.000018486271,0.0006863857,0.000053240397,0.00004237687,0.0000030627061,0.000037601483,0.00017498521,0.0000029667476,0.051561788,0.9463244,0.00023942674],"about_ca_topic_score_codex":0.00026038458,"about_ca_topic_score_gemma":0.00048168222,"teacher_disagreement_score":0.068290465,"about_ca_system_score_codex":0.0000958641,"about_ca_system_score_gemma":0.00040308543,"threshold_uncertainty_score":0.9999978},"labels":[],"label_agreement":null},{"id":"W2136847985","doi":"10.1142/s0217590804000779","title":"ECONOMICS, ECONOMISTS, AND BEHAVIOURAL ECONOMICS: SOME ISSUES OF CHOICE","year":2004,"lang":"en","type":"article","venue":"The Singapore Economic Review","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Economics; Positive economics; Behavioural economics; Variance (accounting); Experimental economics; Behavioral economics; Public economics; Neoclassical economics; Microeconomics","score_opus":0.1539336878156136,"score_gpt":0.39956136528476444,"score_spread":0.24562767746915085,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2136847985","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94796246,0.039839875,0.000007588431,0.008928662,0.001031363,0.0005886159,0.00012459393,0.000036732392,0.0014801237],"genre_scores_gemma":[0.88845587,0.106797785,0.00083426025,0.0025545268,0.0004896204,0.00004010316,0.000023998593,0.00007704124,0.00072677934],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99556774,0.0001550203,0.002689735,0.0010156658,0.0001126258,0.00045920975],"domain_scores_gemma":[0.99520266,0.00089675206,0.0017500571,0.0018323538,0.00008649179,0.00023168298],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00441787,0.00045267874,0.0015543385,0.00021871178,0.0002659873,0.00040685112,0.001776442,0.00014916674,0.0006103276],"category_scores_gemma":[0.00051183853,0.00033191498,0.0005039296,0.000099248406,0.000596194,0.001118243,0.00045136653,0.0002752684,0.0010235788],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000047781272,0.00015329376,0.008903082,0.00017358064,0.00013009836,0.0000057635552,0.000348955,0.0027036823,0.000020383515,0.050208464,0.007498205,0.9298067],"study_design_scores_gemma":[0.0017109433,0.0002397365,0.00880035,0.0011191478,0.00030307347,0.0002146666,0.00033402478,0.0004267061,0.0005269116,0.59500545,0.39013538,0.0011836133],"about_ca_topic_score_codex":0.0007154976,"about_ca_topic_score_gemma":0.00045371437,"teacher_disagreement_score":0.9286231,"about_ca_system_score_codex":0.00038361648,"about_ca_system_score_gemma":0.00031678088,"threshold_uncertainty_score":0.9999133},"labels":[],"label_agreement":null},{"id":"W2136956023","doi":"10.1080/00346764.2010.517631","title":"Freedom to Choose and Choice X-inefficiencies: Human and Consumer Rights, and Positive and Normative Implications of Choice Behavior","year":2010,"lang":"en","type":"article","venue":"Review of Social Economy","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"University of Cambridge","keywords":"Satisficing; Normative; Freedom of choice; Economics; Perspective (graphical); Microeconomics; Consumer choice; Public choice; Rational choice theory (criminology); Preference; Narrative; Public good; Positive economics; Social psychology; Psychology; Computer science","score_opus":0.05603001922893941,"score_gpt":0.40966324351142575,"score_spread":0.35363322428248634,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2136956023","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99265337,0.0032223817,0.000021141856,0.0007158452,0.000049247486,0.0005677161,0.00016170056,0.0000070328165,0.0026015604],"genre_scores_gemma":[0.99784714,0.0007553242,0.0008394751,0.0003773035,0.00005290821,0.000041099527,0.000005598568,0.000008442778,0.00007270334],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9984423,0.00006500671,0.00080920995,0.00040808684,0.00012611982,0.00014925847],"domain_scores_gemma":[0.99766135,0.0010264586,0.0005384017,0.00026478627,0.0003422162,0.00016681426],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010514995,0.00016007035,0.0006606066,0.0001457806,0.00030871568,0.00011378272,0.00023927081,0.00008667322,0.000108635555],"category_scores_gemma":[0.000528237,0.00012875175,0.00006595745,0.00020530516,0.00066559255,0.00035654186,0.00020979487,0.00015076721,0.000008553224],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010616119,0.00024607062,0.0779122,0.0003717188,0.000043562963,9.936828e-7,0.0033719798,2.4687463e-7,0.0019964862,0.012993842,0.0036978007,0.8993545],"study_design_scores_gemma":[0.0006021314,0.00013679727,0.8933373,0.00047061584,0.0001937133,0.000024984265,0.00041822722,0.000015119273,0.0001565754,0.008800088,0.09548905,0.00035537142],"about_ca_topic_score_codex":0.00036703347,"about_ca_topic_score_gemma":0.0003484008,"teacher_disagreement_score":0.8989991,"about_ca_system_score_codex":0.000016119673,"about_ca_system_score_gemma":0.00004418604,"threshold_uncertainty_score":0.5250344},"labels":[],"label_agreement":null},{"id":"W2137079573","doi":"","title":"Risk, Ambiguity, and the Klibanoff Axioms","year":2008,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Expected utility hypothesis; Ambiguity; Axiom; Mathematical economics; Subjective expected utility; Class (philosophy); Econometrics; Choquet integral; Economics; Utility theory; Computer science; Mathematics; Artificial intelligence","score_opus":0.13634121487098547,"score_gpt":0.4234576745316486,"score_spread":0.2871164596606631,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2137079573","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92863405,0.00034369118,0.000013067403,0.0010964792,0.0011839196,0.0008620715,0.0001344728,0.000042208834,0.06769005],"genre_scores_gemma":[0.9616786,0.033310004,0.0004573462,0.00017086185,0.00031161492,0.00015529092,0.000012355018,0.000067163746,0.0038367433],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9919906,0.0017800927,0.0019842633,0.0020781634,0.0011856512,0.000981198],"domain_scores_gemma":[0.985152,0.009980468,0.0008514448,0.0033121044,0.00036424503,0.00033975282],"candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.020974917,0.0004909721,0.0013043259,0.0010962215,0.00076452614,0.0015031011,0.0035993566,0.0007056993,0.00019490912],"category_scores_gemma":[0.010645485,0.00033968358,0.0004944139,0.00039539003,0.002655348,0.00024054,0.006116884,0.0035431564,0.0002075],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002518012,0.000093654744,0.0072627426,0.000006546389,0.00003573302,0.00004665548,0.0008003039,0.00392731,0.0000022521185,0.0003461506,0.0007811361,0.9864457],"study_design_scores_gemma":[0.00510856,0.00022863962,0.052759398,0.00026547082,0.000052259966,0.00022104636,0.003686249,0.08070683,0.000043405715,0.663438,0.19181497,0.0016751746],"about_ca_topic_score_codex":0.0007309674,"about_ca_topic_score_gemma":0.0009382397,"teacher_disagreement_score":0.98477054,"about_ca_system_score_codex":0.00053803454,"about_ca_system_score_gemma":0.0007072309,"threshold_uncertainty_score":0.9999055},"labels":[],"label_agreement":null},{"id":"W2139385563","doi":"10.2139/ssrn.2455861","title":"'And Lead Us Not into Temptation': Presentation Formats and the Choice of Risky Alternatives","year":2014,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Temptation; Lead (geology); Presentation (obstetrics); Business; Economics; Advertising; Psychology; Medicine; Social psychology","score_opus":0.05109051059846425,"score_gpt":0.3863922636890647,"score_spread":0.33530175309060045,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2139385563","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9852963,0.00047960572,0.012480267,0.0011579755,0.00016011618,0.00008789199,0.0000012635168,0.000005220995,0.00033133212],"genre_scores_gemma":[0.9983812,0.00082620664,0.00025937546,0.000103605955,0.0000947837,0.0000024999558,4.324405e-7,0.000006402616,0.0003255015],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99810666,0.00025853395,0.0005474908,0.00018349497,0.00047256384,0.00043125253],"domain_scores_gemma":[0.99733096,0.0017184198,0.0005356225,0.00018210613,0.00018488763,0.000048011],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006201576,0.00009544471,0.00022168916,0.00015772472,0.00026843074,0.00025929054,0.00037437404,0.00003384504,0.000009896665],"category_scores_gemma":[0.0017497382,0.000054368626,0.000067715046,0.00013656658,0.0002220303,0.00054977887,0.00007428581,0.00047156736,0.000014554258],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014907352,0.000018672446,0.017780399,0.0000015403615,0.000025265672,2.2651604e-7,0.0010173806,0.00012069788,0.00019831432,0.025772441,0.00004779178,0.9548682],"study_design_scores_gemma":[0.0014985418,0.00017745302,0.025511516,0.000012732788,0.000026081425,0.00009120162,0.0021906279,0.0068412693,0.0002879036,0.96200615,0.0012694226,0.00008709536],"about_ca_topic_score_codex":0.00025688077,"about_ca_topic_score_gemma":0.0010838151,"teacher_disagreement_score":0.9547811,"about_ca_system_score_codex":0.000092231574,"about_ca_system_score_gemma":0.0001805597,"threshold_uncertainty_score":0.25003445},"labels":[],"label_agreement":null},{"id":"W2139736626","doi":"10.1002/acp.915","title":"Associations between myside bias on an informal reasoning task and amount of post‐secondary education","year":2003,"lang":"en","type":"article","venue":"Applied Cognitive Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":137,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Hospital for Sick Children","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Psychology; Task (project management); Cognitive bias; Cognition; Social psychology; Cognitive psychology; Developmental psychology","score_opus":0.11122602273885301,"score_gpt":0.42982739081744586,"score_spread":0.31860136807859285,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2139736626","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90551835,0.000025086145,0.0005640123,0.00009112081,0.00026470222,0.00019992993,0.00022311693,0.000017558821,0.09309609],"genre_scores_gemma":[0.9970076,0.000007864062,0.0009970145,0.0017003225,0.000058795384,0.000021852407,0.00010471115,0.0000131635115,0.00008867894],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99800885,0.00018693999,0.0007406232,0.00051621726,0.00031270162,0.00023468689],"domain_scores_gemma":[0.99681056,0.0017156636,0.0005893641,0.0003369817,0.00041948745,0.00012791902],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019285437,0.00015925449,0.00038808025,0.00041172127,0.00016701248,0.00009680848,0.00024295528,0.00017975758,0.00022525633],"category_scores_gemma":[0.0018774865,0.00014239995,0.000062021434,0.00036002384,0.00017948248,0.0002557779,0.000041664676,0.0002607747,0.0002591339],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007006564,0.00021267943,0.042200778,7.557611e-7,0.000022012096,7.883743e-7,0.0008010142,0.0000018475768,0.00031012527,0.009093492,0.00044717963,0.9468393],"study_design_scores_gemma":[0.0008579232,0.00042907195,0.9012206,0.00001832356,0.000049234917,0.00001063714,0.0025863403,0.0000037407647,0.00064425706,0.08978019,0.004164511,0.00023512663],"about_ca_topic_score_codex":0.00003417945,"about_ca_topic_score_gemma":0.00004966633,"teacher_disagreement_score":0.94660413,"about_ca_system_score_codex":0.000021396012,"about_ca_system_score_gemma":0.00020392981,"threshold_uncertainty_score":0.58069015},"labels":[],"label_agreement":null},{"id":"W2139981419","doi":"10.1016/j.jet.2015.03.007","title":"Calibration without reduction for non-expected utility","year":2015,"lang":"en","type":"article","venue":"Journal of Economic Theory","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Expected utility hypothesis; Calibration; Axiom; Risk aversion (psychology); Econometrics; Mathematical economics; Economics; Decision maker; Reduction (mathematics); Prospect theory; Class (philosophy); Subjective expected utility; Computer science; Mathematics; Microeconomics; Statistics; Artificial intelligence","score_opus":0.19637265388168457,"score_gpt":0.4241549731591244,"score_spread":0.22778231927743986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2139981419","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96813726,0.000050212708,0.026523521,0.00029524195,0.003355872,0.00012842471,0.000014692752,0.000009757231,0.0014850298],"genre_scores_gemma":[0.9954983,0.000004076679,0.003129031,0.000045737248,0.00063217257,0.0000024585192,0.0000015724785,0.000012008567,0.00067465677],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9980584,0.00016040083,0.0012032954,0.0002323568,0.00020041289,0.00014517903],"domain_scores_gemma":[0.9972843,0.00060444296,0.0012026004,0.00035072357,0.00036725617,0.00019071045],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008450513,0.00011106193,0.00039757404,0.00028149653,0.0000757102,0.00023303852,0.0004956821,0.000093710434,0.00024095587],"category_scores_gemma":[0.0015473783,0.00008326928,0.00023474514,0.00007829398,0.0000809184,0.0009586161,0.00004409631,0.00013189067,0.00010018081],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0031605877,0.00024699853,0.0084859645,0.0000033364622,0.00007840181,0.000006099354,0.002242732,0.004474511,0.0009435218,0.007030042,0.081123784,0.89220405],"study_design_scores_gemma":[0.0013313208,0.00028919743,0.0013252575,0.00001847043,0.00003699392,0.00014888139,0.0033457088,0.009188572,0.0012144747,0.9696752,0.013266283,0.00015966166],"about_ca_topic_score_codex":0.000004568223,"about_ca_topic_score_gemma":0.000005652735,"teacher_disagreement_score":0.9626451,"about_ca_system_score_codex":0.00020800336,"about_ca_system_score_gemma":0.00038435767,"threshold_uncertainty_score":0.33956227},"labels":[],"label_agreement":null},{"id":"W2140237961","doi":"10.1007/s11002-005-5897-x","title":"The Psychology of Intertemporal Discounting: Why are Distant Events Valued Differently from Proximal Ones?","year":2005,"lang":"en","type":"article","venue":"Marketing Letters","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":253,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Time preference; Discounting; Intertemporal choice; Preference; Temporal discounting; Variety (cybernetics); Delay discounting; Function (biology); Economics; Psychology; Key (lock); Positive economics; Microeconomics; Computer science","score_opus":0.08003616924439622,"score_gpt":0.3722128846263321,"score_spread":0.2921767153819359,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2140237961","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9790306,0.00007950046,0.0011112832,0.018265864,0.000977415,0.00016247423,0.000028268463,0.000032278822,0.0003123063],"genre_scores_gemma":[0.9961876,0.0000062345716,0.0012591116,0.0021885955,0.00017973455,0.000011374599,0.0000064229075,0.000022878887,0.00013802861],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9963069,0.00064276654,0.0011774995,0.00066838623,0.0008082827,0.00039616248],"domain_scores_gemma":[0.9958574,0.0020871796,0.00094638835,0.00092539546,0.00009982957,0.000083795734],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0043853885,0.00022895068,0.00042928115,0.00014007924,0.0002647899,0.0002947714,0.0013824011,0.00008140316,0.00014570849],"category_scores_gemma":[0.0022158655,0.00013970469,0.0002429985,0.00023921019,0.00022540092,0.00023422603,0.00029894483,0.000260649,0.00008374119],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008386568,0.00020945266,0.652034,0.000003769341,0.000040057817,0.000012550254,0.0003847548,0.000023080347,0.00525369,0.00001902178,0.041313805,0.29986718],"study_design_scores_gemma":[0.0010548757,0.00005211741,0.9459797,0.0002239315,0.0000423431,0.000008219784,0.0016276332,0.0021006572,0.00022298568,0.0054112454,0.042840086,0.00043617797],"about_ca_topic_score_codex":0.000049939204,"about_ca_topic_score_gemma":0.00016949518,"teacher_disagreement_score":0.29943103,"about_ca_system_score_codex":0.00007063486,"about_ca_system_score_gemma":0.000017083375,"threshold_uncertainty_score":0.56969917},"labels":[],"label_agreement":null},{"id":"W2140580587","doi":"10.1037/bne0000037","title":"Age differences in strategy selection and risk preference during risk-based decision making.","year":2015,"lang":"en","type":"article","venue":"Behavioral Neuroscience","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; National Institutes of Health; Canadian Institutes of Health Research; Evelyn F. McKnight Brain Research Foundation","keywords":"Psychology; Preference; Odds; Delay discounting; Developmental psychology; Discounting; Certainty; Young adult; Risk aversion (psychology); Reinforcement; Cognitive psychology; Social psychology; Impulsivity; Expected utility hypothesis; Medicine; Internal medicine; Statistics; Logistic regression","score_opus":0.30336061822025306,"score_gpt":0.41082597411139476,"score_spread":0.1074653558911417,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2140580587","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9967422,0.000042968215,0.0019489146,0.000017304457,0.0007291122,0.0002875115,0.000045853696,0.000090693124,0.00009545039],"genre_scores_gemma":[0.99772334,0.0000415689,0.002037517,0.00003176267,0.000031607597,0.000022063894,7.737138e-7,0.000018456985,0.00009293038],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9949613,0.0004596692,0.0009793007,0.001482035,0.0015324644,0.00058520946],"domain_scores_gemma":[0.99747723,0.0006469939,0.0006423072,0.0006576815,0.00021944079,0.0003563226],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.002608456,0.00033822499,0.00049567764,0.0007488379,0.0004419091,0.0012625216,0.0012055899,0.00016354804,0.000037877402],"category_scores_gemma":[0.0028870397,0.00026508883,0.00009333765,0.0017340104,0.0003609739,0.0010310584,0.0003340312,0.0005699463,0.000056639732],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011724294,0.00019378512,0.7821621,8.8538184e-7,2.202011e-7,0.000058190526,0.00013215898,0.0023037908,0.00072465895,0.000009684243,0.000040151193,0.21425715],"study_design_scores_gemma":[0.0007187387,0.0005228473,0.9671719,0.000050841245,0.00001829198,0.000031207306,0.00022029271,0.019545017,0.00027765473,0.010973825,0.0001210701,0.00034833435],"about_ca_topic_score_codex":0.0005427744,"about_ca_topic_score_gemma":0.002024953,"teacher_disagreement_score":0.21390882,"about_ca_system_score_codex":0.00013005752,"about_ca_system_score_gemma":0.0002188968,"threshold_uncertainty_score":0.99998015},"labels":[],"label_agreement":null},{"id":"W2141141748","doi":"10.1037/xge0000046","title":"Priming memories of past wins induces risk seeking.","year":2014,"lang":"en","type":"article","venue":"Journal of Experimental Psychology General","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":78,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Alberta Gambling Research Institute, University of Calgary; Natural Sciences and Engineering Research Council of Canada","keywords":"Priming (agriculture); Psychology; Risk-seeking; Task (project management); Social psychology; Cognitive psychology","score_opus":0.12415944770800594,"score_gpt":0.45541992137930165,"score_spread":0.33126047367129574,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2141141748","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9914152,0.00038098946,0.0014727077,0.00030573964,0.0033491745,0.00005176771,0.0000063078905,0.0000071694594,0.0030109123],"genre_scores_gemma":[0.98956144,0.000019057163,0.009053334,0.00045509267,0.0007810707,0.0000012340575,6.1093647e-7,0.000015437035,0.00011275347],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9967949,0.00043357487,0.0015240994,0.00033153206,0.00067189726,0.0002440193],"domain_scores_gemma":[0.9967686,0.0004637757,0.0018784429,0.00047589786,0.00026324872,0.00015002053],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034580526,0.0001834565,0.0006195696,0.0004372264,0.0001580864,0.000103820144,0.0009651683,0.00020411934,0.00030505584],"category_scores_gemma":[0.0006056721,0.00013184702,0.00031445056,0.00025724326,0.00027671622,0.0003873076,0.00013458266,0.0005053645,0.0000476992],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00059234194,0.00097349554,0.06930451,0.0000016172838,0.00009667988,0.000034910347,0.003734896,0.00036532606,0.5949781,0.00033747626,0.022272518,0.30730814],"study_design_scores_gemma":[0.009502502,0.009367549,0.20942646,0.00018193327,0.0002119372,0.0022440662,0.013916742,0.0013058523,0.56880784,0.09222536,0.09134341,0.0014663528],"about_ca_topic_score_codex":0.000010127637,"about_ca_topic_score_gemma":0.0000032632108,"teacher_disagreement_score":0.30584177,"about_ca_system_score_codex":0.000044208333,"about_ca_system_score_gemma":0.00004191985,"threshold_uncertainty_score":0.5376565},"labels":[],"label_agreement":null},{"id":"W2141733736","doi":"","title":"Harsanyi’s Social Aggregation Theorem : A Multi-Profile Approach with Variable-Population Extensions","year":2003,"lang":"en","type":"article","venue":"Papyrus : Institutional Repository (Université de Montréal)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Variable (mathematics); Social choice theory; Mathematical economics; Utilitarianism; Population; Mathematics; Economics; Ex-ante; Econometrics; Sociology; Political science; Law; Demography","score_opus":0.035875470955354184,"score_gpt":0.24486806541656725,"score_spread":0.20899259446121307,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2141733736","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93085647,0.00040141813,0.0343137,0.00011089856,0.00042885327,0.00032039758,0.000043901022,0.00011365895,0.033410687],"genre_scores_gemma":[0.96314824,0.0000072693956,0.030044653,0.00008189147,0.000060590643,0.000015282762,0.000043743003,0.00001796237,0.0065803765],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99726844,0.00028029823,0.00047945365,0.0007114849,0.0009257694,0.0003345463],"domain_scores_gemma":[0.9982442,0.0002481294,0.0004095548,0.00048548076,0.00040910474,0.00020350465],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0009871422,0.00024952236,0.00032465067,0.00032860847,0.0065916856,0.00020753607,0.00042996602,0.00020945004,0.00013748136],"category_scores_gemma":[0.0004020406,0.00020840499,0.00016632187,0.00071767805,0.00023373973,0.0007099073,0.000120110606,0.00022897717,0.000107257896],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018262577,0.0021354654,0.16560192,0.000028698352,0.00029630875,0.0010888221,0.028624598,0.043194495,0.008689104,0.48278877,0.005234996,0.26049057],"study_design_scores_gemma":[0.011843398,0.0006163315,0.49045005,0.00028801442,0.0008577652,0.005666757,0.0818403,0.11883039,0.0047733397,0.121947624,0.1592389,0.0036471335],"about_ca_topic_score_codex":0.002544406,"about_ca_topic_score_gemma":0.00039465338,"teacher_disagreement_score":0.36084116,"about_ca_system_score_codex":0.0015919945,"about_ca_system_score_gemma":0.0005855445,"threshold_uncertainty_score":0.9947016},"labels":[],"label_agreement":null},{"id":"W2141956557","doi":"10.3758/bf03195278","title":"The inverse fallacy: An account of deviations from Bayes’s theorem and the additivity principle","year":2002,"lang":"en","type":"article","venue":"Memory & Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":127,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Additive function; Conditional probability; Fallacy; Inverse; Bayesian probability; Bayes' theorem; Generalization; Normative; Mathematical economics; Posterior probability; Psychology; Chain rule (probability); Econometrics; Mathematics; Statistics; Law of total probability; Epistemology; Mathematical analysis; Philosophy","score_opus":0.11986455281691656,"score_gpt":0.35638252002149096,"score_spread":0.2365179672045744,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2141956557","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9914696,0.000087485016,0.00052932516,0.0007476951,0.00025514243,0.0002348024,0.00024121073,0.000023533888,0.0064111957],"genre_scores_gemma":[0.9990202,0.00008159262,0.00017781823,0.0003123546,0.00008708278,0.000022016948,0.000020891852,0.000008192804,0.0002698467],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99815,0.00040756149,0.0004823019,0.0003203159,0.0004977496,0.00014210636],"domain_scores_gemma":[0.9949104,0.0038265826,0.00033656275,0.0005828241,0.0002820363,0.00006157526],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026748588,0.00011199259,0.00020513395,0.00007176991,0.0005127958,0.0003370658,0.00042677418,0.00006325745,0.00090648123],"category_scores_gemma":[0.0022773317,0.000058475514,0.00009096932,0.0002215236,0.0004728752,0.00047067786,0.0001275898,0.00013528427,0.00027335162],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017343333,0.00017584045,0.0011082826,0.0000013334974,0.000023278968,0.000003334813,0.0019449211,0.00003883654,0.0005681619,0.0021490664,0.004474085,0.9893394],"study_design_scores_gemma":[0.0026424727,0.00012668432,0.06560879,0.000050489583,0.00017612256,0.000014798351,0.0058486066,0.026400967,0.0016369206,0.8681514,0.028986229,0.00035646404],"about_ca_topic_score_codex":0.00006704578,"about_ca_topic_score_gemma":0.001172153,"teacher_disagreement_score":0.988983,"about_ca_system_score_codex":0.00002384906,"about_ca_system_score_gemma":0.000024871148,"threshold_uncertainty_score":0.9925334},"labels":[],"label_agreement":null},{"id":"W2143177887","doi":"10.1016/j.cogpsych.2011.06.001","title":"Intuition, reason, and metacognition","year":2011,"lang":"en","type":"article","venue":"Cognitive Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":694,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Metacognition; Psychology; Cognitive psychology; Intuition; Metamemory; Feeling; Task (project management); Fluency; Cognition; Social psychology; Cognitive science; Mathematics education","score_opus":0.511818764827479,"score_gpt":0.4999096014207356,"score_spread":0.011909163406743417,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2143177887","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.88783777,0.0001770862,0.018983204,0.00020148026,0.00064836856,0.00013727065,0.000039132912,0.000047104746,0.09192858],"genre_scores_gemma":[0.9964789,0.000063293905,0.001284682,0.0018580573,0.00006689907,0.000023189663,0.000009637178,0.00001262421,0.00020268987],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99813807,0.00022725936,0.0005023936,0.00067900494,0.00023062843,0.00022261476],"domain_scores_gemma":[0.99812,0.00068830216,0.00021690932,0.00029564695,0.0005467806,0.00013233421],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0013995792,0.00014437425,0.00027483384,0.00032844674,0.00012560208,0.00007924783,0.00026594306,0.0001387086,0.0029327385],"category_scores_gemma":[0.0020354288,0.00011692262,0.000076813456,0.00033384992,0.00034946387,0.00030415365,0.000096954565,0.00016010698,0.0024237868],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013129028,0.00012845451,0.009565426,4.944856e-7,0.000013484178,0.000024079229,0.00060121896,1.2143834e-8,0.00010274562,0.0009171009,0.0031401073,0.9853756],"study_design_scores_gemma":[0.00074241724,0.00027900757,0.20765626,0.00002038353,0.00004862892,0.00014784354,0.0007786972,0.000012552005,0.00037390983,0.78379893,0.00593776,0.00020358553],"about_ca_topic_score_codex":0.000009807197,"about_ca_topic_score_gemma":0.000018120227,"teacher_disagreement_score":0.985172,"about_ca_system_score_codex":0.000008699077,"about_ca_system_score_gemma":0.000016956723,"threshold_uncertainty_score":0.99835294},"labels":[],"label_agreement":null},{"id":"W2144032325","doi":"10.1177/0886368709341860","title":"Pay for Performance—Panacea or Pandora’s Box? Revisiting an Old Debate in the Current Economic Environment","year":2009,"lang":"en","type":"article","venue":"Compensation & Benefits Review","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Panacea (medicine); Economics; Current (fluid); Public economics; Business; Engineering","score_opus":0.2258718516793867,"score_gpt":0.41508956229201016,"score_spread":0.18921771061262346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2144032325","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9652915,0.025352683,0.0005495389,0.0060713557,0.00051497633,0.0019103272,0.00006116019,0.00003518093,0.00021328496],"genre_scores_gemma":[0.9209656,0.07422611,0.0010806179,0.0031902865,0.00022406588,0.00010486958,0.00008311449,0.000018407216,0.000106885476],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9969001,0.00024171328,0.0014890803,0.00063043117,0.00043663336,0.0003020346],"domain_scores_gemma":[0.9974386,0.0008242629,0.0006357217,0.0009316647,0.00007449295,0.000095260366],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005591047,0.00023675672,0.0006707138,0.00017573414,0.00022904549,0.00031787815,0.0009509354,0.00004730546,0.0004174983],"category_scores_gemma":[0.00042134945,0.00012481806,0.00019365037,0.0002398698,0.000027007598,0.0005765931,0.000058865113,0.00018685972,0.00042629841],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019887544,0.000049003072,0.0008719194,0.000034841327,0.0000019730276,6.920035e-7,0.00009617805,0.0017202433,0.0000023216526,0.00055058545,0.0007974686,0.9958549],"study_design_scores_gemma":[0.00095838815,0.00049331714,0.10122135,0.003457091,0.00014917448,0.000028493025,0.00012938929,0.029002413,0.00001583454,0.0067271823,0.85718566,0.00063172687],"about_ca_topic_score_codex":0.000005583871,"about_ca_topic_score_gemma":0.000036409365,"teacher_disagreement_score":0.99522316,"about_ca_system_score_codex":0.00017635271,"about_ca_system_score_gemma":0.000077919605,"threshold_uncertainty_score":0.5479346},"labels":[],"label_agreement":null},{"id":"W2144066648","doi":"10.3389/fpsyg.2014.01144","title":"The psychology of Bayesian reasoning","year":2014,"lang":"en","type":"article","venue":"Frontiers in Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":42,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada; York University","funders":"","keywords":"Psychology; Cognition; Bayesian probability; Cognitive science; Cognitive psychology; Artificial intelligence; Psychiatry; Computer science","score_opus":0.06115652445867438,"score_gpt":0.42475486965663534,"score_spread":0.36359834519796097,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2144066648","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.52139986,0.0007017258,0.40368772,0.0043594223,0.011794904,0.00017968375,0.0000058682554,0.000033587818,0.057837244],"genre_scores_gemma":[0.95961076,0.0001256625,0.03840633,0.0014700606,0.000089169494,0.000011952772,0.0000011654442,0.00001753916,0.0002673893],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99717003,0.00052180135,0.0009958227,0.00061492546,0.00031694336,0.0003805006],"domain_scores_gemma":[0.9972051,0.00085225306,0.0004138683,0.0013529512,0.00009898073,0.000076842516],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005180096,0.00013936295,0.00045302627,0.0004151357,0.0001264289,0.000060109447,0.0015781714,0.00021465025,0.00008495148],"category_scores_gemma":[0.0022120045,0.000092667884,0.00012779397,0.0006216053,0.0004777853,0.000098431046,0.000092024056,0.00028299482,0.00011590444],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000086159605,0.000042149088,0.091517635,2.7831157e-7,0.000004590155,0.0000026374653,0.00007123787,0.000012281919,0.000032151773,0.0009155966,0.12305263,0.78426266],"study_design_scores_gemma":[0.0005740476,0.00013071448,0.055771247,0.000009727143,0.0000046791256,0.00002157511,0.0002266065,0.0014091154,0.000013194069,0.6188095,0.32291257,0.00011697518],"about_ca_topic_score_codex":0.000010459728,"about_ca_topic_score_gemma":0.000042886375,"teacher_disagreement_score":0.78414565,"about_ca_system_score_codex":0.000020624193,"about_ca_system_score_gemma":0.000021936601,"threshold_uncertainty_score":0.37788868},"labels":[],"label_agreement":null},{"id":"W2144130856","doi":"10.1111/j.1467-9280.2009.02453.x","title":"Order in Choice","year":2009,"lang":"en","type":"article","venue":"Psychological Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":190,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Vineland Research and Innovation Centre; Brock University","funders":"","keywords":"Sequence (biology); Psychology; Wine tasting; Sequence learning; Wine; Cognitive psychology; Process (computing); Order (exchange); Social psychology; Computer science; Economics","score_opus":0.2702629065633216,"score_gpt":0.5464889363158811,"score_spread":0.27622602975255955,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2144130856","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93535763,0.000019258912,0.00037249282,0.00265999,0.00053868495,0.00007688679,7.4585637e-7,0.00003684458,0.060937468],"genre_scores_gemma":[0.99461174,0.0000042832075,0.0025723104,0.0024942923,0.00004950604,0.0000021918213,1.1634818e-7,0.000001646426,0.00026389322],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9970015,0.00005977439,0.0005193457,0.0009431013,0.0010295901,0.00044668146],"domain_scores_gemma":[0.998298,0.0005446188,0.00011141291,0.00068109,0.00017319601,0.00019170373],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0046423012,0.00010780827,0.00020570784,0.00033439408,0.00016522351,0.00043704666,0.0021609992,0.000076567645,0.0008688494],"category_scores_gemma":[0.006994028,0.000065335844,0.00005209835,0.0039593065,0.000451941,0.00053090684,0.0000784737,0.00020033754,0.0014861192],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010022778,0.00021494771,0.01690042,3.699625e-8,7.62752e-8,0.000012393163,0.00004134053,0.00012489222,0.0011981372,0.0009306175,0.0013670187,0.9792001],"study_design_scores_gemma":[0.00018043368,0.00016818572,0.727708,0.0000041856506,4.2649785e-7,0.000011501824,0.000030715342,0.0004697464,0.00005405947,0.26131052,0.009939767,0.0001224879],"about_ca_topic_score_codex":0.000013455175,"about_ca_topic_score_gemma":0.000016405927,"teacher_disagreement_score":0.97907764,"about_ca_system_score_codex":0.00005487398,"about_ca_system_score_gemma":0.00003202224,"threshold_uncertainty_score":0.99929136},"labels":[],"label_agreement":null},{"id":"W2144442684","doi":"10.2139/ssrn.770964","title":"Ellsberg Revisited: An Experimental Study","year":2005,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":49,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Economics; Mathematical economics; Econometrics","score_opus":0.08411198479871994,"score_gpt":0.42033513956677365,"score_spread":0.3362231547680537,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2144442684","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99568665,0.0013096618,0.00057566684,0.00031092262,0.00032140955,0.00015769813,0.0000020695,0.000037937432,0.0015980117],"genre_scores_gemma":[0.9966049,0.00011684696,0.0002939571,0.00017882306,0.00070509117,0.000003556658,0.0000010326128,0.00002469676,0.0020710484],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99547046,0.000299117,0.0009465123,0.0005424725,0.0010735757,0.0016678836],"domain_scores_gemma":[0.9983884,0.0001683413,0.00037150705,0.0006647851,0.00018082657,0.00022610537],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.009075159,0.00021491408,0.00035828704,0.00035118355,0.00041999907,0.0006937606,0.0013299955,0.00007792097,0.00078958715],"category_scores_gemma":[0.00025965655,0.00015847795,0.00019361901,0.00039934262,0.000047139012,0.0011121611,0.0001237192,0.0012931047,0.0013808836],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010127189,0.0017534968,0.0073086857,1.0433918e-7,0.000031709824,0.000015018571,0.0008953932,0.0002113837,0.0005648598,0.0035509423,0.00094477006,0.98462236],"study_design_scores_gemma":[0.004319823,0.010115483,0.0033819096,0.000025323106,0.000106682346,0.002736343,0.10997098,0.001642061,0.0011795849,0.7762491,0.0889829,0.001289791],"about_ca_topic_score_codex":0.000022638867,"about_ca_topic_score_gemma":0.0004932261,"teacher_disagreement_score":0.9833326,"about_ca_system_score_codex":0.00092169887,"about_ca_system_score_gemma":0.0007375531,"threshold_uncertainty_score":0.9993967},"labels":[],"label_agreement":null},{"id":"W2145230123","doi":"10.1016/j.mathsocsci.2012.04.002","title":"Expected multi-utility representations","year":2012,"lang":"en","type":"article","venue":"Mathematical Social Sciences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Expected utility hypothesis; Von Neumann–Morgenstern utility theorem; Subjective expected utility; Constructive; Mathematical economics; Utility theory; Von Neumann architecture; Regular polygon; Mathematics; Computer science; Pure mathematics","score_opus":0.5449282112151731,"score_gpt":0.5456047661647843,"score_spread":0.0006765549496111634,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2145230123","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9372775,0.000030510735,0.014247752,0.0011082914,0.00044553785,0.00014793414,0.00001202325,0.000082266844,0.046648208],"genre_scores_gemma":[0.9855073,5.4421736e-7,0.013566548,0.00013077963,0.00017749394,0.000014172362,7.3793865e-7,0.0000049670807,0.0005974716],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9970707,0.0002015065,0.0006679981,0.000393052,0.0011944388,0.00047224812],"domain_scores_gemma":[0.99754906,0.0016633952,0.00020474957,0.00028957683,0.00012253346,0.00017071432],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0049407687,0.00012146727,0.0002927932,0.00012285155,0.0009790709,0.00046952,0.0008786733,0.000089387744,0.0044647446],"category_scores_gemma":[0.0055610402,0.00007989586,0.00017137725,0.0010659221,0.00080007577,0.00071355456,0.00021774913,0.000111716785,0.0022742404],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019502613,0.002369085,0.13687336,0.000007760769,0.000017996372,0.000004176159,0.020078728,0.000013770521,0.00041921707,0.19841251,0.03152014,0.61026376],"study_design_scores_gemma":[0.00022146267,0.00003103133,0.084269606,0.000008331755,0.000017297481,0.000008242848,0.009295719,0.0033818015,0.00019166135,0.89503706,0.007246578,0.00029119113],"about_ca_topic_score_codex":0.000028421495,"about_ca_topic_score_gemma":0.000014980162,"teacher_disagreement_score":0.6966246,"about_ca_system_score_codex":0.00003664483,"about_ca_system_score_gemma":0.000049061913,"threshold_uncertainty_score":0.9985026},"labels":[],"label_agreement":null},{"id":"W2147458801","doi":"10.1177/0886368707302528","title":"The Motivational Properties of Tangible Incentives","year":2007,"lang":"en","type":"article","venue":"Compensation & Benefits Review","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":83,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Incentive; Business; Marketing; Public economics; Microeconomics; Economics","score_opus":0.23361074051291872,"score_gpt":0.3968952069892371,"score_spread":0.16328446647631836,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2147458801","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.898326,0.09506091,0.0010291142,0.0018686955,0.0004840646,0.0004602353,0.000009062849,0.000025580695,0.0027363384],"genre_scores_gemma":[0.9901389,0.008571104,0.00045899992,0.0003841444,0.00004654295,0.0000069674247,0.0000039079628,0.0000075681196,0.0003819026],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99750495,0.00010321143,0.0011578967,0.00025788546,0.00080654817,0.00016951736],"domain_scores_gemma":[0.99699086,0.0010486953,0.0005988354,0.00050748436,0.00079805497,0.000056093577],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0055050747,0.00011033209,0.00031655355,0.0001050228,0.00024759286,0.00011843413,0.00064176554,0.00003635044,0.00021130488],"category_scores_gemma":[0.0025925105,0.000059960275,0.00014467283,0.0006164481,0.00013309733,0.00026491904,0.00011873444,0.00007996309,0.00027412386],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011880695,0.000034681012,0.0022429845,0.000029166886,0.0000053131853,2.868269e-7,0.000054913926,0.00006199286,0.00028460607,0.011727752,0.0016171492,0.9839293],"study_design_scores_gemma":[0.0005731726,0.0001367304,0.17003421,0.0063910405,0.000080963044,0.000026649066,0.0006117972,0.00066414516,0.0075321766,0.0546631,0.75870955,0.0005764844],"about_ca_topic_score_codex":0.000006496007,"about_ca_topic_score_gemma":0.00002938218,"teacher_disagreement_score":0.9833528,"about_ca_system_score_codex":0.000039263396,"about_ca_system_score_gemma":0.00006664054,"threshold_uncertainty_score":0.35233992},"labels":[],"label_agreement":null},{"id":"W2147624599","doi":"10.7202/602326ar","title":"L’importance de la procédure dans les choix de loteries","year":2009,"lang":"fr","type":"article","venue":"L Actualité économique","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Humanities; Philosophy; Physics","score_opus":0.09819825367198326,"score_gpt":0.37676073834902857,"score_spread":0.2785624846770453,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2147624599","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9651395,0.0010679528,0.005805628,0.009806594,0.0005714073,0.00028029838,0.0001258083,0.00012957046,0.017073216],"genre_scores_gemma":[0.9688033,0.0005501973,0.011173985,0.0034318238,0.0005530392,0.00002539269,0.000008313016,0.000046104225,0.015407837],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9959533,0.00065478886,0.0012958719,0.0009790916,0.0001955806,0.00092137087],"domain_scores_gemma":[0.99562687,0.0021109104,0.0005790872,0.0010611074,0.00014269025,0.0004793484],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0038046376,0.0004998902,0.0007332328,0.00020810471,0.00037023422,0.0012762068,0.0014146812,0.0007197886,0.0011948764],"category_scores_gemma":[0.0022425677,0.0004742628,0.0003703805,0.00033057158,0.0006535814,0.0009649066,0.00015218457,0.0006861467,0.00048573397],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011262017,0.0003736559,0.033627473,0.00001641595,0.000023555138,0.00016454185,0.0061403033,0.0007539281,0.0014747004,0.029599158,0.007403125,0.9203105],"study_design_scores_gemma":[0.00048195885,0.00028775664,0.06364257,0.0001859282,0.000053064858,0.00042664257,0.0018006974,0.0016304987,0.0030515755,0.4354924,0.49225527,0.0006916387],"about_ca_topic_score_codex":0.0007040475,"about_ca_topic_score_gemma":0.00075152394,"teacher_disagreement_score":0.9196189,"about_ca_system_score_codex":0.0007474273,"about_ca_system_score_gemma":0.0010086548,"threshold_uncertainty_score":0.9997709},"labels":[],"label_agreement":null},{"id":"W2147664728","doi":"10.1287/mksc.1060.0254","title":"Zero as a Special Price: The True Value of Free Products","year":2007,"lang":"en","type":"article","venue":"Marketing Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":612,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Zero (linguistics); Value (mathematics); Economics; Microeconomics; Affect (linguistics); Test (biology); Contrast (vision); Perspective (graphical); Set (abstract data type); Marketing; Business; Mathematics; Computer science; Statistics; Psychology","score_opus":0.0584662893362493,"score_gpt":0.3772242976406483,"score_spread":0.318758008304399,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2147664728","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90752476,0.000028511562,0.0005173541,0.0010080438,0.0018118895,0.00018404466,0.000006199311,0.000023736857,0.08889546],"genre_scores_gemma":[0.9931737,0.000002631696,0.004687956,0.00019135381,0.00048446443,0.0000017898773,1.4722278e-7,0.000008032152,0.0014499218],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9950479,0.00019830865,0.00092070346,0.00082555576,0.0024558625,0.00055162166],"domain_scores_gemma":[0.9917468,0.00490186,0.00062331586,0.0018314753,0.00074319995,0.00015336437],"candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.06653059,0.00014545502,0.00025127368,0.00039119984,0.00062491925,0.00050238165,0.0041940324,0.00005523466,0.00030522177],"category_scores_gemma":[0.07851387,0.00008671562,0.00009511658,0.003254998,0.0013236656,0.00047171657,0.000795167,0.00020563994,0.00022325813],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002434413,0.00013054146,0.0114626,0.0000047579356,0.0000030767496,0.000021420597,0.0011886561,0.0001397639,0.012262005,0.0056732213,0.020598583,0.94827193],"study_design_scores_gemma":[0.00066166086,0.0002448138,0.5622595,0.00013836734,0.000023131854,0.00013959636,0.0029829158,0.0014095342,0.023917694,0.24646088,0.16113058,0.0006313267],"about_ca_topic_score_codex":0.00003523433,"about_ca_topic_score_gemma":0.00002497038,"teacher_disagreement_score":0.9476406,"about_ca_system_score_codex":0.00008788468,"about_ca_system_score_gemma":0.0004580683,"threshold_uncertainty_score":0.9612032},"labels":[],"label_agreement":null},{"id":"W2148025462","doi":"10.1080/00223891.2014.976791","title":"The Statistical Developments and Applications Reference List","year":2014,"lang":"en","type":"article","venue":"Journal of Personality Assessment","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; University of Toronto","funders":"","keywords":"Psychology; Library science; Behavioural sciences; Psychometrics; Applied psychology; Clinical psychology; Computer science; Psychotherapist","score_opus":0.15318348383866287,"score_gpt":0.4741059062348594,"score_spread":0.3209224223961965,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2148025462","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7868162,0.00009903229,0.1990423,0.0035899007,0.0004063024,0.00014033548,0.000033104516,0.000007247274,0.00986561],"genre_scores_gemma":[0.98066616,0.000037596186,0.018753177,0.00019002224,0.00011081005,0.0000047135723,0.0000010153277,0.0000038396856,0.00023269412],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9977115,0.00023153897,0.0007884791,0.00018195194,0.00094764313,0.00013889262],"domain_scores_gemma":[0.99586123,0.0027450507,0.00055846106,0.00023958353,0.00044136817,0.00015427644],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0067779515,0.000083815066,0.00021938814,0.00006333637,0.0003678917,0.00056266435,0.00052425935,0.00003967789,0.00012070575],"category_scores_gemma":[0.0008374766,0.000046337533,0.00005205644,0.00012608335,0.00015431226,0.00017136551,0.00010259797,0.00023896743,0.000026368565],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018022447,0.00007140585,0.021740898,0.0000015797563,0.000012882233,0.00000219435,0.00007935518,0.000007488123,0.000039459203,0.033421393,0.0032456173,0.9413597],"study_design_scores_gemma":[0.00023975667,0.000099123965,0.2798374,0.000012552634,0.000017753167,0.000050825172,0.0006527252,0.000523898,0.0000059471827,0.1559474,0.56252366,0.00008893003],"about_ca_topic_score_codex":0.00001253538,"about_ca_topic_score_gemma":0.000042646025,"teacher_disagreement_score":0.94127077,"about_ca_system_score_codex":0.00009599046,"about_ca_system_score_gemma":0.00020962076,"threshold_uncertainty_score":0.5425785},"labels":[],"label_agreement":null},{"id":"W2148104117","doi":"10.1177/1555343414554702","title":"Personality, Cognitive Style, Motivation, and Aptitude Predict Systematic Trends in Analytic Forecasting Behavior","year":2014,"lang":"en","type":"article","venue":"Journal of Cognitive Engineering and Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Intelligence Advanced Research Projects Activity; Interior Business Center; University of Toronto; U.S. Department of the Interior","keywords":"Aptitude; Psychology; Personality; Cognition; Big Five personality traits; Psychometrics; Cognitive style; Sample (material); Cognitive psychology; Social psychology; Developmental psychology","score_opus":0.08933300199234538,"score_gpt":0.36104520688486064,"score_spread":0.27171220489251524,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2148104117","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9139345,0.00034771254,0.0850779,0.000018316541,0.00027704463,0.00014623793,0.000012756926,0.000014217342,0.0001712625],"genre_scores_gemma":[0.9964452,0.000017844779,0.00330826,0.000044910263,0.00013187787,0.000007803668,0.0000010827105,0.00002375341,0.000019278517],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99628764,0.0001700468,0.0017587502,0.00042814293,0.0010694291,0.00028600724],"domain_scores_gemma":[0.98114353,0.016656866,0.0009929342,0.00016169142,0.00085227215,0.00019267596],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.006052542,0.00027540582,0.0009255811,0.001936893,0.00013081954,0.0005029243,0.00026422326,0.00012655692,0.000048020112],"category_scores_gemma":[0.027863681,0.00020946974,0.00017991765,0.0008559826,0.00007501059,0.00064868276,0.00015302395,0.00041141125,0.0000048385004],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021659269,0.00013324415,0.08977061,0.00014275195,0.000059366506,0.00014125626,0.0012385934,0.0023488584,0.00003599225,0.000081759434,0.000035983507,0.905795],"study_design_scores_gemma":[0.0033861098,0.0007370472,0.6341968,0.028336246,0.0005175918,0.0014452183,0.004038861,0.3149207,0.000019626505,0.011743304,0.000022610177,0.00063583755],"about_ca_topic_score_codex":0.0000032674754,"about_ca_topic_score_gemma":0.000010949105,"teacher_disagreement_score":0.9051592,"about_ca_system_score_codex":0.00006550106,"about_ca_system_score_gemma":0.00003085814,"threshold_uncertainty_score":0.98032504},"labels":[],"label_agreement":null},{"id":"W2148627868","doi":"10.1016/j.obhdp.2011.08.003","title":"Wolves in sheep’s clothing: How and when hypothetical questions influence behavior","year":2011,"lang":"en","type":"article","venue":"Organizational Behavior and Human Decision Processes","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Psychology; Consistency (knowledge bases); Clothing; Social psychology; Elaboration; Consumption (sociology); Voting; Cognitive psychology; Computer science","score_opus":0.10346009134150429,"score_gpt":0.3518660322923991,"score_spread":0.2484059409508948,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2148627868","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99795395,0.00025699107,0.0006896241,0.00015972716,0.00014122725,0.00032031865,0.000042406024,0.0000774761,0.0003582905],"genre_scores_gemma":[0.99234325,0.00007725881,0.0068045408,0.00013675108,0.000040088908,0.00006843124,0.000012516376,0.000043955533,0.00047321993],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9966752,0.00007900901,0.0009344142,0.0010046886,0.0009729353,0.0003337887],"domain_scores_gemma":[0.9970465,0.00084638107,0.00027599384,0.0005047106,0.0010309739,0.0002954747],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009717865,0.00032866574,0.00045998895,0.00072039774,0.0005351626,0.00096614094,0.0007227238,0.00023668939,0.0014778522],"category_scores_gemma":[0.003506667,0.00027082526,0.000050026352,0.00086557673,0.00046225704,0.0012886625,0.0003890804,0.00028148628,0.000081776816],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000034235753,0.00064945675,0.9154149,0.00000819281,0.0000031324053,0.000062176165,0.0018974605,0.0000034898467,0.0007512363,0.0066124294,0.0003909544,0.07417229],"study_design_scores_gemma":[0.00052441185,0.00014541538,0.829697,0.000093641436,0.00006434293,0.00013245278,0.0005753733,0.000007782687,0.00044120656,0.16686939,0.0010434577,0.00040552422],"about_ca_topic_score_codex":0.000057853445,"about_ca_topic_score_gemma":0.00029688617,"teacher_disagreement_score":0.16025697,"about_ca_system_score_codex":0.00005172553,"about_ca_system_score_gemma":0.0001824144,"threshold_uncertainty_score":0.99997437},"labels":[],"label_agreement":null},{"id":"W2149255028","doi":"10.1111/j.1754-9434.2010.01272.x","title":"Taking Workplace Decisions Seriously: This Conversation Has Been Fruitful!","year":2010,"lang":"en","type":"article","venue":"Industrial and Organizational Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Constructive; Conversation; Field (mathematics); Psychology; Social psychology; Applied psychology; Epistemology; Computer science","score_opus":0.2565953050500834,"score_gpt":0.40951454955406413,"score_spread":0.15291924450398076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2149255028","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97750825,0.00001995555,0.0018878699,0.011751326,0.004730134,0.00019019004,0.000047546422,0.00006470186,0.0038000075],"genre_scores_gemma":[0.9951249,0.000010452106,0.0016160802,0.00144682,0.00094030926,0.000004352345,0.00003679619,0.00002434824,0.00079593784],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9975163,0.0001375833,0.000787147,0.0007236396,0.0005689759,0.00026639045],"domain_scores_gemma":[0.9965436,0.0018431538,0.0004687431,0.00050136977,0.0004415853,0.0002015757],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0016097212,0.00019469272,0.00033006127,0.00035835826,0.00045461263,0.00051263475,0.0006241321,0.000578298,0.012028067],"category_scores_gemma":[0.008378645,0.00016043716,0.000064776075,0.0009905508,0.00032281043,0.0003387747,0.00018300935,0.0006138955,0.0011542856],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018869592,0.00016656387,0.18731484,3.518279e-7,0.00002654179,0.000021033775,0.0007595149,0.000035035253,0.003277831,0.006067339,0.09158368,0.7105586],"study_design_scores_gemma":[0.004259579,0.0002616028,0.14184606,0.000031226627,0.000063328574,0.00038124187,0.0005174993,0.000471427,0.00048909296,0.32084492,0.53004974,0.00078428723],"about_ca_topic_score_codex":0.000041206753,"about_ca_topic_score_gemma":0.0001274075,"teacher_disagreement_score":0.7097743,"about_ca_system_score_codex":0.000025512058,"about_ca_system_score_gemma":0.00020523828,"threshold_uncertainty_score":0.9999742},"labels":[],"label_agreement":null},{"id":"W2149442301","doi":"10.1080/02724980543000033","title":"It looks easy! Heuristics for combinatorial optimization problems","year":2005,"lang":"en","type":"article","venue":"Quarterly Journal of Experimental Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Heuristics; Heuristic; Boundary (topology); Mathematical optimization; Computer science; Simple (philosophy); Combinatorial optimization; Optimization problem; Artificial intelligence; Mathematics","score_opus":0.12181949981586823,"score_gpt":0.4537068838271673,"score_spread":0.331887384011299,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2149442301","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8288209,0.00083824055,0.14819944,0.0033231394,0.012833398,0.0005151333,0.000029850673,0.000028642013,0.005411247],"genre_scores_gemma":[0.9693294,0.000007886004,0.028645527,0.00086287776,0.0009317479,0.000009191494,0.0000031010022,0.000023074923,0.00018716104],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9971289,0.0001353787,0.0015936411,0.000345474,0.00052158243,0.00027499197],"domain_scores_gemma":[0.9975433,0.0004250155,0.0010325413,0.000374618,0.00044839253,0.00017614561],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016258571,0.00018222314,0.00046757943,0.00026579495,0.00012866971,0.0002240031,0.0007827624,0.0001659099,0.0008197807],"category_scores_gemma":[0.00018268984,0.00014583085,0.0002737536,0.00015958074,0.00012560209,0.00046760117,0.000021615082,0.00019821018,0.00018058263],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0026327467,0.004501329,0.0006925287,0.0000045761662,0.000113711925,0.00005432459,0.0075395075,0.018971682,0.018404853,0.002043456,0.23977429,0.705267],"study_design_scores_gemma":[0.027006889,0.040498722,0.0003749342,0.00015579071,0.00014480899,0.0022259443,0.009345909,0.031477656,0.0065741157,0.16552962,0.71510553,0.0015600453],"about_ca_topic_score_codex":8.1229166e-7,"about_ca_topic_score_gemma":0.0000015575616,"teacher_disagreement_score":0.703707,"about_ca_system_score_codex":0.00009143103,"about_ca_system_score_gemma":0.000055846052,"threshold_uncertainty_score":0.8976024},"labels":[],"label_agreement":null},{"id":"W2150168892","doi":"10.1177/0956797611421484","title":"On Assets and Debt in the Psychology of Perceived Wealth","year":2011,"lang":"en","type":"article","venue":"Psychological Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":54,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Association for Psychological Science; Canadian Institute for Advanced Research; National Science Foundation","keywords":"Debt; Perception; Psychology; Function (biology); Net worth; Social psychology; Monetary economics; Economics; Finance","score_opus":0.37851987929346853,"score_gpt":0.5270128778227844,"score_spread":0.14849299852931586,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2150168892","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9586641,0.000014333739,0.00009853517,0.0005955307,0.0002462795,0.000110837354,0.0000023428352,0.000008685787,0.040259305],"genre_scores_gemma":[0.9965736,0.00002081513,0.0014266153,0.0019469265,0.000007658976,0.0000053459903,8.3829214e-8,0.000002007677,0.00001691515],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99756235,0.000216471,0.00050121284,0.0007350944,0.00068408606,0.00030081606],"domain_scores_gemma":[0.9979487,0.00097009045,0.00017853023,0.0007180931,0.00008058155,0.00010399146],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0071358406,0.000099502664,0.00021891357,0.00025392717,0.00013728497,0.000081145045,0.0019429739,0.00008058643,0.0003838637],"category_scores_gemma":[0.0021796962,0.000047437166,0.000046285415,0.0011275036,0.0013113561,0.0001750617,0.000104264815,0.00020920459,0.00016994456],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019552781,0.0011815621,0.15433688,6.850864e-7,8.539709e-7,0.00003628399,0.0023886366,0.0000051442976,0.0029807384,0.019890597,0.0016667577,0.8173163],"study_design_scores_gemma":[0.00013891509,0.000365565,0.7464875,0.000004482777,7.8882914e-7,0.000022283115,0.0001784927,0.000030625186,0.00001100978,0.25254318,0.00016556002,0.000051621744],"about_ca_topic_score_codex":0.000030683794,"about_ca_topic_score_gemma":0.000024294386,"teacher_disagreement_score":0.8172647,"about_ca_system_score_codex":0.000013790989,"about_ca_system_score_gemma":0.000020631833,"threshold_uncertainty_score":0.48317462},"labels":[],"label_agreement":null},{"id":"W2152123405","doi":"10.1037/a0022148","title":"Time is tight: How higher economic value of time increases feelings of time pressure.","year":2011,"lang":"en","type":"article","venue":"Journal of Applied Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":124,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Department of Families, Housing, Community Services and Indigenous Affairs","keywords":"Feeling; Value of time; Scarcity; Value (mathematics); Psychology; Affect (linguistics); Social psychology; Time value of money; Economics; Microeconomics; Travel time; Statistics; Mathematics","score_opus":0.08846709901199876,"score_gpt":0.36313234096307656,"score_spread":0.2746652419510778,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2152123405","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96337104,0.00014555847,0.000072022,0.0004438513,0.00048434213,0.00012263595,0.000061816194,0.000010931108,0.0352878],"genre_scores_gemma":[0.99057406,0.000043885004,0.0048798826,0.00050878065,0.00023301935,0.000002138087,0.000001633188,0.00003312218,0.0037234977],"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9969255,0.00012021823,0.0017461608,0.00044090045,0.00048697807,0.0002802479],"domain_scores_gemma":[0.9953199,0.0006598421,0.002771884,0.00075634086,0.00030451204,0.00018754759],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0025483428,0.0002399111,0.001142936,0.0006191587,0.0000478653,0.000047509573,0.0014581383,0.00029591544,0.016185807],"category_scores_gemma":[0.000093325616,0.00018005638,0.00037958208,0.00021413517,0.00036307672,0.00025781046,0.0001386646,0.00027996534,0.0027886622],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005565559,0.002389374,0.0037932885,0.000020233561,0.0008308929,0.00007030103,0.0026557997,0.0006584172,0.08438125,0.0018336644,0.73012704,0.1676742],"study_design_scores_gemma":[0.009154643,0.0044847727,0.056124978,0.00023386392,0.0012203114,0.00079023716,0.00036725745,0.002171501,0.037174758,0.45416835,0.4323961,0.0017132254],"about_ca_topic_score_codex":0.000018291094,"about_ca_topic_score_gemma":7.7573907e-7,"teacher_disagreement_score":0.45233467,"about_ca_system_score_codex":0.00002983566,"about_ca_system_score_gemma":0.000117016345,"threshold_uncertainty_score":0.9979878},"labels":[],"label_agreement":null},{"id":"W2152812298","doi":"10.1111/j.1747-9991.2007.00099.x","title":"Decision‐Making: A Neuroeconomic Perspective","year":2007,"lang":"en","type":"article","venue":"Philosophy Compass","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Neuroeconomics; Irrationality; Perspective (graphical); Field (mathematics); Point (geometry); Epistemology; Positive economics; Psychology; Rationality; Behavioural economics; Economics; Cognitive psychology; Philosophy; Computer science; Artificial intelligence","score_opus":0.1472587113847063,"score_gpt":0.4314207116274592,"score_spread":0.2841620002427529,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2152812298","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8390976,0.00012095111,0.018206775,0.0021491956,0.0026451459,0.00024502393,0.00002694202,0.00015330964,0.13735503],"genre_scores_gemma":[0.9935673,0.0000046699893,0.0043465123,0.0012849766,0.0006413704,0.0000057098887,0.0000011796868,0.000036985242,0.000111314585],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9958967,0.000096189324,0.0013366902,0.0011489033,0.0009514602,0.0005700547],"domain_scores_gemma":[0.99302816,0.0042729676,0.00049808086,0.0013712156,0.00053490466,0.0002946869],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0032522536,0.00033144536,0.0006242709,0.0008488764,0.00033281674,0.0005414143,0.0017999082,0.00012933004,0.00077363383],"category_scores_gemma":[0.0020213502,0.00027633726,0.00040591593,0.0007812107,0.00020970212,0.00053308404,0.0004104579,0.00037737482,0.0052668042],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006804056,0.00048666718,0.010732554,0.000001916707,0.000038242688,0.00024033086,0.00076482445,0.0006756653,0.00011137742,0.16670106,0.019988038,0.7995789],"study_design_scores_gemma":[0.0004563466,0.000111516434,0.018689832,0.000026891577,0.000013108345,0.00006301748,0.00040976916,0.0010533704,0.000051724903,0.9486408,0.030142287,0.00034129416],"about_ca_topic_score_codex":0.000021458263,"about_ca_topic_score_gemma":0.00008289194,"teacher_disagreement_score":0.7992376,"about_ca_system_score_codex":0.00031730573,"about_ca_system_score_gemma":0.00008955964,"threshold_uncertainty_score":0.9999689},"labels":[],"label_agreement":null},{"id":"W2152999879","doi":"10.2139/ssrn.960520","title":"Collective Risk Management in a Flight to Quality Episode","year":2007,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":203,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Risk management; Quality (philosophy); Quality management; Business; Risk analysis (engineering); Operations management; Economics; Finance; Management system; Philosophy","score_opus":0.06599872250646012,"score_gpt":0.4194888761972835,"score_spread":0.35349015369082337,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2152999879","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9373681,0.00025923993,0.048917044,0.00047050015,0.00046406614,0.00022695828,0.0000046473833,0.000017813585,0.012271611],"genre_scores_gemma":[0.9921849,0.00023971683,0.001489845,0.00021439833,0.00011910737,0.0000053278363,3.7209628e-7,0.00001539084,0.0057309647],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9946739,0.00031306708,0.0012584747,0.0005361433,0.0010040216,0.002214405],"domain_scores_gemma":[0.9978427,0.0008327878,0.0004555106,0.00047027637,0.00018150122,0.00021719154],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.03498624,0.00018530396,0.00037856953,0.0009887506,0.00029965676,0.00028519187,0.0010661114,0.000093662944,0.00010844937],"category_scores_gemma":[0.001282874,0.0001441646,0.00019269875,0.0015153673,0.0000379792,0.00027050506,0.00017495542,0.001462385,0.0006286343],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029186683,0.0001372354,0.028439103,3.3102137e-7,0.00003637579,0.000032328928,0.00053331,0.0002718332,0.000015324935,0.014723246,0.0004959884,0.95502305],"study_design_scores_gemma":[0.00070444227,0.00023433109,0.04475709,0.000011631246,0.000014683878,0.00008533754,0.0047643213,0.000046465575,0.000059098777,0.93860936,0.010499157,0.00021407311],"about_ca_topic_score_codex":0.0002484887,"about_ca_topic_score_gemma":0.021530483,"teacher_disagreement_score":0.954809,"about_ca_system_score_codex":0.003985274,"about_ca_system_score_gemma":0.0010237028,"threshold_uncertainty_score":0.99983823},"labels":[],"label_agreement":null},{"id":"W2154576508","doi":"10.1016/j.ijresmar.2013.08.002","title":"Consumer response to uncertain promotions: An empirical analysis of conditional rebates","year":2013,"lang":"en","type":"article","venue":"International Journal of Research in Marketing","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":77,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Universidad Carlos III de Madrid; Dartmouth College","keywords":"Event (particle physics); Receipt; Conditional probability; Conjoint analysis; Econometrics; Economics; Risk aversion (psychology); Marketing; Advertising; Microeconomics; Actuarial science; Business; Preference; Expected utility hypothesis; Statistics; Financial economics; Mathematics","score_opus":0.35382856606715946,"score_gpt":0.5903400542026845,"score_spread":0.23651148813552508,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2154576508","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9915589,0.000035674533,0.00056636025,0.0070458176,0.00025405915,0.00014088159,0.000042762866,0.000004071053,0.00035147843],"genre_scores_gemma":[0.99383074,0.00001306181,0.0057423958,0.00011280489,0.00009876163,0.000010585284,0.000006345241,0.0000076577135,0.00017764202],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9908527,0.0033179657,0.001699114,0.00033061526,0.003516528,0.00028307803],"domain_scores_gemma":[0.9732395,0.019189838,0.0005901456,0.00032177626,0.0063965837,0.00026218552],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.05332181,0.0001008929,0.00040774784,0.006126932,0.00008256602,0.00049067225,0.001665341,0.000079016674,0.002553665],"category_scores_gemma":[0.048725378,0.000077115,0.00023024555,0.0025214301,0.00022342011,0.00077104766,0.0002650451,0.0004647652,0.00010380878],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004029961,0.0007153472,0.6856995,0.000003280073,0.00040716605,0.00025410892,0.0009221465,0.010626605,0.005140016,0.000098667886,0.010644772,0.2814584],"study_design_scores_gemma":[0.00064418593,0.00036458834,0.9266979,0.00023218803,0.00003206493,0.00007707377,0.0033237017,0.01926724,0.0002055232,0.043701157,0.0053021344,0.00015223824],"about_ca_topic_score_codex":0.00010950548,"about_ca_topic_score_gemma":0.00006524241,"teacher_disagreement_score":0.28130618,"about_ca_system_score_codex":0.00029379607,"about_ca_system_score_gemma":0.00039194842,"threshold_uncertainty_score":0.99835813},"labels":[],"label_agreement":null},{"id":"W2154772733","doi":"10.1002/bdm.617","title":"A behavioral account of compensation awarding decisions","year":2008,"lang":"en","type":"article","venue":"Journal of Behavioral Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Compensation (psychology); Value (mathematics); Object (grammar); Economics; Microeconomics; Zero (linguistics); Actuarial science; Psychology; Social psychology; Computer science; Artificial intelligence; Philosophy","score_opus":0.27258908242826174,"score_gpt":0.46125417756629405,"score_spread":0.1886650951380323,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2154772733","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96961856,0.00023692149,0.026791496,0.00006503452,0.0027550885,0.00022899457,0.0000431736,0.000030039611,0.00023066727],"genre_scores_gemma":[0.9434223,0.00008317858,0.05605462,0.000067569745,0.0002463375,0.000003332564,0.0000019200133,0.000053080395,0.0000676256],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9884306,0.00031390437,0.0053168377,0.0006976986,0.0046694414,0.00057150295],"domain_scores_gemma":[0.98622936,0.0043779304,0.004517649,0.0012796957,0.003225907,0.000369465],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.005866947,0.0004755408,0.0016701331,0.0024146468,0.0005547293,0.00037995487,0.0023983563,0.0003585522,0.00084992155],"category_scores_gemma":[0.0030378203,0.0003634138,0.0012784989,0.0017871924,0.0003512778,0.001922982,0.00054718874,0.00079630205,0.00019465512],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00062406505,0.0009929629,0.054891482,0.0000016707626,0.000017222586,0.0006244075,0.0011866278,0.002158424,0.003426891,0.000098209166,0.0054414533,0.93053657],"study_design_scores_gemma":[0.013645395,0.0088969525,0.59671825,0.0052152374,0.0015430768,0.021552313,0.017072072,0.008490362,0.006413112,0.2724988,0.043639984,0.0043144487],"about_ca_topic_score_codex":0.000040386625,"about_ca_topic_score_gemma":0.000041886906,"teacher_disagreement_score":0.92622215,"about_ca_system_score_codex":0.00034339115,"about_ca_system_score_gemma":0.00048149482,"threshold_uncertainty_score":0.9998818},"labels":[],"label_agreement":null},{"id":"W2158027157","doi":"10.1287/mnsc.1110.1429","title":"A Case-Based Model of Probability and Pricing Judgments: Biases in Buying and Selling Uncertainty","year":2011,"lang":"en","type":"article","venue":"Management Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Econometrics; Economics; Heuristics; Odds; Bayes' theorem; Valuation (finance); Microeconomics; Actuarial science; Bayesian probability; Computer science; Statistics; Mathematics","score_opus":0.4098736491539777,"score_gpt":0.3833561576868238,"score_spread":0.02651749146715393,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2158027157","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9852616,0.00001700172,0.012746264,0.000028905219,0.00005783124,0.00026491063,0.0000039053543,0.000013751952,0.0016058375],"genre_scores_gemma":[0.9651779,0.0000066807247,0.034711313,0.00006488681,0.0000019333277,0.000007943597,1.296732e-7,0.0000033331696,0.000025875708],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979422,0.000042061933,0.00053375977,0.0006739101,0.000539816,0.00026823053],"domain_scores_gemma":[0.9988914,0.00030281037,0.00019704647,0.00043079312,0.00008811641,0.00008980135],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00585255,0.00010782617,0.00020484846,0.0005682018,0.00019442814,0.000173359,0.00044227327,0.000023686505,0.00001541153],"category_scores_gemma":[0.0005852161,0.000083595456,0.000025200368,0.0009507554,0.00051941996,0.00050681335,0.0003583082,0.00006203015,0.000002696672],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008094596,0.0003610314,0.13379288,0.000058345307,0.000005149828,0.0001973148,0.0035208934,0.30512926,0.0006719775,0.004146968,0.000019276149,0.55201596],"study_design_scores_gemma":[0.00030377184,0.0000516859,0.0059014265,0.00009352762,0.000010723439,0.000012544684,0.0013738911,0.9294633,0.0003982604,0.06223977,0.000011189281,0.00013990965],"about_ca_topic_score_codex":0.0002505519,"about_ca_topic_score_gemma":0.00018686801,"teacher_disagreement_score":0.62433404,"about_ca_system_score_codex":0.000066540706,"about_ca_system_score_gemma":0.000040682702,"threshold_uncertainty_score":0.34089237},"labels":[],"label_agreement":null},{"id":"W2158925497","doi":"10.1371/journal.pone.0004362","title":"Genetic Determinants of Financial Risk Taking","year":2009,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"Alliance for Cancer Gene Therapy; National Science Foundation","keywords":"Allele; Financial risk; Addiction; Genetics; Anxiety; Gene; Psychology; Biology; Economics; Finance; Psychiatry","score_opus":0.20363823246645943,"score_gpt":0.36753531630156705,"score_spread":0.16389708383510762,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2158925497","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99863786,0.00007398529,0.000118325544,0.000031046075,0.00009719693,0.00009252244,0.000020587573,0.000019412224,0.0009090761],"genre_scores_gemma":[0.98992974,0.000025357416,0.00968872,0.000093784874,0.000088514455,0.0000017507725,2.4304023e-7,0.0000060316966,0.00016583363],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9979948,0.00006291265,0.00070037006,0.00033321264,0.0007095847,0.00019914834],"domain_scores_gemma":[0.99798566,0.00035858585,0.0008554842,0.0005471481,0.00017932072,0.00007381595],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008032594,0.00010313094,0.00038768115,0.00017932909,0.00009311711,0.00008200919,0.0005842209,0.0000812651,0.00027997882],"category_scores_gemma":[0.00490401,0.000083610044,0.000099171215,0.000299253,0.000049277573,0.0001310314,0.00006377244,0.00011263275,0.0003547146],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020923222,0.0004659068,0.19211157,0.0000011174694,0.0000021383707,0.000010341371,0.00009236842,0.000021376318,0.0013461268,0.0000100224415,0.00013228972,0.80578583],"study_design_scores_gemma":[0.00022879224,0.00026656134,0.93034863,0.000080238955,0.000047873888,0.000002848575,0.000020440177,0.0019753661,0.009028667,0.057739917,0.000115430805,0.0001452446],"about_ca_topic_score_codex":0.000026270984,"about_ca_topic_score_gemma":0.000045331963,"teacher_disagreement_score":0.8056406,"about_ca_system_score_codex":0.00001909174,"about_ca_system_score_gemma":0.000055422573,"threshold_uncertainty_score":0.5870912},"labels":[],"label_agreement":null},{"id":"W2159196754","doi":"10.1287/deca.1070.0094","title":"Analysis of the Biological Clock Decision","year":2007,"lang":"en","type":"article","venue":"Decision Analysis","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"AGE-WELL","keywords":"Function (biology); Quality of life (healthcare); Quality (philosophy); Psychology; Epistemology; Philosophy","score_opus":0.13803290465819482,"score_gpt":0.4382528561120483,"score_spread":0.3002199514538535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2159196754","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.80334723,0.00011667595,0.19449697,0.00010693749,0.00048187276,0.00011230182,0.00005517317,0.000029411936,0.0012534289],"genre_scores_gemma":[0.9928309,0.000034907633,0.006363463,0.0003687553,0.00004605169,0.0000023767898,0.0000125343295,0.000012471618,0.0003285865],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99174666,0.00028887257,0.0030948767,0.0012678561,0.0030883593,0.0005133899],"domain_scores_gemma":[0.9815776,0.012614365,0.0012581412,0.0032652044,0.0009802614,0.00030443503],"candidate_categories":["metaresearch","bibliometrics","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0134114595,0.00033723266,0.001673799,0.005411959,0.00036844457,0.0003152162,0.003244924,0.00035271278,0.0036871114],"category_scores_gemma":[0.010883815,0.00017605691,0.0039111283,0.033545427,0.00030645344,0.00022217422,0.0008471386,0.0003058216,0.00042445023],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014726035,0.00014256133,0.36702028,1.3080117e-7,0.0009041438,0.000008881353,0.00008160357,0.0100037735,0.0001431766,0.00028718205,0.0009816382,0.6202794],"study_design_scores_gemma":[0.00031850435,0.000060267004,0.9233964,0.000010543972,0.0045189774,0.000003228039,0.00047967426,0.018311175,0.00032683832,0.035736807,0.016536765,0.00030078273],"about_ca_topic_score_codex":0.000096131385,"about_ca_topic_score_gemma":0.0015985671,"teacher_disagreement_score":0.6199786,"about_ca_system_score_codex":0.00011926127,"about_ca_system_score_gemma":0.00006176398,"threshold_uncertainty_score":0.9974479},"labels":[],"label_agreement":null},{"id":"W2159425318","doi":"10.7202/1021504ar","title":"La valeur psychologique du temps : une synthèse de la littérature","year":2014,"lang":"fr","type":"article","venue":"L Actualité économique","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Humanities; Philosophy","score_opus":0.05972069598088731,"score_gpt":0.3598605995205902,"score_spread":0.3001399035397029,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2159425318","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91475147,0.0012458242,0.0070835366,0.01297201,0.0027267595,0.00031816735,0.00016867748,0.0001872929,0.06054628],"genre_scores_gemma":[0.9762552,0.001574419,0.0066319956,0.004714473,0.0011805955,0.000053791522,0.000013873159,0.0000966793,0.009478979],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99093837,0.004776658,0.0015891042,0.0015155524,0.00024982993,0.0009305052],"domain_scores_gemma":[0.9803974,0.016097622,0.00072759506,0.0019043116,0.00022618138,0.00064686994],"candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication","research_integrity","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.014498825,0.00068705477,0.0010890182,0.00036383863,0.0003301697,0.0017352637,0.002106815,0.002044907,0.0012223556],"category_scores_gemma":[0.008429389,0.00061325316,0.00057592883,0.0007313567,0.0010711732,0.00084731966,0.00043128166,0.0015911206,0.0028206992],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011924307,0.00048692693,0.0057778494,0.00002471286,0.00004155196,0.000115349736,0.001714521,0.0004056677,0.00021946461,0.14749622,0.01648843,0.82711005],"study_design_scores_gemma":[0.00059851457,0.00018497375,0.005248056,0.00017726721,0.000050080926,0.00047986495,0.00063730916,0.0012215065,0.0002937619,0.2924494,0.698092,0.0005672882],"about_ca_topic_score_codex":0.0006242519,"about_ca_topic_score_gemma":0.0003826961,"teacher_disagreement_score":0.8265428,"about_ca_system_score_codex":0.00037827741,"about_ca_system_score_gemma":0.00049440854,"threshold_uncertainty_score":0.99992305},"labels":[],"label_agreement":null},{"id":"W2159861263","doi":"10.3758/s13423-011-0057-1","title":"Magnitude comparison revisited: An alternative approach to binary choice under uncertainty","year":2011,"lang":"en","type":"article","venue":"Psychonomic Bulletin & Review","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Heuristics; Psychology; Probabilistic logic; Task (project management); Magnitude (astronomy); Cognitive psychology; Focus (optics); Binary number; Process (computing); Social psychology; Artificial intelligence; Computer science; Mathematics; Arithmetic; Mathematical optimization","score_opus":0.3361898231911778,"score_gpt":0.45171437028887135,"score_spread":0.11552454709769355,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2159861263","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7727279,0.049206946,0.008238481,0.007421082,0.0037463186,0.0044819764,0.00015891153,0.0003828439,0.15363553],"genre_scores_gemma":[0.8675097,0.014510748,0.074674115,0.037535697,0.0010019505,0.0004706448,0.000099808196,0.00020444964,0.0039928653],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9946238,0.0006325823,0.0019489421,0.0016284663,0.0006350847,0.0005311253],"domain_scores_gemma":[0.9956207,0.0005901549,0.00079558603,0.002134507,0.00032624014,0.00053279893],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.004493462,0.0004640668,0.0012954727,0.00030978248,0.00019885541,0.00027761774,0.0026218959,0.00013119393,0.0061707366],"category_scores_gemma":[0.00076878635,0.00035863422,0.00036745824,0.00066432805,0.00012722013,0.0002176066,0.0003322039,0.00040524,0.014816593],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010935953,0.001082304,0.0019044298,0.000099247954,0.000038442296,0.0000046611854,0.00050077896,0.00068788126,0.000015805668,0.00074753625,0.33314413,0.66166544],"study_design_scores_gemma":[0.00041526664,0.00028057187,0.006307866,0.0009184847,0.00009007151,0.000022402819,0.00033147886,0.00055221375,0.000005600193,0.0052284608,0.985221,0.0006265456],"about_ca_topic_score_codex":0.00034925714,"about_ca_topic_score_gemma":0.000021188745,"teacher_disagreement_score":0.6610389,"about_ca_system_score_codex":0.00016006314,"about_ca_system_score_gemma":0.00005847636,"threshold_uncertainty_score":0.9998866},"labels":[],"label_agreement":null},{"id":"W2160048429","doi":"10.1111/j.1467-9779.2008.00394.x","title":"<scp>The Repugnant Conclusion and Utilitarianism under Domain Restrictions</scp>","year":2008,"lang":"en","type":"article","venue":"Journal of Public Economic Theory","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Utilitarianism; Economics; Domain (mathematical analysis); Bounded function; Subsistence agriculture; Population; Consumption (sociology); Mathematics; Biology; Ecology; Philosophy; Demography; Sociology; Epistemology","score_opus":0.13074083856109545,"score_gpt":0.346102418429089,"score_spread":0.21536157986799356,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2160048429","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98519564,0.0005890005,0.0035760151,0.004134529,0.0014141653,0.00008944881,0.000012517179,0.000014586747,0.0049740765],"genre_scores_gemma":[0.99630666,0.00020930945,0.0006553524,0.0004832762,0.0003651973,0.0000017908342,5.5640976e-7,0.000016948974,0.0019609283],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9967268,0.00067956303,0.0015529606,0.00035278875,0.00037902477,0.0003088556],"domain_scores_gemma":[0.99288976,0.004755485,0.0013061035,0.00056704774,0.00024161143,0.00023998415],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.013690116,0.00017962331,0.00047371545,0.00053273165,0.0008291814,0.00041613498,0.0010380876,0.00014424835,0.00025000644],"category_scores_gemma":[0.002439405,0.00010922355,0.00027291666,0.0002226871,0.00051440723,0.0009647144,0.00032345988,0.00042152338,0.00018212115],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009874825,0.00028511463,0.013318613,0.0000027963783,0.00016329832,0.00019734965,0.0050562574,0.0003827285,0.00039790585,0.550719,0.14992864,0.27944952],"study_design_scores_gemma":[0.0005992032,0.0001194787,0.025476879,0.000008916215,0.00001794236,0.0021111865,0.0053842072,0.00012757487,0.000024613417,0.7606722,0.20539078,0.00006700174],"about_ca_topic_score_codex":0.00001285379,"about_ca_topic_score_gemma":0.00001465931,"teacher_disagreement_score":0.27938253,"about_ca_system_score_codex":0.00022442259,"about_ca_system_score_gemma":0.00043025476,"threshold_uncertainty_score":0.6377477},"labels":[],"label_agreement":null},{"id":"W2160791614","doi":"","title":"The Effect of an Additional Alternative on Measured Risk Preferences in a Laboratory Experiment in Peru","year":2006,"lang":"en","type":"preprint","venue":"eScholarship@McGill (McGill)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University","funders":"McGill University; Johns Hopkins University; Brown University","keywords":"Quarter (Canadian coin); Test (biology); Chose; Psychology; Econometrics; Economics; Demography; Geography; Sociology; Political science; Biology","score_opus":0.06328413792776501,"score_gpt":0.3428289377699449,"score_spread":0.2795447998421799,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2160791614","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97655445,0.00017162277,2.2699926e-7,0.000014284193,0.0011905085,0.00088631304,0.014467997,0.000047364392,0.0066672596],"genre_scores_gemma":[0.9987105,0.00005415498,0.00037399173,0.00003579873,0.000055635814,0.00046910858,0.00015569036,0.000055571687,0.00008951693],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9885795,0.0042355848,0.0021852725,0.0018392132,0.0025675541,0.0005928757],"domain_scores_gemma":[0.9883711,0.0073933722,0.0017093328,0.001761944,0.00054559374,0.00021866665],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.011593099,0.00072533346,0.0012162501,0.0009802259,0.0005584767,0.0003935055,0.0027004832,0.0006121034,0.00048768864],"category_scores_gemma":[0.008171908,0.0004983384,0.0003974578,0.0008061623,0.00029481118,0.0006158126,0.00091842236,0.0023084083,0.00018295422],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001066142,0.00069047645,0.003465416,0.00001714966,0.000060964605,0.0000840232,0.000035052246,0.012073038,0.0006734659,0.0018016913,0.00006480247,0.9799678],"study_design_scores_gemma":[0.0049978136,0.0033547755,0.08245496,0.0020845202,0.00012423367,0.00001214122,0.00069014024,0.002455366,0.07476937,0.7972223,0.029287733,0.00254662],"about_ca_topic_score_codex":0.0017049423,"about_ca_topic_score_gemma":0.0066337353,"teacher_disagreement_score":0.97742116,"about_ca_system_score_codex":0.0010688687,"about_ca_system_score_gemma":0.00015598815,"threshold_uncertainty_score":0.9999933},"labels":[],"label_agreement":null},{"id":"W2161077460","doi":"10.20982/tqmp.02.1.p001","title":"An Introduction to Model Selection: Tools and Algorithms","year":2006,"lang":"en","type":"article","venue":"Tutorials in Quantitative Methods for Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":49,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Computer science; Selection (genetic algorithm); Algorithm; Machine learning","score_opus":0.39920512981782014,"score_gpt":0.6268989075808892,"score_spread":0.22769377776306904,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2161077460","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.26137027,0.00004767547,0.7317003,0.0016461131,0.0045291707,0.00039399517,0.000038900107,0.000033816068,0.00023978639],"genre_scores_gemma":[0.024019554,0.0000052502774,0.973833,0.00025789192,0.0014805173,0.000121487996,0.000010417087,0.000022397378,0.00024945592],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99591094,0.0013108107,0.0010785629,0.0011456123,0.00022545496,0.00032861278],"domain_scores_gemma":[0.9945538,0.0041132285,0.00029514357,0.00050227554,0.00044138535,0.000094135845],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01594947,0.00019864825,0.00063259894,0.0006687139,0.00014837248,0.00026133918,0.00040964267,0.00019432858,0.000060127364],"category_scores_gemma":[0.0069031455,0.00017043533,0.00008467688,0.0007897963,0.00013555035,0.0005436623,0.000046374866,0.00015525587,0.000034131837],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046000825,0.00019053064,0.00046682567,0.0000015718022,0.000006039876,8.2616424e-7,0.0004219807,0.008005199,0.034000825,0.08940019,0.009252902,0.8577931],"study_design_scores_gemma":[0.00066710095,0.0008974374,0.0024349266,0.000003395402,0.000012126289,0.000013869011,0.00018808294,0.0335723,0.0013889129,0.87448657,0.08609123,0.00024406232],"about_ca_topic_score_codex":0.000037015812,"about_ca_topic_score_gemma":0.00007878407,"teacher_disagreement_score":0.857549,"about_ca_system_score_codex":0.0000693681,"about_ca_system_score_gemma":0.0000431649,"threshold_uncertainty_score":0.82642084},"labels":[],"label_agreement":null},{"id":"W2162793682","doi":"10.7202/1027909ar","title":"Dual-process theory et résolution de problèmes additifs de comparaison par des étudiants universitaires","year":2014,"lang":"fr","type":"article","venue":"Éducation et francophonie","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Université du Québec à Rimouski","funders":"","keywords":"Humanities; Philosophy; Physics; Mathematics","score_opus":0.07171104742290241,"score_gpt":0.38157115671509606,"score_spread":0.30986010929219365,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2162793682","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9381849,0.0014024252,0.037348673,0.007911672,0.003921009,0.0002831237,0.00013800694,0.00011163612,0.010698518],"genre_scores_gemma":[0.9915012,0.0003152005,0.004542169,0.00098718,0.00032096118,0.000029957886,0.0000434062,0.00004277518,0.0022171505],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9956541,0.0015183133,0.000749395,0.00078119914,0.00056850514,0.0007285108],"domain_scores_gemma":[0.9951237,0.0027126693,0.00056358037,0.00068839034,0.00055139506,0.00036025405],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.006426351,0.0003665414,0.000500393,0.00037700348,0.0006609333,0.0005006486,0.00071236904,0.00033466896,0.002347017],"category_scores_gemma":[0.0026109735,0.00037042197,0.00021103786,0.0009110329,0.0006462057,0.0017167352,0.00011699076,0.00041808575,0.0019712143],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022160888,0.0011948996,0.021236487,0.00009266989,0.00005326679,0.000019020223,0.026709493,0.011743831,0.00034324496,0.02150199,0.08124257,0.8356409],"study_design_scores_gemma":[0.0011708362,0.00027006253,0.12102164,0.0006349487,0.000105305764,0.000087285865,0.017992273,0.012411122,0.0009800768,0.7554416,0.089130245,0.0007545749],"about_ca_topic_score_codex":0.00048546694,"about_ca_topic_score_gemma":0.0012903115,"teacher_disagreement_score":0.8348864,"about_ca_system_score_codex":0.00079379755,"about_ca_system_score_gemma":0.0019838153,"threshold_uncertainty_score":0.9998748},"labels":[],"label_agreement":null},{"id":"W2162873672","doi":"10.1503/cmaj.091546","title":"Rainy weather and medical school admission interviews","year":2009,"lang":"en","type":"article","venue":"Canadian Medical Association Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"Health Sciences Centre; University of Toronto; Institute for Clinical Evaluative Sciences; Sunnybrook Health Science Centre","funders":"","keywords":"Mood; Medical school; Cognition; Medical education; Psychology; Medicine; Psychiatry","score_opus":0.048817502883090134,"score_gpt":0.36723198068723,"score_spread":0.3184144778041399,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2162873672","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7904821,0.00053803576,0.0005337425,0.19241197,0.0018650753,0.000100057034,0.000011796722,0.000024865207,0.014032338],"genre_scores_gemma":[0.9475477,0.00024096621,0.00025554866,0.048503395,0.0014308386,0.0000013164439,0.00000177637,0.00001105972,0.0020073988],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99423265,0.00039427142,0.0010405134,0.00030787344,0.0035789723,0.00044570863],"domain_scores_gemma":[0.99177057,0.00070871116,0.00038820598,0.00021017397,0.0004093642,0.0065130084],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.012719916,0.00014186765,0.00035442883,0.00039237877,0.00034529468,0.000630103,0.0008007895,0.0005570635,0.052625667],"category_scores_gemma":[0.05304493,0.000099887795,0.00014799615,0.00033867688,0.000046580193,0.00031577566,0.000043905886,0.0011191696,0.0011249465],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000037566203,0.000015631711,0.007949071,1.6753788e-7,0.000005068323,0.00017204898,0.00009009559,4.906919e-7,0.0000017960692,0.000052685387,0.22886747,0.7628417],"study_design_scores_gemma":[0.00064462546,0.00009476281,0.024602981,0.00010670635,0.000008962533,0.00062096387,0.000365559,0.00071373,0.000002139086,0.03710667,0.93556494,0.00016793508],"about_ca_topic_score_codex":0.00029821863,"about_ca_topic_score_gemma":0.006166981,"teacher_disagreement_score":0.7626738,"about_ca_system_score_codex":0.00058302074,"about_ca_system_score_gemma":0.0034840677,"threshold_uncertainty_score":0.9996528},"labels":[],"label_agreement":null},{"id":"W2162895624","doi":"10.1016/j.beproc.2006.09.007","title":"The consequences of surrendering a degree of freedom to the participant in a contingency assessment task","year":2006,"lang":"en","type":"article","venue":"Behavioural Processes","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Contingency; Psychology; Task (project management); Outcome (game theory); Contingency management; Social psychology; Value (mathematics); Variety (cybernetics); Contingency table; Developmental psychology; Cognitive psychology; Computer science; Statistics; Artificial intelligence; Mathematics; Intervention (counseling)","score_opus":0.3159016008127257,"score_gpt":0.42280831898949006,"score_spread":0.10690671817676434,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2162895624","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99680376,0.00069722196,0.00031758923,0.001059534,0.00029467876,0.00031482617,0.00004450211,0.000014081636,0.000453787],"genre_scores_gemma":[0.999095,0.000020674765,0.0006703746,0.000016250253,0.00002842584,0.00005702152,0.0000015483092,0.000008922568,0.00010176495],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99688196,0.00014421692,0.0014209138,0.000362039,0.00084228965,0.0003485653],"domain_scores_gemma":[0.9962027,0.0019688308,0.00065310317,0.00053586415,0.0005823217,0.00005715666],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030230212,0.00016508641,0.0004138231,0.00015804569,0.00020426694,0.00022445085,0.0012383303,0.00005504975,0.000034738892],"category_scores_gemma":[0.0019924538,0.00008262476,0.00010302317,0.0009839984,0.00041133206,0.00020844747,0.00020125994,0.00015031322,0.000012365105],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007926788,0.00034196343,0.8436113,0.00001964231,0.000010312227,0.000014963247,0.0010843977,0.0031373384,0.0049690087,0.0011157335,0.0014281166,0.14418796],"study_design_scores_gemma":[0.0007587788,0.00040595848,0.9385919,0.00031193817,0.00011107434,0.000028000723,0.009180944,0.00067055016,0.012023499,0.034306325,0.0031278362,0.00048316983],"about_ca_topic_score_codex":0.002970542,"about_ca_topic_score_gemma":0.014042896,"teacher_disagreement_score":0.14370479,"about_ca_system_score_codex":0.00003393244,"about_ca_system_score_gemma":0.00036532086,"threshold_uncertainty_score":0.78362656},"labels":[],"label_agreement":null},{"id":"W2162944011","doi":"10.1111/j.1467-937x.2005.00339.x","title":"A Bayesian Approach to Uncertainty Aversion","year":2005,"lang":"en","type":"article","venue":"The Review of Economic Studies","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":84,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Bayesian probability; Economics; Library science; Positive economics; Computer science; Statistics; Mathematics","score_opus":0.19577125160444472,"score_gpt":0.44144546834073956,"score_spread":0.24567421673629483,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2162944011","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.54125446,0.30179062,0.0012964739,0.037925262,0.0020018856,0.0024305028,0.000095189615,0.000090890404,0.113114685],"genre_scores_gemma":[0.91802716,0.0702279,0.0044646636,0.005113278,0.00035965198,0.00006397637,0.0000021827827,0.00002054062,0.0017206671],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99794436,0.00014212089,0.0010675532,0.00041614322,0.00023200022,0.00019780602],"domain_scores_gemma":[0.99736696,0.0010861099,0.00043308365,0.0009090118,0.0001323245,0.0000724806],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004517549,0.00016484015,0.0008051198,0.0001117518,0.00015805247,0.00004289035,0.001043203,0.000029144467,0.00024206383],"category_scores_gemma":[0.0012532898,0.0000883599,0.00027460698,0.00020411254,0.00014629561,0.00014524705,0.00040851557,0.00008195243,0.001835762],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014156124,0.000041100906,0.00012698605,0.00009645925,0.00004510243,2.0245868e-7,0.00057167455,0.0025361215,0.0000026290775,0.0011807592,0.13059618,0.86478865],"study_design_scores_gemma":[0.00030739835,0.000107690095,0.00034739508,0.0019188663,0.00012871144,0.000018390267,0.0030888733,0.0029935068,0.00004639814,0.02552752,0.96514183,0.0003734128],"about_ca_topic_score_codex":0.000015917165,"about_ca_topic_score_gemma":0.000025682604,"teacher_disagreement_score":0.8644152,"about_ca_system_score_codex":0.00017581276,"about_ca_system_score_gemma":0.000051818824,"threshold_uncertainty_score":0.9989414},"labels":[],"label_agreement":null},{"id":"W2163382546","doi":"10.1016/s0010-0277(01)00137-8","title":"Wisdom and aging: irrational preferences in college students but not older adults","year":2001,"lang":"en","type":"article","venue":"Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":94,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"National Institute on Aging","keywords":"Psychology; Irrational number; Social psychology; Developmental psychology","score_opus":0.11816549674905466,"score_gpt":0.39717008254632136,"score_spread":0.2790045857972667,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2163382546","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99607617,0.000039414383,0.00011264548,0.0002970207,0.00024043157,0.00019765229,0.000055991768,0.000019886473,0.0029607643],"genre_scores_gemma":[0.99882376,0.00003721987,0.00018734156,0.0002529837,0.000052598098,0.000021131342,0.000019450048,0.000005609944,0.0005998806],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9982177,0.00007767415,0.00045822316,0.00041976557,0.00067430414,0.00015234141],"domain_scores_gemma":[0.99893886,0.00049021124,0.00013733695,0.0001575014,0.00020293787,0.000073176525],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008776182,0.000105451996,0.00017386381,0.00025722527,0.000111995374,0.0002627447,0.00026646556,0.00007563716,0.0005311576],"category_scores_gemma":[0.00048502392,0.000087436616,0.000033546257,0.0003095021,0.000075070864,0.0004524406,0.00009527807,0.00009964601,0.0002785896],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031584845,0.0004679936,0.22553352,0.000004014497,0.000007443147,0.00006110388,0.0010382867,0.000020101597,0.00021655625,0.00016954045,0.0016899824,0.7704756],"study_design_scores_gemma":[0.0020867304,0.00009840645,0.91512805,0.00017884262,0.000014102079,0.000038479684,0.0033999148,0.00083708647,0.0003699186,0.075928055,0.0016757618,0.00024467552],"about_ca_topic_score_codex":0.000017409066,"about_ca_topic_score_gemma":0.00029146302,"teacher_disagreement_score":0.77023095,"about_ca_system_score_codex":0.000027060452,"about_ca_system_score_gemma":0.000036809248,"threshold_uncertainty_score":0.5815803},"labels":[],"label_agreement":null},{"id":"W2163442724","doi":"10.1142/s0217590805002104","title":"THE APPROPRIATE CHOICE OF VALUATION MEASURE IN USUAL CASES OF LOSSES VALUED MORE THAN GAINS","year":2005,"lang":"en","type":"article","venue":"The Singapore Economic Review","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Measure (data warehouse); Valuation (finance); Econometrics; Economics; Variation (astronomy); Value (mathematics); Statistics; Mathematics; Actuarial science; Computer science; Finance","score_opus":0.2989379139337575,"score_gpt":0.45627615114369036,"score_spread":0.15733823720993284,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2163442724","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96963817,0.025914641,0.000043659824,0.0025239934,0.00030241162,0.0005713603,0.000028012537,0.000010489244,0.0009672364],"genre_scores_gemma":[0.9926881,0.006494982,0.0002231677,0.00024411448,0.00012580057,0.000018231078,0.000004138653,0.000016533666,0.00018491872],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9963982,0.0005480039,0.001977834,0.0003955421,0.00044564417,0.00023474157],"domain_scores_gemma":[0.994135,0.0029075523,0.0015030884,0.0012042299,0.00019799406,0.00005213328],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011496125,0.00019702018,0.0007564429,0.00011787345,0.00015972958,0.00010281834,0.0012853558,0.0000687035,0.00014060648],"category_scores_gemma":[0.0040630675,0.000102676466,0.00030933265,0.00030836105,0.0003173697,0.0003052805,0.00015172352,0.00017738981,0.00015880849],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030218887,0.000066617074,0.0033415314,0.000055672128,0.000019865387,0.0000012317313,0.00030969977,0.0018093961,0.000043443746,0.0007575819,0.0016909146,0.9918738],"study_design_scores_gemma":[0.0063341567,0.0012529326,0.17089087,0.022092706,0.0016835512,0.00045501106,0.0074875676,0.06533553,0.0063894456,0.2818958,0.43266228,0.0035201749],"about_ca_topic_score_codex":0.00019776607,"about_ca_topic_score_gemma":0.00086254184,"teacher_disagreement_score":0.98835367,"about_ca_system_score_codex":0.00013382176,"about_ca_system_score_gemma":0.00023862398,"threshold_uncertainty_score":0.48641646},"labels":[],"label_agreement":null},{"id":"W2163508470","doi":"10.1177/0956797610369493","title":"Physical Contact and Financial Risk Taking","year":2010,"lang":"en","type":"article","venue":"Psychological Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":93,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Psychology; Finance; Business","score_opus":0.12954184770145097,"score_gpt":0.4768079337914606,"score_spread":0.34726608609000964,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2163508470","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98859215,0.0000061854475,0.00045915923,0.00024836403,0.0012640082,0.00008221581,0.000008464065,0.000043048614,0.009296383],"genre_scores_gemma":[0.99725366,0.0000039714746,0.0021389949,0.00036174196,0.00018835386,0.000004147085,1.2080746e-7,0.0000032439439,0.000045773282],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9973599,0.000058565485,0.0003404147,0.0009964001,0.00085609534,0.00038863858],"domain_scores_gemma":[0.99763733,0.00094921933,0.00038066768,0.00060549163,0.0001445543,0.00028273708],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0040898127,0.00013084245,0.00024310582,0.00014614195,0.00055158645,0.00066026073,0.001355835,0.000094034,0.00040969782],"category_scores_gemma":[0.016659677,0.00007742957,0.000081903316,0.0009267582,0.0011318737,0.00045158627,0.00028345393,0.0005080768,0.0005041833],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017579281,0.00012786649,0.043607373,9.457158e-8,2.1613486e-7,0.000008235974,0.0001329728,0.0000022938764,0.01986544,0.0036786413,0.0003363476,0.93222296],"study_design_scores_gemma":[0.00018481119,0.00018052815,0.76580447,0.000002461419,0.0000031234276,0.000031465835,0.000040242026,0.0009266193,0.00029874482,0.2268342,0.005538071,0.0001552623],"about_ca_topic_score_codex":0.000019272858,"about_ca_topic_score_gemma":0.000028051434,"teacher_disagreement_score":0.9320677,"about_ca_system_score_codex":0.0000132890345,"about_ca_system_score_gemma":0.000035147707,"threshold_uncertainty_score":0.9916234},"labels":[],"label_agreement":null},{"id":"W2163612855","doi":"10.1177/0956797611407933","title":"Banking on a Bad Bet","year":2011,"lang":"en","type":"article","venue":"Psychological Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Outcome (game theory); Psychology; Matching (statistics); Task (project management); Econometrics; Cognition; Social psychology; Statistics; Economics; Mathematical economics; Mathematics; Psychiatry","score_opus":0.49187082861120285,"score_gpt":0.5132829181339926,"score_spread":0.02141208952278978,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2163612855","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.78078,0.0000061996698,0.0006902246,0.0002329769,0.000916153,0.000068662564,0.0000025628046,0.000055818786,0.2172474],"genre_scores_gemma":[0.99362767,0.0000028158588,0.00459612,0.0014452086,0.000052224754,0.0000058785386,1.337713e-7,0.0000041508415,0.0002658183],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99653286,0.00007399392,0.0004950083,0.0011325509,0.0012891683,0.00047641707],"domain_scores_gemma":[0.9979599,0.00048645766,0.00017367957,0.00096178567,0.00015660589,0.0002615365],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0053458377,0.0001390822,0.00021649868,0.00029747927,0.00038351616,0.00036350673,0.0027490337,0.00008457846,0.0052482584],"category_scores_gemma":[0.0026564172,0.00008030578,0.000107167776,0.0016418764,0.0009002532,0.00041049402,0.0002575899,0.00020910254,0.0055282298],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004491805,0.00029851592,0.0109421825,8.153414e-8,5.6088913e-7,0.000027307524,0.0002661508,0.0000059450736,0.0006727626,0.008338945,0.0020143,0.9773883],"study_design_scores_gemma":[0.00019474258,0.00057845755,0.3849636,0.000011190963,0.000002489588,0.000028667751,0.00011929063,0.00018671635,0.0005400539,0.60224706,0.010886461,0.0002412609],"about_ca_topic_score_codex":0.000010067035,"about_ca_topic_score_gemma":0.0000032594023,"teacher_disagreement_score":0.97714704,"about_ca_system_score_codex":0.00004474282,"about_ca_system_score_gemma":0.000025048099,"threshold_uncertainty_score":0.9956611},"labels":[],"label_agreement":null},{"id":"W2165760983","doi":"10.1111/j.1467-9779.2006.00260.x","title":"<scp>Welfare Economics with Intransitive Revealed Preferences: A Theory of the Endowment Effect</scp>","year":2006,"lang":"en","type":"article","venue":"Journal of Public Economic Theory","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Economics; Normative; Endowment; Welfare; Endowment effect; Microeconomics; Rationality; Econometrics","score_opus":0.041006775258459416,"score_gpt":0.2864494477156988,"score_spread":0.24544267245723939,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2165760983","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98045576,0.00023787709,0.0016767251,0.0005877892,0.0010336351,0.00030969668,0.000084543535,0.000012674437,0.015601292],"genre_scores_gemma":[0.99820715,0.000031998385,0.0004057017,0.00012230684,0.000273457,0.00000877747,0.0000019948584,0.000029949859,0.000918655],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99512696,0.0014911357,0.0021284837,0.00045811312,0.00037398134,0.00042133752],"domain_scores_gemma":[0.98917633,0.006236116,0.0031456545,0.000875015,0.0003783946,0.00018847396],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.015777634,0.0003309194,0.0009939305,0.0005182195,0.00021738019,0.00043692123,0.002048673,0.00016917697,0.00039019148],"category_scores_gemma":[0.0015196508,0.00018089598,0.0005651915,0.00023886783,0.0005325367,0.00095788395,0.00019740265,0.0004565269,0.00006123042],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006027278,0.00044273568,0.039650705,0.000020778407,0.00042688925,0.000024883275,0.0016686609,0.006247706,0.00016556133,0.49491188,0.003909539,0.45192793],"study_design_scores_gemma":[0.0021166974,0.0007895683,0.027693793,0.00010692006,0.00015569659,0.00031127248,0.00415979,0.00010397534,0.0014879319,0.94488496,0.01801,0.00017942482],"about_ca_topic_score_codex":0.000023311277,"about_ca_topic_score_gemma":0.00016458896,"teacher_disagreement_score":0.45174852,"about_ca_system_score_codex":0.000381199,"about_ca_system_score_gemma":0.0005618513,"threshold_uncertainty_score":0.7376724},"labels":[],"label_agreement":null},{"id":"W2165868536","doi":"10.1002/bdm.645","title":"Goal attainment as a resource: The cushion effect in risky choice above a goal","year":2009,"lang":"en","type":"article","venue":"Journal of Behavioral Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Outcome (game theory); Set (abstract data type); Psychology; Salient; Resource (disambiguation); Goal pursuit; Social psychology; Value (mathematics); Economics; Microeconomics; Computer science","score_opus":0.05689584315870033,"score_gpt":0.43832850563218967,"score_spread":0.38143266247348934,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2165868536","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9952866,0.00040459176,0.0010061429,0.0008908883,0.0012503335,0.00040558216,0.000008465873,0.00002345118,0.00072393747],"genre_scores_gemma":[0.99604046,0.000025075127,0.002498979,0.00078900566,0.0004229694,0.0000054555862,6.6339766e-7,0.000032067586,0.00018532324],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9906982,0.00082662393,0.0032868234,0.0007352837,0.00375881,0.0006942626],"domain_scores_gemma":[0.9894495,0.006316191,0.0022642622,0.001170383,0.0004976332,0.00030205102],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.01303724,0.0004818562,0.0011423242,0.0012917075,0.00040069962,0.0012345882,0.0026084401,0.00032420122,0.00042682094],"category_scores_gemma":[0.0042805164,0.00028168998,0.00085138704,0.0015614494,0.00013951941,0.0010010267,0.0003442579,0.0013905517,0.00035031847],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010312253,0.00037041825,0.02694178,8.247527e-7,0.0000058285823,0.0005196054,0.0005953002,0.0017107431,0.00057623483,0.000038561375,0.0052617206,0.9629478],"study_design_scores_gemma":[0.0077041453,0.009403849,0.7033191,0.0020250564,0.0003717243,0.0021155886,0.0042456775,0.0025701812,0.000543382,0.17863896,0.08760681,0.0014555502],"about_ca_topic_score_codex":0.000041627103,"about_ca_topic_score_gemma":0.000096092066,"teacher_disagreement_score":0.9614922,"about_ca_system_score_codex":0.0005669817,"about_ca_system_score_gemma":0.00018703674,"threshold_uncertainty_score":0.9999635},"labels":[],"label_agreement":null},{"id":"W2167366201","doi":"10.1017/s0140525x00003435","title":"Individual differences in reasoning: Implications for the rationality debate?","year":2000,"lang":"en","type":"article","venue":"Behavioral and Brain Sciences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4225,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Normative; Heuristics; Construal level theory; Rationality; Psychology; Cognitive psychology; Cognition; Axiom; Task (project management); Norm (philosophy); Computational model; Rational analysis; Social psychology; Computer science; Epistemology; Artificial intelligence; Mathematics","score_opus":0.3357910294845187,"score_gpt":0.45758631628237123,"score_spread":0.12179528679785251,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2167366201","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9865448,0.00016420432,0.00017543836,0.012157115,0.00013591652,0.00029394697,0.0001095393,0.00001907868,0.00039998943],"genre_scores_gemma":[0.997541,0.000021405589,0.0011359615,0.00046238842,0.000051684423,0.000085038395,0.000005318493,0.0000037125737,0.00069349917],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9979312,0.00010943681,0.0005521329,0.0005988197,0.00051730045,0.00029113074],"domain_scores_gemma":[0.9966602,0.0027229586,0.00013622182,0.00030360883,0.000089267036,0.00008777374],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0041779815,0.00013525951,0.00022280935,0.00014601009,0.0009156243,0.0009866175,0.0011002631,0.00006864739,0.00041848907],"category_scores_gemma":[0.00055408373,0.00007312846,0.000083689774,0.00076731184,0.00076344947,0.0005007982,0.000091261245,0.00009993775,0.000026457861],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009953591,0.00007325037,0.2867758,2.6574722e-7,9.194845e-7,3.6564222e-7,0.00031696956,0.000021531849,0.000032427102,0.0022178125,0.0016712775,0.7088794],"study_design_scores_gemma":[0.00020821266,0.00012172472,0.88897854,0.000008787847,0.000011063542,0.000012733607,0.00075333973,0.00062168174,0.000014214105,0.100682005,0.008444285,0.00014341887],"about_ca_topic_score_codex":0.00025538495,"about_ca_topic_score_gemma":0.00071626616,"teacher_disagreement_score":0.708736,"about_ca_system_score_codex":0.000016292826,"about_ca_system_score_gemma":0.00011267906,"threshold_uncertainty_score":0.9513976},"labels":[],"label_agreement":null},{"id":"W2167539968","doi":"10.1017/s0266267109990010","title":"EXTERNAL NORMS AND RATIONALITY OF CHOICE","year":2009,"lang":"en","type":"article","venue":"Economics and Philosophy","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Rationalizability; Axiom; Rationality; Mathematical economics; Norm (philosophy); Preference theory; Preference; Economics; Mathematics; Epistemology; Microeconomics; Philosophy","score_opus":0.12191257713421992,"score_gpt":0.37260557742137373,"score_spread":0.2506930002871538,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2167539968","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9904203,0.00020859428,0.00010341265,0.0020775567,0.0001592393,0.00005444652,0.000033902234,0.000005205128,0.00693739],"genre_scores_gemma":[0.99822193,0.00015869868,0.00084933697,0.000541083,0.0001634442,7.5846845e-7,0.0000014936076,0.000003503296,0.000059729184],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9989796,0.000020497835,0.0005029524,0.00031192336,0.00009346421,0.00009153806],"domain_scores_gemma":[0.9990156,0.0003379122,0.00023321577,0.00025994296,0.000058975274,0.00009434704],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007007386,0.00009415842,0.0002497912,0.00010313429,0.000078847654,0.00015730612,0.00020314261,0.000054162185,0.000076034376],"category_scores_gemma":[0.00013880285,0.00007615769,0.00005699369,0.00005763293,0.00008798268,0.0002901905,0.000056648023,0.000062610656,0.000021877928],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000054156037,0.000089230336,0.04558359,0.0000022101513,0.0000073948377,0.000001356703,0.00013704176,0.0001827484,0.000118331875,0.21391387,0.00022158501,0.73968846],"study_design_scores_gemma":[0.00023154567,0.00007865661,0.10000983,0.00000568588,0.0000039425004,0.000006957764,0.0000071711456,0.00094434916,0.000058445043,0.89151824,0.0070467936,0.00008841243],"about_ca_topic_score_codex":0.000012901711,"about_ca_topic_score_gemma":0.0000066200987,"teacher_disagreement_score":0.73960006,"about_ca_system_score_codex":0.000011077208,"about_ca_system_score_gemma":0.000022495764,"threshold_uncertainty_score":0.31056204},"labels":[],"label_agreement":null},{"id":"W2168460233","doi":"10.1348/000711009x480640","title":"Coping with stress through decisional control: Quantification of negotiating the environment","year":2010,"lang":"en","type":"article","venue":"British Journal of Mathematical and Statistical Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Coping (psychology); Negotiation; Cognition; Computer science; Cognitive psychology; Psychology; Hierarchy; Social psychology; Clinical psychology; Economics","score_opus":0.08798309826525118,"score_gpt":0.40092374668028197,"score_spread":0.3129406484150308,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2168460233","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.46522826,0.000108094355,0.5333835,0.00071299303,0.00016826019,0.00006636349,0.000064428124,0.0000018875659,0.0002662363],"genre_scores_gemma":[0.9425409,0.000045895616,0.05712119,0.00021154404,0.000054065513,0.0000021305334,0.0000011298683,0.000007997851,0.00001513716],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99742496,0.00018791555,0.0012718919,0.00023654739,0.0007078394,0.00017085172],"domain_scores_gemma":[0.9920001,0.006737405,0.0006766202,0.0002473774,0.00022684655,0.00011163195],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024855123,0.00010198016,0.0004671948,0.000051494346,0.00013093566,0.00019609713,0.00043094676,0.00009027479,0.000670554],"category_scores_gemma":[0.003320954,0.000060029663,0.000064028805,0.00008420364,0.0007114699,0.00015109993,0.000044205302,0.00044658998,0.000027140022],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003601943,0.0008988484,0.002772106,0.000016751792,0.00006423061,0.00022465891,0.00029608118,0.00048326136,0.0010778984,0.16786084,0.0051150755,0.82083005],"study_design_scores_gemma":[0.0013560889,0.00045907855,0.037284885,0.00010716713,0.00006633944,0.003577301,0.00031024922,0.0026231355,0.00002967381,0.9512377,0.0028055746,0.0001428529],"about_ca_topic_score_codex":0.000005723677,"about_ca_topic_score_gemma":0.0000070903766,"teacher_disagreement_score":0.8206872,"about_ca_system_score_codex":0.0000054336797,"about_ca_system_score_gemma":0.000029458797,"threshold_uncertainty_score":0.7342096},"labels":[],"label_agreement":null},{"id":"W2169258761","doi":"10.1177/1948550613490964","title":"When the Going Gets Tough","year":2013,"lang":"en","type":"article","venue":"Social Psychological and Personality Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":58,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Salience (neuroscience); Roulette; Psychology; Game of chance; Economics; Economic risk; Control (management); Social psychology; Actuarial science; Cognitive psychology","score_opus":0.3031078566846019,"score_gpt":0.4740597776891398,"score_spread":0.17095192100453793,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2169258761","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9590717,0.000057829475,0.00011514596,0.020206917,0.00037335517,0.00013351254,0.000006706479,0.000027287557,0.020007528],"genre_scores_gemma":[0.9946783,0.0000052599466,0.00048114528,0.003517189,0.00018747678,0.000009900496,2.636469e-7,0.0000025241156,0.0011178968],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99740386,0.00014977193,0.00036122184,0.0007256188,0.0009870786,0.00037243395],"domain_scores_gemma":[0.9984562,0.0007176498,0.00013705119,0.00031786144,0.00021416775,0.00015708494],"candidate_categories":["sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.004504849,0.00011946517,0.00019843389,0.00005524835,0.0014559635,0.0012419224,0.0013099469,0.00008806489,0.0017112477],"category_scores_gemma":[0.0013420692,0.00005878935,0.00009255965,0.00045457843,0.0023851881,0.0005809276,0.0002717806,0.00022886686,0.0009790988],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000095943415,0.000062937,0.011519799,4.719763e-7,0.0000013925763,0.0000022273468,0.0030082231,4.399472e-7,0.00058809755,0.0021373515,0.016295886,0.96637356],"study_design_scores_gemma":[0.000103542065,0.00006162765,0.4932992,0.0000020945608,0.0000027209649,0.000010025486,0.0019851008,0.00019347273,0.000006312428,0.48600537,0.01820223,0.00012831224],"about_ca_topic_score_codex":0.00018639116,"about_ca_topic_score_gemma":0.000028826007,"teacher_disagreement_score":0.9662453,"about_ca_system_score_codex":0.000027340497,"about_ca_system_score_gemma":0.0000305929,"threshold_uncertainty_score":0.999844},"labels":[],"label_agreement":null},{"id":"W2169861135","doi":"10.2139/ssrn.761608","title":"Actions and Beliefs: Estimating Distribution-Based Preferences Using a Large Scale Experiment with Probability Questions on Expectations","year":2005,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Ultimatum game; Dictator game; Dictator; Economics; Equity (law); Inequity aversion; Population; Microeconomics; Psychology; Econometrics; Inequality; Mathematics; Political science; Politics","score_opus":0.08438490108740206,"score_gpt":0.3913081046609685,"score_spread":0.30692320357356645,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2169861135","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7995596,0.00018707187,0.19915392,0.00067433785,0.00010997693,0.00015252351,0.000032518343,0.000032221476,0.000097863965],"genre_scores_gemma":[0.9761482,0.000014084367,0.023552384,0.000034416105,0.00014822213,0.000022012164,0.000007673545,0.000011220182,0.000061806815],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9972695,0.00016206123,0.00057673984,0.00043314445,0.0005858951,0.0009726337],"domain_scores_gemma":[0.99848825,0.0004269594,0.0003479516,0.0003170666,0.00027392007,0.0001458626],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021947755,0.00018036019,0.00023275732,0.000173198,0.0011800355,0.00044971454,0.0002861974,0.00006662365,0.0000624272],"category_scores_gemma":[0.00054279534,0.00012700658,0.00008651104,0.00036804783,0.000116827716,0.0004909028,0.000035990513,0.00076303066,0.00002942105],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030905096,0.0025476445,0.020881956,0.000005515603,0.00010414654,0.000004011047,0.003404314,0.115245774,0.00047198235,0.03102509,0.00024202048,0.8257585],"study_design_scores_gemma":[0.0025635737,0.0020355068,0.0041906266,0.0003358304,0.00013668693,0.00055153866,0.028781325,0.2180579,0.0007097587,0.7390103,0.0027133352,0.0009136593],"about_ca_topic_score_codex":0.000034279936,"about_ca_topic_score_gemma":0.0018353832,"teacher_disagreement_score":0.82484484,"about_ca_system_score_codex":0.0010934162,"about_ca_system_score_gemma":0.0015785244,"threshold_uncertainty_score":0.90759987},"labels":[],"label_agreement":null},{"id":"W2171794807","doi":"10.1093/ije/dyr093","title":"Commentary: Money and models: double-edged swords","year":2011,"lang":"en","type":"letter","venue":"International Journal of Epidemiology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Lottery; Pill; Population; Premise; Accidental; Economics; Actuarial science; Medicine; Microeconomics","score_opus":0.42341555404415354,"score_gpt":0.4683751396720869,"score_spread":0.04495958562793334,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2171794807","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.033297308,0.0013854429,0.00849831,0.9424968,0.011333131,0.000115831754,0.00012578892,0.000014141753,0.0027332618],"genre_scores_gemma":[0.024945581,0.0009392466,0.009550523,0.95679426,0.0068663685,0.000005040258,0.00006058431,0.000044438293,0.00079394766],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9938729,0.00096038304,0.0033071954,0.0005781322,0.00089749764,0.00038392763],"domain_scores_gemma":[0.98522073,0.009001667,0.0037014843,0.0005270576,0.0013739879,0.00017504352],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010401525,0.00034478414,0.0014606133,0.0011121496,0.000070744965,0.00013758393,0.0029757614,0.00080059236,0.00073162804],"category_scores_gemma":[0.004011148,0.00024228854,0.0005337038,0.00010886768,0.00037242583,0.0005743377,0.00051319966,0.0021332223,0.00011667283],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002508332,0.000036320103,0.0020192352,0.0000012765612,0.00017150909,0.00043077974,0.000099446224,0.00016585887,0.0000014651198,0.00048813302,0.90048313,0.09585201],"study_design_scores_gemma":[0.0005855813,0.000113571565,0.0001786171,0.000059351045,0.000041604093,0.0007067075,0.000027985452,0.0005425373,0.0000023903967,0.3903465,0.6072428,0.000152351],"about_ca_topic_score_codex":0.00022467645,"about_ca_topic_score_gemma":0.000024443649,"teacher_disagreement_score":0.38985837,"about_ca_system_score_codex":0.00018541567,"about_ca_system_score_gemma":0.000128074,"threshold_uncertainty_score":0.988024},"labels":[],"label_agreement":null},{"id":"W2171935043","doi":"10.5465/amr.2006.22527462","title":"Integrating Theories of Motivation","year":2006,"lang":"en","type":"article","venue":"Academy of Management Review","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":734,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Expectancy theory; Behaviorism; Psychology; Cumulative prospect theory; Construct (python library); Organizational behavior; Cognitive science; Cognitive psychology; Prospect theory; Social psychology; Computer science; Economics; Microeconomics","score_opus":0.11985058076134746,"score_gpt":0.41490250420021485,"score_spread":0.2950519234388674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2171935043","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6669038,0.07500775,0.012984423,0.008568027,0.00041628658,0.0018829516,0.000025777765,0.00008956896,0.23412141],"genre_scores_gemma":[0.98422116,0.009055112,0.0048733633,0.00055736915,0.000032301574,0.000011183107,0.000002954696,0.000007386401,0.0012391692],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9977461,0.000099676145,0.0012321898,0.00024930987,0.0005677406,0.00010499741],"domain_scores_gemma":[0.9983579,0.00052158756,0.0007967842,0.00023506397,0.00007108268,0.00001759499],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033776704,0.00010038352,0.0004229652,0.00016473857,0.000035887333,0.000025949068,0.000624244,0.00004174078,0.00029064727],"category_scores_gemma":[0.0006185661,0.00006726264,0.00015094593,0.0005498635,0.00007873865,0.00022565809,0.00016336744,0.00008414527,0.00006645467],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002282851,0.000028361135,0.0021177796,0.00019447645,0.0000059361864,2.812033e-7,0.0000080620675,0.000017285449,0.000019392857,0.15592112,0.011102095,0.8305829],"study_design_scores_gemma":[0.00013508493,0.000027160964,0.018457426,0.0026629772,0.00008109748,0.0000011333533,0.00012560347,0.0000440474,0.00045909564,0.7328511,0.24502648,0.00012882303],"about_ca_topic_score_codex":0.000012121331,"about_ca_topic_score_gemma":9.849219e-7,"teacher_disagreement_score":0.8304541,"about_ca_system_score_codex":0.000014281675,"about_ca_system_score_gemma":0.000004661855,"threshold_uncertainty_score":0.31823838},"labels":[],"label_agreement":null},{"id":"W2172106739","doi":"10.3389/fnhum.2014.00797","title":"Different Neural Systems Contribute to Semantic Bias and Conflict Detection in the Inclusion Fallacy Task","year":2014,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Beijing Nova Program; State Key Laboratory of Cognitive Neuroscience and Learning; National Natural Science Foundation of China","keywords":"Fallacy; Premise; Generalization; Categorization; Cognitive psychology; Psychology; Cognition; Task (project management); Set (abstract data type); Cognitive science; Computer science; Artificial intelligence; Epistemology; Neuroscience","score_opus":0.10013063749643765,"score_gpt":0.3543238772839557,"score_spread":0.25419323978751807,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2172106739","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.966567,0.00006644253,0.029281512,0.0004294656,0.0030817825,0.00046574444,0.0000062091294,0.000022763013,0.000079108155],"genre_scores_gemma":[0.9989351,0.00001038496,0.00003687528,0.0008350984,0.000054230797,0.000024045039,5.871104e-7,0.000009256089,0.00009443131],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9963468,0.0006891981,0.0007646273,0.0008326508,0.00095824304,0.0004084823],"domain_scores_gemma":[0.9982402,0.0006598781,0.00023943899,0.000660731,0.00006621476,0.0001335359],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0044019986,0.00020185258,0.00041478442,0.0006877201,0.0006520847,0.00087073614,0.0014063827,0.000073539144,0.0000019335062],"category_scores_gemma":[0.0026040056,0.00012812212,0.00005768173,0.00090643164,0.00023256832,0.00033960526,0.0007532039,0.00027760846,0.000004056818],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016905277,0.0003914865,0.47494116,0.000021190368,0.000001963098,0.0001027313,0.008565997,0.023021875,0.03826932,0.0007616461,0.0052918014,0.44846177],"study_design_scores_gemma":[0.0010923775,0.00070445664,0.47290057,0.000091597096,0.000010730759,0.000057086683,0.0011296163,0.48625156,0.00040152943,0.014112261,0.022753228,0.000494968],"about_ca_topic_score_codex":0.00015743684,"about_ca_topic_score_gemma":0.00031621213,"teacher_disagreement_score":0.4632297,"about_ca_system_score_codex":0.00008633095,"about_ca_system_score_gemma":0.000013411316,"threshold_uncertainty_score":0.83965284},"labels":[],"label_agreement":null},{"id":"W2173645876","doi":"10.1111/cjag.12089","title":"Existing Food Habits and Recent Choices Lead to Disregard of Food Safety Announcements","year":2015,"lang":"en","type":"article","venue":"Canadian Journal of Agricultural Economics/Revue canadienne d agroeconomie","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Cognitive dissonance; Commit; Confirmation bias; Incentive; Food safety; Psychology; Social psychology; Perception; Cognition; Marketing; Economics; Welfare economics; Advertising; Business; Microeconomics; Medicine; Computer science","score_opus":0.20056402583352304,"score_gpt":0.2878393866063336,"score_spread":0.08727536077281059,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2173645876","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9899403,0.00048409615,0.000021634933,0.0030928599,0.0027834214,0.00030280015,0.0007483862,0.0000067734613,0.0026197636],"genre_scores_gemma":[0.99761665,0.00006186916,0.0008986007,0.00036241216,0.0005382383,0.0000056696695,0.000021382708,0.000024877354,0.000470287],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9957924,0.00010075321,0.0024839926,0.00067436264,0.000088283996,0.00086023845],"domain_scores_gemma":[0.99264383,0.0004640647,0.0017955877,0.00049238437,0.0011783332,0.0034257798],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0024265014,0.00040792776,0.0011667514,0.00078559265,0.00025596764,0.00051899976,0.0013430069,0.00017797406,0.00013186317],"category_scores_gemma":[0.002118266,0.00032292388,0.0002685378,0.0004000125,0.0001858,0.0011218517,0.00012334352,0.00031050376,0.00006506664],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00079694495,0.0001796675,0.107226424,0.00006850918,0.00090346613,0.00013251223,0.014296694,0.032682147,0.00039110842,0.01846383,0.047986183,0.7768725],"study_design_scores_gemma":[0.0044445316,0.008075211,0.14836052,0.00050985656,0.0002322125,0.0015985167,0.021515217,0.00031172147,0.00060095836,0.05984035,0.75228983,0.0022210707],"about_ca_topic_score_codex":0.0062103802,"about_ca_topic_score_gemma":0.7482949,"teacher_disagreement_score":0.77465147,"about_ca_system_score_codex":0.0020016967,"about_ca_system_score_gemma":0.001355173,"threshold_uncertainty_score":0.9999223},"labels":[],"label_agreement":null},{"id":"W2179187724","doi":"","title":"A signal detection analysis of contingency data","year":2004,"lang":"en","type":"article","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Contingency; SIGNAL (programming language); Detection theory; Contingency table; Task (project management); Computer science; Interpretation (philosophy); Psychology; Artificial intelligence; Social psychology; Cognitive psychology; Data mining; Machine learning; Epistemology; Engineering","score_opus":0.32624433343535153,"score_gpt":0.4614711499477292,"score_spread":0.13522681651237767,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2179187724","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.88135356,0.000020116335,0.11509844,0.00006999243,0.00014266028,0.000039806902,0.000037910966,0.000019938585,0.0032176054],"genre_scores_gemma":[0.9968536,0.0000029400928,0.0028488454,0.00004362347,0.000020171383,7.4496575e-7,0.000008269677,0.0000032727573,0.0002185361],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9982321,0.000034263663,0.0006673602,0.00043655338,0.0005156834,0.000114037895],"domain_scores_gemma":[0.9979884,0.00037068824,0.00026556873,0.0011304106,0.00019006022,0.0000548881],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0019469913,0.000070948605,0.00031040283,0.00061168836,0.000060498587,0.00011360046,0.0010324103,0.000051016108,0.0013273313],"category_scores_gemma":[0.00078975875,0.00004976384,0.0001455123,0.0018097573,0.0000489615,0.0003622037,0.00024401736,0.00005511316,0.00018092553],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016782156,0.00008360008,0.0061241714,2.6150744e-7,0.00008181904,0.0000025288928,0.00008212528,0.004525811,0.0023336506,0.00018288239,0.00021000595,0.9863564],"study_design_scores_gemma":[0.0029077295,0.00077370554,0.22462665,0.000042644446,0.003935979,0.000026152224,0.004275166,0.23077302,0.038566057,0.45656142,0.03613558,0.0013759173],"about_ca_topic_score_codex":0.00037647193,"about_ca_topic_score_gemma":0.0017362062,"teacher_disagreement_score":0.98498046,"about_ca_system_score_codex":0.00002369606,"about_ca_system_score_gemma":0.000044736145,"threshold_uncertainty_score":0.99958557},"labels":[],"label_agreement":null},{"id":"W2182569073","doi":"","title":"On Microeconomic Errors and Ordinal Group Decision Making","year":2012,"lang":"en","type":"article","venue":"National Conference on Artificial Intelligence","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Impossibility; Mathematical economics; Von Neumann architecture; Group (periodic table); Group decision-making; Pareto principle; Game theory; Decision theory; Social choice theory; Computer science; Economics; Mathematics; Microeconomics; Mathematical optimization; Psychology; Social psychology","score_opus":0.3247082787357758,"score_gpt":0.46449957791930896,"score_spread":0.13979129918353317,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2182569073","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9586214,0.0000371184,0.027638711,0.0006089874,0.0013283808,0.00017982944,0.00004149779,0.0000410929,0.011502979],"genre_scores_gemma":[0.9957537,0.000012067978,0.0030418239,0.0008301126,0.00022405568,0.000013496181,0.000004676394,0.000016329763,0.00010372883],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99658424,0.0001274838,0.0010014289,0.0007099663,0.0011511995,0.0004256601],"domain_scores_gemma":[0.99518204,0.0034105498,0.00035472718,0.00037464485,0.00046458357,0.00021346315],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.003291665,0.00026337677,0.00033376613,0.0006203374,0.00034945278,0.0006044721,0.00069387973,0.00016115778,0.0022186565],"category_scores_gemma":[0.0036021436,0.00021875884,0.000118843964,0.00038125223,0.00021948836,0.00061084493,0.00015897358,0.00033075718,0.004766563],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018301465,0.00014327034,0.00064662425,5.7140767e-7,0.0000034887178,0.0000015365098,0.00012178307,0.0003966905,0.00024068014,0.3284515,0.00059405103,0.6692168],"study_design_scores_gemma":[0.000045856337,0.00019821698,0.0059190127,0.00007737673,0.000006217721,0.000017752243,0.0005008219,0.0131356,0.000900639,0.97672224,0.0021584767,0.00031779762],"about_ca_topic_score_codex":0.000011424802,"about_ca_topic_score_gemma":0.000067528905,"teacher_disagreement_score":0.668899,"about_ca_system_score_codex":0.00018789603,"about_ca_system_score_gemma":0.00010928872,"threshold_uncertainty_score":0.99869347},"labels":[],"label_agreement":null},{"id":"W2183236895","doi":"","title":"Measuring the degree to which probability weighting affects risk-taking Behavior in financial decisions","year":2012,"lang":"en","type":"article","venue":"Journal of finance and investment analysis","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Weighting; Econometrics; Degree (music); Perception; Actuarial science; Expected utility hypothesis; Prospect theory; Risk perception; Financial risk; Risk-seeking; Statistics; Economics; Psychology; Mathematics; Microeconomics","score_opus":0.2363672371012722,"score_gpt":0.3670036610448052,"score_spread":0.130636423943533,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2183236895","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99700403,0.0007161003,0.0011069797,0.00035874866,0.00032398876,0.00018883964,0.0000069398084,0.000003979129,0.0002904127],"genre_scores_gemma":[0.99326766,0.0001244235,0.006169192,0.00022770003,0.00015853193,0.000014131576,4.3819534e-7,0.000007552813,0.000030381118],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99661916,0.0003453246,0.0013122269,0.00033931664,0.0009725392,0.00041142202],"domain_scores_gemma":[0.9951064,0.0015315893,0.0022052038,0.00054953404,0.0003981829,0.00020907489],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.010197105,0.0001987308,0.00070205424,0.0010332873,0.00035694524,0.00028746706,0.00070859096,0.00009830174,0.000054578093],"category_scores_gemma":[0.012554502,0.00011598037,0.00039082926,0.0033072121,0.00006728425,0.0008142856,0.0002035931,0.0004179594,0.00002186644],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000038817016,0.00016805205,0.7733222,6.739148e-7,0.000031587442,0.000007807272,0.00071935816,0.0017614762,0.000058349473,0.00023551293,0.00025998897,0.22339617],"study_design_scores_gemma":[0.00024760325,0.00012798031,0.98766464,0.00005977859,0.00047813283,0.000016317594,0.00026811444,0.000655926,0.0001508399,0.00812013,0.0020492505,0.00016128273],"about_ca_topic_score_codex":0.00008382209,"about_ca_topic_score_gemma":0.001463766,"teacher_disagreement_score":0.22323489,"about_ca_system_score_codex":0.00016503524,"about_ca_system_score_gemma":0.00013393293,"threshold_uncertainty_score":0.9957632},"labels":[],"label_agreement":null},{"id":"W2184681077","doi":"10.1093/oxfordhb/9780199734689.013.0022","title":"On the Distinction Between Rationality and Intelligence: Implications for Understanding Individual Differences in Reasoning","year":2012,"lang":"en","type":"book-chapter","venue":"Oxford University Press eBooks","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":160,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Rationality; Irrationality; Cognition; Ecological rationality; Psychology; Context (archaeology); Epistemology; Great Rationality Debate; Extension (predicate logic); Cognitive science; Cognitive psychology; Social psychology; Computer science; Philosophy","score_opus":0.440341880957961,"score_gpt":0.3617296448261046,"score_spread":0.07861223613185642,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2184681077","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.084453516,0.000064598054,0.094943926,0.0005360236,0.0003720243,0.0013293932,0.0015720711,0.00006272492,0.8166657],"genre_scores_gemma":[0.9300121,0.000034935387,0.00024551846,0.000029165809,0.00008531573,0.0000038875564,0.000042602147,0.000014681515,0.069531806],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99858123,0.00006927578,0.00036786546,0.00046253265,0.00033198405,0.00018711665],"domain_scores_gemma":[0.9949825,0.0040338147,0.000408665,0.00039372724,0.00009446259,0.000086836924],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012737819,0.00020169611,0.00031679,0.00024436624,0.0005206052,0.00025041413,0.00062829535,0.00023049621,0.00003490007],"category_scores_gemma":[0.00026011796,0.00015386319,0.00011267694,0.000024510606,0.00023601783,0.00015753912,0.0002689502,0.00030065025,0.0000010648946],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033542416,0.0000067184023,0.0027351927,0.0000022881825,0.00001762647,3.6677002e-7,0.00022259768,0.0000038583835,2.4155793e-7,0.8955638,0.00020300316,0.10121078],"study_design_scores_gemma":[0.00013711356,0.000055639233,0.010243057,0.00009333726,0.00009731196,0.000001438926,0.00062854856,0.00007235764,0.0000027650656,0.8625155,0.12591025,0.00024269137],"about_ca_topic_score_codex":0.000017522143,"about_ca_topic_score_gemma":0.00008021002,"teacher_disagreement_score":0.8455586,"about_ca_system_score_codex":0.00022326653,"about_ca_system_score_gemma":0.000057502864,"threshold_uncertainty_score":0.62743586},"labels":[],"label_agreement":null},{"id":"W2186683519","doi":"","title":"Decision under Complete Uncertainty: Bridging Economic and Philosophical Research","year":2012,"lang":"en","type":"article","venue":"Library and Archives Canada (Government of Canada)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Bridging (networking); Decision theory; Computer science; Management science; Epistemology; Economics; Philosophy; Microeconomics","score_opus":0.07887474952652274,"score_gpt":0.2998956546475922,"score_spread":0.22102090512106948,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2186683519","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9524197,0.00026932266,0.00019361232,0.008329154,0.00045367473,0.00011353995,0.00014970636,0.000006489805,0.038064823],"genre_scores_gemma":[0.9971961,0.000068376765,0.00089547323,0.0008028402,0.00016330006,0.0000030377612,0.000002253195,0.000015788106,0.0008528363],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9959257,0.00017769285,0.00057265174,0.00041764724,0.0024150386,0.00049125106],"domain_scores_gemma":[0.9951879,0.0037052247,0.00016809578,0.00039743655,0.000002012898,0.0005393415],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029017203,0.00016916066,0.0003618017,0.00009636518,0.00038773616,0.00015004835,0.0004784473,0.000040881307,0.00013459551],"category_scores_gemma":[0.000054137367,0.00013975424,0.000036886162,0.000119475255,0.0002463078,0.0007286032,0.00055169273,0.00024253309,1.2246494e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007652674,0.000066441215,0.09452744,0.000017764243,0.00004069538,0.00004059356,0.00018404191,0.0010800208,0.0028260935,0.28123766,0.0057473537,0.6134666],"study_design_scores_gemma":[0.0009922911,0.0001696697,0.2432606,0.00017079253,0.000023879431,0.000071606504,0.0063214726,0.02447681,0.0030322208,0.60444766,0.11633555,0.00069742434],"about_ca_topic_score_codex":0.0020906911,"about_ca_topic_score_gemma":0.010511824,"teacher_disagreement_score":0.6127692,"about_ca_system_score_codex":0.000024273588,"about_ca_system_score_gemma":0.00083580834,"threshold_uncertainty_score":0.58658445},"labels":[],"label_agreement":null},{"id":"W2188657252","doi":"10.1287/mnsc.2015.2349","title":"Intertemporal Uncertainty Avoidance: When the Future Is Uncertain, People Prefer the Present, and When the Present Is Uncertain, People Prefer the Future","year":2016,"lang":"en","type":"article","venue":"Management Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":60,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Risk-seeking; Intertemporal choice; Economics; Uncertainty avoidance; Value (mathematics); Prospect theory; Relation (database); Psychology; Microeconomics; Social psychology; Computer science; Individualism","score_opus":0.05837759396561091,"score_gpt":0.33853616275240406,"score_spread":0.2801585687867931,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2188657252","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.56189495,0.0023622212,0.0014340626,0.41847056,0.0040210094,0.003161218,0.00013292563,0.00012400365,0.008399053],"genre_scores_gemma":[0.9527608,0.0008601677,0.00024264152,0.007837164,0.0013792341,0.00033863724,0.0000031420366,0.00004068437,0.03653753],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99132305,0.00066217856,0.001134137,0.002013493,0.0036622945,0.0012048703],"domain_scores_gemma":[0.99200994,0.0018929039,0.00072921085,0.0045362995,0.00057206204,0.00025958612],"candidate_categories":["sts","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.009587501,0.00062787754,0.0005360266,0.00026325765,0.0033827438,0.0032725611,0.009691634,0.00015452817,0.001526627],"category_scores_gemma":[0.00034824447,0.00020487688,0.00033119888,0.0018234486,0.0020797555,0.001407308,0.0040749596,0.0005882751,0.0004408213],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010423202,0.00009477275,0.010716305,0.000012769874,0.000057707915,0.0000055459723,0.019056542,0.00032570516,0.000020204872,0.0023779664,0.57691395,0.3903143],"study_design_scores_gemma":[0.0005220372,0.00010159693,0.03750206,0.00006965659,0.000091416005,0.000017494593,0.028380865,0.004565982,0.000050359737,0.07597894,0.8523013,0.00041826104],"about_ca_topic_score_codex":0.00065999944,"about_ca_topic_score_gemma":0.00265382,"teacher_disagreement_score":0.41063341,"about_ca_system_score_codex":0.00024887358,"about_ca_system_score_gemma":0.00021031832,"threshold_uncertainty_score":0.99938613},"labels":[],"label_agreement":null},{"id":"W2207156987","doi":"10.2139/ssrn.2259327","title":"Ratings and Asset Allocation: An Experimental Analysis","year":2013,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Asset allocation; Business; Actuarial science; Economics; Econometrics; Financial economics; Portfolio","score_opus":0.05184616152527,"score_gpt":0.38094753990632824,"score_spread":0.32910137838105824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2207156987","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99413353,0.0005503802,0.004045915,0.00064180733,0.00012591679,0.00007333481,0.000001336333,0.000016884878,0.00041089574],"genre_scores_gemma":[0.99821615,0.000091387425,0.00064226496,0.00015327774,0.00011940646,0.000006034496,0.0000031598977,0.000009604741,0.0007586931],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99740523,0.00014659774,0.00058847695,0.0003756581,0.00056372466,0.00092031603],"domain_scores_gemma":[0.9987531,0.00018188021,0.00031095755,0.00034859232,0.00022408018,0.00018140774],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.003848639,0.00013689764,0.0002802599,0.0003922244,0.00032759763,0.001067987,0.00054573844,0.000068700225,0.00078255753],"category_scores_gemma":[0.00022742356,0.00010014088,0.00014652759,0.00059063017,0.000064818545,0.0011558185,0.000070919166,0.00060296175,0.00024610528],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000263711,0.00022176186,0.030813646,2.4966477e-7,0.00022192267,0.0000034780599,0.0007483188,0.00026927452,0.0040638847,0.01126224,0.000987373,0.9513815],"study_design_scores_gemma":[0.0006126903,0.0007396875,0.014553558,0.0000043546775,0.00016148882,0.00042743896,0.019805253,0.008702165,0.0005607043,0.95237964,0.001659054,0.00039394113],"about_ca_topic_score_codex":0.00013054539,"about_ca_topic_score_gemma":0.00046781727,"teacher_disagreement_score":0.9509875,"about_ca_system_score_codex":0.0002773274,"about_ca_system_score_gemma":0.0004188027,"threshold_uncertainty_score":0.999969},"labels":[],"label_agreement":null},{"id":"W2208714138","doi":"","title":"Can We Steer Income Comparison Attitudes by Information Provision?: Evidence from Randomized Survey Experiments in the US and the UK","year":2015,"lang":"en","type":"preprint","venue":"Econstor (Econstor)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Japan Society for the Promotion of Science","keywords":"Welfare; Randomized experiment; Demographic economics; Economics; Public economics; Psychology; Medicine","score_opus":0.12797543062644612,"score_gpt":0.39360442847568466,"score_spread":0.26562899784923855,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2208714138","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98491144,0.0063662506,0.00022160495,0.0012718932,0.003236853,0.0024343145,0.0008060795,0.000045577748,0.0007059799],"genre_scores_gemma":[0.99796045,0.00042163106,0.00041355545,0.00042656774,0.000108437314,0.00035685167,0.0001345168,0.000023896471,0.00015410276],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.98893595,0.0043190676,0.0034795424,0.001126972,0.0016432023,0.0004952888],"domain_scores_gemma":[0.97406393,0.020510018,0.002474067,0.002140634,0.0005667498,0.00024462692],"candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.028251316,0.00069800805,0.0025556802,0.0005297239,0.0003700601,0.0026002973,0.003168041,0.0005440792,0.00051737635],"category_scores_gemma":[0.010944692,0.00038725886,0.0004114597,0.0003676298,0.0016386189,0.001054228,0.0016513653,0.0012685644,0.00039109364],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0054753763,0.000104277315,0.95219773,0.000010442817,0.00007900313,0.0000036797887,0.008510766,0.0003761386,0.0000028262295,0.00005357415,0.022829482,0.010356689],"study_design_scores_gemma":[0.13040084,0.00026075658,0.7509317,0.0025966794,0.00045039307,0.00006482411,0.009702983,0.021493834,0.00010648642,0.068753324,0.011902041,0.0033361753],"about_ca_topic_score_codex":0.0124196615,"about_ca_topic_score_gemma":0.007587713,"teacher_disagreement_score":0.20126608,"about_ca_system_score_codex":0.00047088388,"about_ca_system_score_gemma":0.00090110017,"threshold_uncertainty_score":0.9998579},"labels":[],"label_agreement":null},{"id":"W2213709983","doi":"10.1016/j.cognition.2013.03.003","title":"The role of answer fluency and perceptual fluency in the monitoring and control of reasoning: Reply to","year":2013,"lang":"en","type":"letter","venue":"Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan; Red Deer College; University of Waterloo","funders":"","keywords":"Fluency; Psychology; Cognitive psychology; Perception; Variety (cybernetics); Metacognition; Cognition; Meaning (existential); Control (management); Processing fluency; Cognitive science; Computer science; Artificial intelligence; Mathematics education; Neuroscience","score_opus":0.050266336855068094,"score_gpt":0.3348025094932448,"score_spread":0.2845361726381767,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2213709983","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97501737,0.0008127596,0.000042265485,0.022169812,0.00028565273,0.00045215577,0.000056457797,0.0000071257864,0.0011563745],"genre_scores_gemma":[0.98794824,0.000090107394,0.00014856094,0.011334576,0.00032381158,0.00004407009,0.000005885038,0.000013837131,0.00009089519],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9976999,0.00026563095,0.00077211234,0.0004293402,0.00062752987,0.00020548607],"domain_scores_gemma":[0.9961182,0.0025029457,0.00041704977,0.0005171078,0.00040609,0.00003859183],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018596683,0.00017353271,0.00037959625,0.00022088831,0.00013798862,0.00026941145,0.0005035395,0.00022113544,0.000038100723],"category_scores_gemma":[0.0020903847,0.00009753503,0.00007569107,0.00023807104,0.00021083068,0.00020486962,0.00008560584,0.00045966517,0.000032958807],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009766516,0.000054613018,0.020574044,0.00001590307,0.00002209903,0.000018450834,0.0039400146,0.000004944318,0.002622657,0.0000425055,0.061061196,0.91154593],"study_design_scores_gemma":[0.0022958254,0.0011693801,0.22019935,0.0016369129,0.0003884622,0.00013796086,0.028988281,0.0005096384,0.002178634,0.21367307,0.52766246,0.0011600184],"about_ca_topic_score_codex":0.00008242403,"about_ca_topic_score_gemma":0.0000069621083,"teacher_disagreement_score":0.9103859,"about_ca_system_score_codex":0.000017309983,"about_ca_system_score_gemma":0.000037487636,"threshold_uncertainty_score":0.3977363},"labels":[],"label_agreement":null},{"id":"W2216166587","doi":"","title":"Revealed Preference Foundations of Expectations-Based Reference-Dependence","year":2013,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Unobservable; Axiom; Preference; Revealed preference; Mathematical economics; Econometrics; Economics; Positive economics; Mathematics; Microeconomics","score_opus":0.3176147541834413,"score_gpt":0.4632364730765734,"score_spread":0.14562171889313208,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2216166587","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.938063,0.000073729134,0.000113499766,0.00044367742,0.0006859512,0.0011088809,0.00023192762,0.000050654213,0.059228644],"genre_scores_gemma":[0.98968196,0.0005926954,0.0063995346,0.000051984898,0.00008643274,0.0004853862,0.000086099106,0.00005322116,0.0025627073],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99219257,0.0008872595,0.0027663484,0.0019567185,0.0013827595,0.0008143553],"domain_scores_gemma":[0.9868021,0.006668169,0.0012885263,0.0033899483,0.0015316866,0.0003195798],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.005872232,0.00045393337,0.0011646979,0.0020570834,0.00028272305,0.00084545737,0.0037184665,0.00072516216,0.0017032054],"category_scores_gemma":[0.008111365,0.0004236837,0.0003484093,0.0006435463,0.00074348395,0.00044910755,0.0017130452,0.0019871856,0.0004998146],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010957806,0.00039750323,0.009038695,0.00004709036,0.000032128257,0.000015507214,0.00052444625,0.020779917,0.00017436343,0.001054684,0.0005616509,0.9672644],"study_design_scores_gemma":[0.0028268956,0.00077552453,0.06646584,0.0018785137,0.00006788373,0.000021405842,0.010228618,0.14613312,0.0010804626,0.73229134,0.03537181,0.0028585803],"about_ca_topic_score_codex":0.00029897955,"about_ca_topic_score_gemma":0.0009249301,"teacher_disagreement_score":0.96440583,"about_ca_system_score_codex":0.000816816,"about_ca_system_score_gemma":0.0023394707,"threshold_uncertainty_score":0.9998215},"labels":[],"label_agreement":null},{"id":"W2218675706","doi":"10.1007/s10683-021-09739-2","title":"Experimental elicitation of ambiguity attitude using the random incentive system","year":2022,"lang":"en","type":"article","venue":"Experimental Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":47,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek","keywords":"Ambiguity; Incentive compatibility; Incentive; Ambiguity aversion; Certainty; Decision maker; Microeconomics; Compatibility (geochemistry); Computer science; Econometrics; Mathematical economics; Economics; Mathematics; Operations research; Engineering","score_opus":0.15234836393363366,"score_gpt":0.4096902730082398,"score_spread":0.25734190907460613,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2218675706","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9949801,0.00045700814,0.00036675643,0.000045975663,0.0018271108,0.0004024127,0.00009553693,0.000029326971,0.0017957868],"genre_scores_gemma":[0.9988973,0.000001991947,0.00071497884,0.0001288888,0.000082789535,0.00006716896,0.000009591544,0.000023786868,0.00007351518],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99732554,0.0003241319,0.0011155757,0.0005437067,0.000442524,0.0002485344],"domain_scores_gemma":[0.99794734,0.00045582818,0.0007788914,0.0006699947,0.00006678337,0.00008116011],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00186679,0.00020368591,0.00046657733,0.0001841586,0.0007633975,0.00021002442,0.0010559224,0.000047254063,0.0006628472],"category_scores_gemma":[0.00006586481,0.00016538454,0.00028435397,0.00024039044,0.0002101109,0.0003917564,0.00081450347,0.00016726354,0.0000593633],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.006068187,0.0056218426,0.016560378,0.000022398943,0.00048443832,0.000061429935,0.06089431,0.26963958,0.50391924,0.049218882,0.005833741,0.08167558],"study_design_scores_gemma":[0.006173267,0.00076437707,0.0010986354,0.00003062044,0.00005315472,0.00013703525,0.32980272,0.12753607,0.519959,0.0036206304,0.009894762,0.00092972926],"about_ca_topic_score_codex":0.0002362947,"about_ca_topic_score_gemma":0.0000075928583,"teacher_disagreement_score":0.2689084,"about_ca_system_score_codex":0.001071828,"about_ca_system_score_gemma":0.00010831254,"threshold_uncertainty_score":0.7257712},"labels":[],"label_agreement":null},{"id":"W2219998170","doi":"10.2139/ssrn.2665823","title":"Valuation as a Mechanism of Self-Control","year":2015,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Valuation (finance); Mechanism (biology); Economics; Actuarial science; Business; Accounting; Epistemology; Philosophy","score_opus":0.08644143932972072,"score_gpt":0.37507581624966535,"score_spread":0.28863437691994465,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2219998170","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93932396,0.0003511433,0.05703853,0.00059101055,0.00061497395,0.00010790693,0.0000023786151,0.000024574752,0.0019455402],"genre_scores_gemma":[0.99851173,0.00007589627,0.00054213236,0.00008693839,0.00015776764,0.0000023914924,4.768652e-7,0.000012712967,0.0006099492],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.996411,0.00025630422,0.0008069352,0.0002609072,0.0012799721,0.000984846],"domain_scores_gemma":[0.9978256,0.0003150017,0.0006239036,0.0003494807,0.0007175793,0.0001684276],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.017476475,0.00012713994,0.0003182179,0.00032005712,0.00010785054,0.00016471854,0.00074377,0.00009540532,0.00008419177],"category_scores_gemma":[0.0018944012,0.00009278353,0.00018635095,0.0003399424,0.000027440492,0.0004085698,0.000048742255,0.0007107625,0.0005962393],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001949936,0.00021849455,0.001095579,5.297411e-7,0.00008547076,0.000008975444,0.00072146364,0.0005484375,0.0004294716,0.36810416,0.00055666897,0.6280357],"study_design_scores_gemma":[0.001097753,0.0006374992,0.00006522888,0.000005578072,0.000041641048,0.00047972045,0.0022152162,0.0022028068,0.00015717384,0.991769,0.0012234605,0.000104921506],"about_ca_topic_score_codex":0.00004032055,"about_ca_topic_score_gemma":0.0001049323,"teacher_disagreement_score":0.6279308,"about_ca_system_score_codex":0.0006613232,"about_ca_system_score_gemma":0.0038315898,"threshold_uncertainty_score":0.7663648},"labels":[],"label_agreement":null},{"id":"W2222340070","doi":"","title":"A Principal-Agent Model of Affect and Cognition: How to Explain Cognitive 'Biases and Fallacies' with a Unified Model","year":2009,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Cognitive dissonance; Simplicity; Cognition; Affect (linguistics); Principal (computer security); Cognitive bias; Psychology; Cognitive psychology; Fallacy; Maximization; Confirmation bias; Social psychology; Epistemology; Computer science; Philosophy","score_opus":0.10843900930614865,"score_gpt":0.3586299427851932,"score_spread":0.2501909334790446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2222340070","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90443176,0.00036067073,0.09364256,0.00096293894,0.000020819816,0.00022026549,0.000025180492,0.0000132935465,0.00032252312],"genre_scores_gemma":[0.9973481,0.0003894966,0.0015239419,0.00023797825,0.000030392284,0.0000055228406,0.0000018174289,0.00001250501,0.00045023623],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9975117,0.00009892505,0.00041720062,0.0004352822,0.0006262191,0.0009107035],"domain_scores_gemma":[0.9983277,0.0005719404,0.00030697853,0.00019474374,0.00037085763,0.00022780357],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027261595,0.0002133815,0.00040561313,0.0003371662,0.00022293482,0.0003146929,0.00026196972,0.000075399555,0.0000067307146],"category_scores_gemma":[0.00095331285,0.0001493757,0.000077160876,0.00029211884,0.000106862484,0.00040241532,0.000070417875,0.0005550439,0.000004844842],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021847691,0.00038805808,0.00090759643,0.000004623291,0.00012821614,0.000032519016,0.0026798511,0.027197905,0.0027548461,0.015462827,0.0001846439,0.94807416],"study_design_scores_gemma":[0.0026137626,0.0036039369,0.0009438375,0.00030136114,0.0001699641,0.00096363056,0.009588591,0.15058248,0.00068867777,0.8300071,0.000029378814,0.00050727697],"about_ca_topic_score_codex":0.000004142862,"about_ca_topic_score_gemma":0.00030498137,"teacher_disagreement_score":0.94756687,"about_ca_system_score_codex":0.00014054473,"about_ca_system_score_gemma":0.00087482855,"threshold_uncertainty_score":0.6091364},"labels":[],"label_agreement":null},{"id":"W2224157864","doi":"","title":"A REVIEW OF THE IMPLICATIONS OF PROSPECT THEORY FOR NATURAL HAZARDS AND DISASTER PLANNING","year":2009,"lang":"en","type":"review","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Prospect theory; Normative; Management science; Decision theory; Expected utility hypothesis; Risk analysis (engineering); Robustness (evolution); Economics; Computer science; Political science; Business; Mathematical economics; Microeconomics","score_opus":0.22310779299787054,"score_gpt":0.5046843937783109,"score_spread":0.28157660078044033,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2224157864","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000043836026,0.99615717,0.00033233874,0.00014679614,0.0001827245,0.0012178606,0.00013196106,0.0000074070044,0.0017799257],"genre_scores_gemma":[0.00012796167,0.9972365,0.0012754216,0.00025780007,0.000032836808,0.000055961467,0.000007033241,0.000012812144,0.0009936685],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9975028,0.00017145491,0.0014927656,0.0004173605,0.00027969293,0.00013592721],"domain_scores_gemma":[0.99488795,0.002535269,0.0012709147,0.0010099427,0.0002573345,0.00003860512],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029560202,0.00021328092,0.0015910498,0.0001284695,0.00007913037,0.00006636156,0.0010638722,0.000108907385,0.000065038854],"category_scores_gemma":[0.0022026873,0.0000926147,0.0007755494,0.0004300711,0.00014253882,0.0000925025,0.00019902404,0.00016014311,0.0000061540413],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000022071235,0.000015689295,0.000007658469,0.0029988682,0.0000102506,4.4882185e-8,0.00001928923,7.141142e-8,1.1460431e-7,0.0033593574,0.0049202526,0.9886662],"study_design_scores_gemma":[0.000051311374,0.000034411096,0.000059180486,0.04811406,0.00029226,0.000022306655,0.000024006635,0.0000038199423,5.0157604e-7,0.07357133,0.8777022,0.0001246261],"about_ca_topic_score_codex":0.0000010131516,"about_ca_topic_score_gemma":0.0000019146676,"teacher_disagreement_score":0.98854154,"about_ca_system_score_codex":0.000025602141,"about_ca_system_score_gemma":0.00021105434,"threshold_uncertainty_score":0.37767178},"labels":[],"label_agreement":null},{"id":"W2225428089","doi":"10.3389/fpsyg.2015.01872","title":"Editorial: Improving Bayesian Reasoning: What Works and Why?","year":2015,"lang":"en","type":"editorial","venue":"Frontiers in Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Comisión Nacional de Investigación Científica y Tecnológica","keywords":"Psychology; Bayesian probability; Cognitive science; Cognitive psychology; Artificial intelligence; Computer science","score_opus":0.04095256939231714,"score_gpt":0.3905398267846853,"score_spread":0.3495872573923682,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2225428089","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00029133924,0.009016608,0.012706928,0.00041397108,0.97637355,0.00026618657,0.000037926548,0.00006456473,0.00082890346],"genre_scores_gemma":[0.0000806982,0.0030289968,0.01450445,0.0002545889,0.9816321,0.000034902754,0.00006187861,0.000091926166,0.0003104461],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9929225,0.0005602352,0.0016162351,0.0022224046,0.0018907775,0.0007878656],"domain_scores_gemma":[0.9943529,0.0017365867,0.0010204716,0.0018134394,0.00068066316,0.00039596265],"candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication","research_integrity"],"consensus_categories":["research_integrity"],"category_scores_codex":[0.008275808,0.0005874059,0.0015598363,0.0013574123,0.00013846676,0.0025425376,0.002191587,0.0035787201,0.0000735545],"category_scores_gemma":[0.012445722,0.0005208807,0.00019742677,0.0006075209,0.00043134234,0.0017093889,0.00046797807,0.0023354513,0.000095659205],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001487578,0.000033028387,0.00022385923,0.0000020259713,0.000008261419,0.000020819049,0.00014056264,0.0000018831747,4.3333372e-7,8.972022e-7,0.5379128,0.4615067],"study_design_scores_gemma":[0.0011144289,0.00017049006,0.000011126543,0.00030792409,0.000030114941,0.0000071240684,0.0011077002,0.00017994909,2.0609626e-7,0.1077348,0.88885844,0.00047768393],"about_ca_topic_score_codex":0.000081154016,"about_ca_topic_score_gemma":0.00013226164,"teacher_disagreement_score":0.46102902,"about_ca_system_score_codex":0.00028935348,"about_ca_system_score_gemma":0.0004446697,"threshold_uncertainty_score":0.9999662},"labels":[],"label_agreement":null},{"id":"W2225505438","doi":"","title":"The Effect of Base-Rate Information on the Perception of Risk for Reoffense","year":2006,"lang":"en","type":"article","venue":"American journal of forensic psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Poison control; Human factors and ergonomics; Occupational safety and health; Suicide prevention; Injury prevention; Medical emergency; Base (topology); Environmental health; Forensic engineering; Medicine; Engineering; Mathematics","score_opus":0.03427426429716592,"score_gpt":0.37277514223241554,"score_spread":0.33850087793524963,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2225505438","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99351186,0.000015282592,0.0036879317,0.0013414018,0.00078975764,0.00013221834,0.0000278593,0.0000025736501,0.000491109],"genre_scores_gemma":[0.9987892,0.000028491833,0.00082906923,0.00023861931,0.00009416584,0.0000029803032,0.0000011828448,0.0000052673176,0.000011006144],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99762136,0.00056970597,0.0011893521,0.00011103922,0.00035614485,0.0001523917],"domain_scores_gemma":[0.987759,0.008359754,0.0029660251,0.00044197636,0.00044010294,0.000033168897],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0069667026,0.000106425185,0.0004242245,0.0002261996,0.0001272027,0.000041474115,0.00052755786,0.000040943087,0.000025113693],"category_scores_gemma":[0.0026919579,0.000045405162,0.00030823934,0.00033800947,0.0007033419,0.00016854942,0.000019691042,0.00018051564,0.000022135902],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013042139,0.000020219144,0.0044602556,6.171361e-7,0.000013363449,5.693601e-7,0.00016059096,0.00029667834,0.0003611608,0.00023071178,0.018480616,0.974671],"study_design_scores_gemma":[0.0049445117,0.032936394,0.65357286,0.00015414467,0.00030222247,0.0003433197,0.006896604,0.0019054546,0.004353989,0.24944828,0.044721488,0.00042074264],"about_ca_topic_score_codex":0.000042276268,"about_ca_topic_score_gemma":0.000015379308,"teacher_disagreement_score":0.97425026,"about_ca_system_score_codex":0.000023272514,"about_ca_system_score_gemma":0.000027633418,"threshold_uncertainty_score":0.32227194},"labels":[],"label_agreement":null},{"id":"W2238668872","doi":"","title":"Multiutility representations for incomplete difference preorders","year":2012,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Trent University","funders":"Natural Sciences and Engineering Research Council of Canada; Université de Montréal","keywords":"Preorder; Abelian group; Mathematics; Preference; Interpersonal communication; Space (punctuation); State space; Mathematical economics; Discrete mathematics; Pure mathematics; Social psychology; Computer science; Psychology; Statistics","score_opus":0.3060354782086988,"score_gpt":0.49497234365354625,"score_spread":0.18893686544484745,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2238668872","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9683995,0.000104481864,0.00042888083,0.00058613153,0.001957773,0.0020930553,0.00067720556,0.000067475405,0.0256855],"genre_scores_gemma":[0.98906326,0.00055101427,0.006267207,0.00008133459,0.0003160081,0.0007805741,0.00011022374,0.00007139251,0.0027589796],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99243516,0.00077107304,0.0022430024,0.0023069126,0.0009240453,0.0013198082],"domain_scores_gemma":[0.9840233,0.0104602035,0.00075271283,0.0035781502,0.00071043224,0.00047523092],"candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.011721335,0.00049331255,0.0011493583,0.0011862025,0.00047646914,0.00093722984,0.0032307545,0.00069129444,0.00036658722],"category_scores_gemma":[0.011945294,0.00046243155,0.0005924761,0.0003553556,0.0007168299,0.00032102969,0.0032730177,0.0017817866,0.00011617798],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016319398,0.0003060316,0.03650128,0.000029824008,0.000032180054,0.0000037772754,0.0006188283,0.0042978465,0.0000534127,0.00027955827,0.00033643047,0.9573776],"study_design_scores_gemma":[0.0023067568,0.00021435725,0.25419062,0.00030503355,0.000053103227,0.00001687342,0.0043095406,0.11615819,0.00017763923,0.518726,0.10167419,0.0018676824],"about_ca_topic_score_codex":0.00027978377,"about_ca_topic_score_gemma":0.0011884181,"teacher_disagreement_score":0.95550996,"about_ca_system_score_codex":0.00094668963,"about_ca_system_score_gemma":0.00078721263,"threshold_uncertainty_score":0.99978274},"labels":[],"label_agreement":null},{"id":"W2239841147","doi":"","title":"Revealed Preference and Choice under Uncertainty","year":2011,"lang":"en","type":"article","venue":"RePEc: Research Papers in Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Rationalizability; Transitive relation; Dominance (genetics); Preference; Mathematical economics; Property (philosophy); Class (philosophy); Stochastic dominance; Revealed preference; Economics; Preference theory; Mathematics; Observable; Social choice theory; Econometrics; Mathematical optimization; Computer science; Microeconomics; Artificial intelligence; Combinatorics; Nash equilibrium","score_opus":0.3322906550061952,"score_gpt":0.4313822186688504,"score_spread":0.0990915636626552,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2239841147","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9046762,0.000038660226,0.000009708051,0.00013850007,0.00021380674,0.00023195936,0.000014343951,0.00002350056,0.09465332],"genre_scores_gemma":[0.99504626,0.00060673704,0.0010343865,0.00014771649,0.00005928811,0.000032630152,0.000002147063,0.000022203696,0.0030486095],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9967195,0.00033113122,0.0008657275,0.00100228,0.0004455678,0.0006357977],"domain_scores_gemma":[0.99541193,0.0027835402,0.00018956188,0.0011135412,0.00021114564,0.00029030553],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005363069,0.0001946895,0.00042546715,0.000564793,0.00022091565,0.0002880828,0.0010986929,0.00019262017,0.00070078525],"category_scores_gemma":[0.0026838707,0.00016310043,0.000090608206,0.00035439854,0.00046322113,0.00039796,0.00053900824,0.00054602465,0.0001534301],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008565697,0.00010227214,0.045253783,0.0000028293757,0.000008422068,0.000013434999,0.0004697123,0.0004000939,0.00007043767,0.0006106534,0.00015421642,0.95282847],"study_design_scores_gemma":[0.0019592524,0.00053179107,0.58803326,0.00012832612,0.000012882209,0.000058098474,0.0064131785,0.0139259705,0.00015323155,0.31022364,0.07757754,0.0009828345],"about_ca_topic_score_codex":0.00027706352,"about_ca_topic_score_gemma":0.001415539,"teacher_disagreement_score":0.95184565,"about_ca_system_score_codex":0.00026155423,"about_ca_system_score_gemma":0.00021431799,"threshold_uncertainty_score":0.7673107},"labels":[],"label_agreement":null},{"id":"W2243759935","doi":"10.1016/j.econmod.2012.10.006","title":"Utilitarianism and unequal longevities: A remedy?","year":2012,"lang":"en","type":"article","venue":"Economic Modelling","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":35,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Utilitarianism; Counterintuitive; Economics; Redistribution (election); Microeconomics; Welfare; Planner; Consumption (sociology); Robustness (evolution); Mathematical economics; Computer science; Sociology; Political science; Law; Artificial intelligence","score_opus":0.31936491768061054,"score_gpt":0.405982293900649,"score_spread":0.08661737622003846,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2243759935","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9421264,0.0005498531,0.04897605,0.0001665003,0.0012567509,0.00009711033,0.000020337258,0.000039195205,0.0067678248],"genre_scores_gemma":[0.9916939,0.00005775152,0.0068503167,0.00013647616,0.00035501862,0.000006325533,0.000002272273,0.000020121179,0.0008778014],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99802804,0.00006944034,0.00079385284,0.0004912329,0.00019175191,0.00042569204],"domain_scores_gemma":[0.99811,0.0008088279,0.00021245393,0.00058086857,0.000032650518,0.00025520052],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0031716232,0.0001783755,0.00036618597,0.00020047314,0.00018769105,0.00030619843,0.00040460264,0.00011529899,0.00081497995],"category_scores_gemma":[0.0001225707,0.00015618658,0.00011011075,0.00006200068,0.000095510826,0.000954435,0.00016986298,0.00015038796,0.001751784],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008544137,0.00012680794,0.019901128,0.0000070693827,0.00003726475,0.000006530217,0.0070262286,0.20161246,0.000039747873,0.03917156,0.005020527,0.72696525],"study_design_scores_gemma":[0.00035963993,0.00004216279,0.00038738342,0.000019495832,0.000020690715,0.000023983608,0.0017329315,0.7292144,0.00007160259,0.1964887,0.07121273,0.00042633078],"about_ca_topic_score_codex":0.000118126,"about_ca_topic_score_gemma":0.000027485286,"teacher_disagreement_score":0.7265389,"about_ca_system_score_codex":0.000108070795,"about_ca_system_score_gemma":0.000053497108,"threshold_uncertainty_score":0.99902546},"labels":[],"label_agreement":null},{"id":"W2249072996","doi":"","title":"Data Dispersion in Economics(II) - Inevitability and Consequences of Restrictions","year":2012,"lang":"en","type":"article","venue":"Review of Economics and Finance","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Economics; Zero (linguistics); Dispersion (optics); Mathematical economics; Prospect theory; Risk aversion (psychology); Equity premium puzzle; Econometrics; Loss aversion; Expected utility hypothesis; Equity (law); Microeconomics; Physics; Risk premium; Philosophy; Quantum mechanics","score_opus":0.2030694654889453,"score_gpt":0.39670275949052375,"score_spread":0.19363329400157844,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2249072996","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9421446,0.056129944,0.000007904272,0.00067796,0.00017088713,0.0001554482,0.00029086595,0.0000016023733,0.0004208164],"genre_scores_gemma":[0.61711454,0.38196325,0.0008285093,0.000057248624,0.000013262668,0.0000024602396,0.0000054283964,0.0000029159298,0.000012399906],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.998238,0.000054420656,0.0011273702,0.00039051354,0.00004165066,0.00014800715],"domain_scores_gemma":[0.9979233,0.0005140327,0.0006249177,0.00083772535,0.000049542858,0.000050484523],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031153844,0.00010883518,0.0006183368,0.00011122441,0.00005962055,0.000024075734,0.0004606475,0.0000557738,0.000022926439],"category_scores_gemma":[0.00078775256,0.00008995657,0.000053821826,0.00014893519,0.00030184895,0.00071709836,0.00045230397,0.00007468643,0.000004730566],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015166179,0.00013279715,0.09056065,0.00016210195,0.0000053801223,2.0771796e-7,0.00007608827,0.000043799773,0.000014634548,0.017269375,0.0004372031,0.8912826],"study_design_scores_gemma":[0.00073639816,0.00023358183,0.21108055,0.0027169585,0.000072954346,0.000049229453,0.00030677527,0.00499547,0.00016179265,0.102567784,0.67647535,0.0006031851],"about_ca_topic_score_codex":0.0000875891,"about_ca_topic_score_gemma":0.00009902303,"teacher_disagreement_score":0.8906794,"about_ca_system_score_codex":0.00002600406,"about_ca_system_score_gemma":0.000072037896,"threshold_uncertainty_score":0.36683226},"labels":[],"label_agreement":null},{"id":"W2255306320","doi":"","title":"The Prevalence of Meta-Cognitive Routes to Judgment","year":2004,"lang":"en","type":"article","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Processing fluency; Fluency; Psychology; Cognition; Cognitive psychology; Information processing; Cognitive bias; Persuasion; Social psychology","score_opus":0.2619273423306071,"score_gpt":0.4342654462087001,"score_spread":0.172338103878093,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2255306320","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98443156,0.00019471874,0.0046612876,0.0021166247,0.00026360113,0.00021651738,0.000029109251,0.00001804623,0.008068522],"genre_scores_gemma":[0.9919063,0.000021496777,0.0021790473,0.00043741573,0.000016763861,0.000019745446,1.386665e-7,0.0000046741397,0.00541445],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9981448,0.000052664353,0.0005900487,0.00034474197,0.00069497,0.0001727901],"domain_scores_gemma":[0.9970683,0.0018503943,0.00016924582,0.0004952954,0.0003253383,0.00009143634],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0022240852,0.000101912454,0.00025007164,0.00009316214,0.00014013564,0.00019032611,0.0008092377,0.00003086416,0.00073248113],"category_scores_gemma":[0.002162681,0.000046718884,0.00021151577,0.0003447498,0.00009399334,0.00016694715,0.00019751684,0.0000575464,0.001007383],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009596886,0.00022547088,0.0026293208,0.0000043522023,0.00014618183,0.0000057488787,0.0009895843,0.0015061605,0.00033668464,0.010501176,0.0030957658,0.98046356],"study_design_scores_gemma":[0.0011003683,0.00094034843,0.04477492,0.00009004535,0.0009691723,0.000018041195,0.0048273383,0.00011269744,0.052218456,0.8557119,0.03861794,0.0006187945],"about_ca_topic_score_codex":0.000056817727,"about_ca_topic_score_gemma":0.00009392913,"teacher_disagreement_score":0.9798448,"about_ca_system_score_codex":0.000029247263,"about_ca_system_score_gemma":0.00006143899,"threshold_uncertainty_score":0.99977046},"labels":[],"label_agreement":null},{"id":"W2259056550","doi":"10.22004/ag.econ.205763","title":"Was Sandmo Right? Experimental Evidence on Attitudes to Price Risk and Uncertainty","year":2015,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of Guelph; University of Georgia; University of Minnesota","keywords":"Ambiguity; Economics; Certainty; Contradiction; Price level; Risk aversion (psychology); Hedge; Factor price; Mid price; Price risk; Econometrics; Ambiguity aversion; Distribution (mathematics); Microeconomics; Expected utility hypothesis; Mathematical economics; Financial economics; Monetary economics; Mathematics; Computer science; Futures contract","score_opus":0.22915696164699925,"score_gpt":0.4835074613162342,"score_spread":0.25435049966923495,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2259056550","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97336173,0.0004789933,0.000007692778,0.00039713693,0.0010190955,0.0009777672,0.0001374713,0.000044059816,0.02357603],"genre_scores_gemma":[0.99414957,0.0023711943,0.0011948504,0.0001779667,0.0002660791,0.0001926682,0.000008975815,0.000056665158,0.0015820154],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99258775,0.00091023144,0.0015365356,0.0026452143,0.0013551252,0.00096513506],"domain_scores_gemma":[0.9893693,0.006227215,0.0005085401,0.0025944563,0.0004698859,0.0008306122],"candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0147278495,0.0005423591,0.0011025051,0.0012950659,0.00037513592,0.0014757876,0.0026273113,0.0005505944,0.00038207613],"category_scores_gemma":[0.0098437555,0.00045438827,0.0002442167,0.00036805225,0.00051421445,0.00036455414,0.0040953103,0.0019645342,0.0003928136],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000811637,0.00045586043,0.020308807,0.000019458997,0.000041169085,0.0000765253,0.0016415021,0.04155328,0.00013831671,0.00015245983,0.002618875,0.93218213],"study_design_scores_gemma":[0.0070503815,0.007901248,0.11851312,0.00766101,0.00011876067,0.00019141697,0.023269786,0.061787367,0.004506859,0.24680082,0.51295996,0.009239291],"about_ca_topic_score_codex":0.00045476508,"about_ca_topic_score_gemma":0.0007499723,"teacher_disagreement_score":0.9229428,"about_ca_system_score_codex":0.0021202515,"about_ca_system_score_gemma":0.00089732936,"threshold_uncertainty_score":0.9997908},"labels":[],"label_agreement":null},{"id":"W2261535159","doi":"","title":"Chapter 20: Human Psychology and Market Seasonality","year":2014,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Mood; Financial market; Stock market; Phenomenon; Affect (linguistics); Economics; Stock (firearms); Financial economics; Efficient-market hypothesis; Behavioral economics; Psychology; Positive economics; Social psychology; Microeconomics; Finance; Geography; Epistemology","score_opus":0.06929669184290022,"score_gpt":0.40479366739964456,"score_spread":0.33549697555674435,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2261535159","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97401917,0.00047578287,0.0041839457,0.002091795,0.0003346387,0.000047223082,0.0000028766399,0.00001757659,0.018826975],"genre_scores_gemma":[0.9957875,0.00030778817,0.0001439291,0.0005362433,0.00024696,0.0000011499632,5.916962e-7,0.000013117328,0.0029627187],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99706936,0.00024242216,0.0005654513,0.00043387446,0.0004757116,0.0012131605],"domain_scores_gemma":[0.9986553,0.00032049767,0.00030417074,0.00041979755,0.00013945311,0.0001607686],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012254843,0.00015114972,0.00029168001,0.00014045028,0.0003588604,0.00028129906,0.00063841295,0.000102269514,0.0008759405],"category_scores_gemma":[0.00046319724,0.00011084695,0.00012937997,0.00012741503,0.0001338135,0.0002478252,0.00009784261,0.0010638582,0.00020300885],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004238363,0.00003828002,0.018980902,2.945182e-7,0.000015462474,0.000002316856,0.000027256823,0.0000019188751,0.00016809462,0.066626765,0.0017554149,0.9123409],"study_design_scores_gemma":[0.0004175504,0.00024618415,0.017525034,0.000004804099,0.000011220386,0.00054726674,0.00011192104,0.00013785383,0.0000042596184,0.9131026,0.067757346,0.0001339215],"about_ca_topic_score_codex":0.000010968097,"about_ca_topic_score_gemma":0.00048148402,"teacher_disagreement_score":0.912207,"about_ca_system_score_codex":0.00012525835,"about_ca_system_score_gemma":0.00016204614,"threshold_uncertainty_score":0.95909345},"labels":[],"label_agreement":null},{"id":"W2265410261","doi":"","title":"Integration-segregation decisions under general value functions: \"Create your own bundle -- choose 1, 2, or all 3 !\"","year":2012,"lang":"en","type":"article","venue":"QUT ePrints (Queensland University of Technology)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Agencia Nacional de Investigación e Innovación","keywords":"Portfolio; Product (mathematics); Value (mathematics); Sign (mathematics); Capital (architecture); Cover (algebra); Microeconomics; Economics; Business; Computer science; Mathematics; Financial economics; Engineering","score_opus":0.1368852723062701,"score_gpt":0.35444948985129654,"score_spread":0.21756421754502644,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2265410261","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9641385,0.00005633242,0.030378468,0.0016963442,0.000526433,0.00020866728,0.000051762654,0.00016452404,0.0027789867],"genre_scores_gemma":[0.97217274,0.00010208268,0.019094119,0.00008083099,0.000047423793,0.0000012407526,0.000018084293,0.000014288275,0.00846919],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9979189,0.000098552046,0.00053079525,0.0005591671,0.0004978994,0.00039465615],"domain_scores_gemma":[0.9974943,0.00045034662,0.0004373147,0.0010402316,0.00039474617,0.00018306097],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001114234,0.0002278569,0.00043160777,0.001125706,0.00037067328,0.00007467745,0.0010341975,0.0004238446,0.0013940341],"category_scores_gemma":[0.0012635501,0.00017906776,0.00020248086,0.00102413,0.00032459685,0.0006821181,0.00045114342,0.00034696807,0.0014044428],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047774072,0.0008206763,0.07544589,0.0000023352836,0.000108288885,0.000020065962,0.0005747652,0.00074400636,0.001464984,0.017982146,0.012598943,0.88976014],"study_design_scores_gemma":[0.0030810942,0.0004580175,0.35990983,0.00016128186,0.00031819625,0.0001526404,0.014366352,0.0033070594,0.0030978231,0.27056938,0.34351197,0.0010663398],"about_ca_topic_score_codex":0.00032559576,"about_ca_topic_score_gemma":0.0002882044,"teacher_disagreement_score":0.8886938,"about_ca_system_score_codex":0.00017654996,"about_ca_system_score_gemma":0.00011807223,"threshold_uncertainty_score":0.9995188},"labels":[],"label_agreement":null},{"id":"W2271262700","doi":"10.1371/journal.pone.0168045","title":"Quantum Decision Theory in Simple Risky Choices","year":2016,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Cogito Foundation; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Mathematical economics; Quarter (Canadian coin); Formalism (music); Quantum probability; Decision theory; Quantum; Computer science; Mathematics; Quantum mechanics; Physics; Quantum process; Quantum dynamics; Statistics","score_opus":0.19610481715450573,"score_gpt":0.3746953224475208,"score_spread":0.17859050529301507,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2271262700","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99499005,0.00011293129,0.0020731639,0.00036261647,0.0001791804,0.0001536368,0.000032538115,0.000054070184,0.0020418088],"genre_scores_gemma":[0.99638516,0.00007152547,0.0020393946,0.00016030468,0.00009763597,0.000013984134,0.000001014834,0.000019101037,0.0012119064],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99679554,0.00020493993,0.00087239355,0.00065325183,0.0011197956,0.00035406603],"domain_scores_gemma":[0.9913288,0.0071210386,0.00026254536,0.00096076727,0.00018250832,0.0001443905],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0039831083,0.0001680319,0.00045427855,0.00045375913,0.00010469834,0.00021549239,0.0010504668,0.00012652202,0.002410597],"category_scores_gemma":[0.0079903845,0.000095197276,0.00010977002,0.0005064956,0.00010966755,0.00057498255,0.00025716214,0.00013316699,0.0050270995],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019165038,0.0009905228,0.084611826,0.0000015861332,0.0000135679875,0.000017754484,0.00010909571,0.000009393034,0.0044452064,0.002057466,0.0013211924,0.90623075],"study_design_scores_gemma":[0.0007694662,0.00012407127,0.043042645,0.00021019719,0.000019872781,0.0000017265169,0.00014871593,0.0005266583,0.002931135,0.9465606,0.0054142904,0.0002505995],"about_ca_topic_score_codex":0.000033292945,"about_ca_topic_score_gemma":0.00019167356,"teacher_disagreement_score":0.9445031,"about_ca_system_score_codex":0.000081829225,"about_ca_system_score_gemma":0.00005258879,"threshold_uncertainty_score":0.99850136},"labels":[],"label_agreement":null},{"id":"W2274268699","doi":"10.1177/1474704915596295","title":"Inequality and Risk-Taking","year":2015,"lang":"en","type":"article","venue":"Evolutionary Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":64,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa; University of Guelph; University of Regina","funders":"Social Sciences and Humanities Research Council of Canada; Ontario Problem Gambling Research Centre","keywords":"Inequality; Economic inequality; Social inequality; Economics; Demographic economics; Psychology; Mathematics","score_opus":0.37242365136744127,"score_gpt":0.5002848410627674,"score_spread":0.12786118969532612,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2274268699","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97748536,0.0005507153,0.0036980477,0.0011832312,0.0015692709,0.00006999999,0.000028594994,0.000053630836,0.015361138],"genre_scores_gemma":[0.9941461,0.000038022434,0.0047255317,0.0005243438,0.00016708944,0.000005693984,0.000004166508,0.000008329322,0.0003807129],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99775183,0.00040890984,0.00057856407,0.00060287875,0.0004273433,0.00023045806],"domain_scores_gemma":[0.99759936,0.0006408491,0.00064772,0.0006456553,0.00025881839,0.00020756839],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003474987,0.000120048455,0.0002512564,0.0002301082,0.00014820226,0.00007094751,0.00044333455,0.00014031355,0.00037007657],"category_scores_gemma":[0.0057661827,0.00009565333,0.00005435652,0.000384825,0.00021947194,0.00027036056,0.00017294986,0.00020844472,0.001312552],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006749066,0.00007944188,0.5949366,2.4719495e-7,0.000005921642,0.000011442818,0.00018348216,0.00006179949,0.000012031741,0.001015857,0.0805736,0.3230521],"study_design_scores_gemma":[0.0003976452,0.00009795585,0.5685753,0.000002341244,0.000006329169,0.000099441706,0.000174936,0.0005929945,7.965633e-7,0.33040738,0.099537134,0.00010770884],"about_ca_topic_score_codex":0.000071716815,"about_ca_topic_score_gemma":0.000034639237,"teacher_disagreement_score":0.32939154,"about_ca_system_score_codex":0.00004950245,"about_ca_system_score_gemma":0.000065974746,"threshold_uncertainty_score":0.99946505},"labels":[],"label_agreement":null},{"id":"W2274516545","doi":"10.1016/j.neuroscience.2016.02.028","title":"Inactivation of the orbitofrontal cortex reduces irrational choice on a rodent Betting Task","year":2016,"lang":"en","type":"article","venue":"Neuroscience","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":21,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Canadian Institutes of Health Research","keywords":"Orbitofrontal cortex; Infralimbic cortex; Psychology; Task (project management); Iowa gambling task; Preference; Cognitive psychology; Neuroscience; Impulsivity; Odds; Addiction; Prefrontal cortex; Cognition; Developmental psychology; Medicine; Economics; Microeconomics","score_opus":0.12855788192761716,"score_gpt":0.3871258353234358,"score_spread":0.2585679533958186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2274516545","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9949769,0.0000029535368,0.00043738034,0.0015682707,0.0017435945,0.00010276629,0.000018543298,0.000014129721,0.0011354901],"genre_scores_gemma":[0.99869996,0.0000016443688,0.00008887406,0.0004752049,0.000071298084,0.0000044315866,1.4887414e-7,0.0000049341093,0.0006535032],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9975194,0.00010214091,0.00046515226,0.00051598385,0.0012261927,0.0001711796],"domain_scores_gemma":[0.99773675,0.001128737,0.00043751815,0.00049614377,0.00014525045,0.000055573928],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00093503733,0.000096081974,0.00013516165,0.0001204506,0.00026740046,0.00014682747,0.0010679591,0.00003760084,0.00004580833],"category_scores_gemma":[0.0050230306,0.00004585287,0.000081780854,0.000552682,0.00028165965,0.0005272005,0.00017957109,0.00008824842,0.00005786308],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015830492,0.00008037278,0.024164226,2.9672228e-7,3.1738435e-7,8.89844e-7,0.00006571824,0.00011786813,0.66011566,0.00041860846,0.0010525417,0.3139677],"study_design_scores_gemma":[0.00021298818,0.00016449596,0.92319196,0.00005433755,0.000003170061,0.000010419297,0.000058144127,0.0008584886,0.055109598,0.007903271,0.012307598,0.00012552385],"about_ca_topic_score_codex":0.000020678533,"about_ca_topic_score_gemma":0.000020242514,"teacher_disagreement_score":0.89902776,"about_ca_system_score_codex":0.000064321015,"about_ca_system_score_gemma":0.000116270785,"threshold_uncertainty_score":0.60134},"labels":[],"label_agreement":null},{"id":"W2278093153","doi":"","title":"Local Utility and Risk Aversion","year":2012,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Risk aversion (psychology); Economics; Risk analysis (engineering); Psychology; Business; Expected utility hypothesis; Financial economics","score_opus":0.0589741161451992,"score_gpt":0.3114001571649144,"score_spread":0.2524260410197152,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2278093153","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.77794284,0.00095376,0.19693276,0.0017489592,0.0006171488,0.00027297388,0.0001620077,0.00012414042,0.021245409],"genre_scores_gemma":[0.9766182,0.00070955686,0.0191785,0.000051904077,0.000029009068,0.000015443266,0.00008450814,0.000031213574,0.0032816932],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98940444,0.006785026,0.0010491232,0.001319436,0.0010023032,0.0004396883],"domain_scores_gemma":[0.98676497,0.0059744236,0.0011097997,0.003552665,0.002178527,0.00041960983],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.026197974,0.00038681342,0.00061318814,0.0003214816,0.0005690128,0.0010589439,0.0020337556,0.0005015809,0.00084441266],"category_scores_gemma":[0.0072843404,0.0003427924,0.00031138762,0.0003880748,0.00060464494,0.00032601468,0.0038588273,0.0010037544,0.00048123542],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018902101,0.00030501105,0.03024339,0.000013783742,0.000022209428,0.000002616151,0.0028532436,0.00003682924,0.000033999633,0.0031634672,0.002756351,0.9605502],"study_design_scores_gemma":[0.0016097868,0.0000016101413,0.17653024,0.0017554538,0.0003445661,0.00005614726,0.0017357863,0.08823432,0.009359814,0.47514632,0.24313836,0.0020875912],"about_ca_topic_score_codex":0.00169018,"about_ca_topic_score_gemma":0.0013995876,"teacher_disagreement_score":0.9584626,"about_ca_system_score_codex":0.00012417162,"about_ca_system_score_gemma":0.00021813832,"threshold_uncertainty_score":0.99997807},"labels":[],"label_agreement":null},{"id":"W2288204951","doi":"10.2139/ssrn.2504745","title":"Prince: An Improved Method for Measuring Incentivized Preferences","year":2014,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":31,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Center for Interuniversity Research and Analysis on Organizations","funders":"Economic and Social Research Council","keywords":"Economics; Econometrics; Psychology; Computer science","score_opus":0.10972215738432402,"score_gpt":0.40860822774715916,"score_spread":0.29888607036283515,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2288204951","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.55091524,0.00011574901,0.44769993,0.00018577889,0.00047904134,0.00015704568,0.0000029907067,0.000030163326,0.00041406453],"genre_scores_gemma":[0.9767117,0.00009824295,0.021836475,0.00008714327,0.00040420052,0.000016182968,0.0000018328915,0.00002543313,0.00081876985],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9954408,0.0005042687,0.0009097428,0.00060442474,0.00070271635,0.0018380511],"domain_scores_gemma":[0.996958,0.0011707315,0.00064436864,0.0005444825,0.0004815436,0.00020087864],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.027051274,0.00021887041,0.00046410854,0.00028766264,0.0004915001,0.00072613306,0.0014541462,0.00012796068,0.00005646716],"category_scores_gemma":[0.0021376507,0.00015433745,0.0002690872,0.00027800637,0.00005023378,0.0007879421,0.00010672137,0.0010179467,0.000050056897],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013556615,0.000067848756,0.0009818644,9.249457e-7,0.000022538197,1.976885e-7,0.00010004889,0.000061760154,0.0013563616,0.0056820684,0.000035270547,0.9915556],"study_design_scores_gemma":[0.0010002506,0.00065542303,0.00034759278,0.0000130006365,0.000031376636,0.000083217084,0.0009713539,0.01882282,0.0005028985,0.9678301,0.009504532,0.00023741006],"about_ca_topic_score_codex":0.000041152125,"about_ca_topic_score_gemma":0.0012658611,"teacher_disagreement_score":0.99131817,"about_ca_system_score_codex":0.0004358251,"about_ca_system_score_gemma":0.0012749187,"threshold_uncertainty_score":0.9375486},"labels":[],"label_agreement":null},{"id":"W2291239260","doi":"10.2139/ssrn.2725953","title":"A Neuroeconomic Theory of Attention- and Task-Switching with Implications for Autism and ADHD","year":2016,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Autism; Psychology; Cognitive psychology; Neuroeconomics; Task (project management); Developmental psychology; Economics","score_opus":0.051546478713512436,"score_gpt":0.3434037642049364,"score_spread":0.291857285491424,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2291239260","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9081694,0.00034509794,0.088224195,0.003001837,0.00007257206,0.00010782925,0.000014236297,0.0000072076405,0.000057656147],"genre_scores_gemma":[0.99866205,0.00042889448,0.00040879459,0.000042105854,0.00004390913,0.0000064718156,2.8182626e-7,0.000012360908,0.0003951385],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9985026,0.000065852284,0.00045122352,0.00028988742,0.00010982114,0.0005805995],"domain_scores_gemma":[0.9981995,0.0010033455,0.0003946179,0.00023206408,0.00009044441,0.00008001693],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032870574,0.00010177831,0.00021485274,0.00018275341,0.00021432451,0.00012903835,0.0002731661,0.000039875944,0.000012348216],"category_scores_gemma":[0.0002796069,0.000056597528,0.00006920891,0.000079880076,0.00009258918,0.00035989162,0.000050589417,0.00022307552,0.0000062101417],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000080648766,0.000017966886,0.009700921,7.1462955e-7,0.00002271538,2.031818e-7,0.00006122751,0.0000019041513,0.0026277287,0.12447306,0.00003778349,0.8629751],"study_design_scores_gemma":[0.00069773174,0.0003217883,0.029388888,0.000021351716,0.000028949307,0.0004645799,0.0004941331,0.00003188501,0.00001521018,0.9677338,0.0007133413,0.000088335946],"about_ca_topic_score_codex":0.000005339558,"about_ca_topic_score_gemma":0.00011180223,"teacher_disagreement_score":0.8628868,"about_ca_system_score_codex":0.000101643134,"about_ca_system_score_gemma":0.0004416403,"threshold_uncertainty_score":0.23079802},"labels":[],"label_agreement":null},{"id":"W2295338520","doi":"10.3389/fpsyg.2016.00009","title":"Commentary: Cognitive reflection vs. calculation in decision making","year":2016,"lang":"en","type":"article","venue":"Frontiers in Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":93,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Psychology; Cognition; Reflection (computer programming); Cognitive psychology; Cognitive science; Volume (thermodynamics); Neuroscience; Computer science; Physics","score_opus":0.09309772626100003,"score_gpt":0.45680279035260846,"score_spread":0.3637050640916084,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2295338520","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7205442,0.00008288543,0.2702887,0.0029234237,0.0043702736,0.00017708506,0.0000115298535,0.000021381316,0.001580496],"genre_scores_gemma":[0.9820949,0.000056552537,0.01459138,0.0030930093,0.00007636579,0.000018791232,0.00000315728,0.000015078864,0.00005077105],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9972494,0.00034135213,0.0009206658,0.0007721552,0.00037702767,0.00033936294],"domain_scores_gemma":[0.99804336,0.0010969442,0.00026412637,0.00044545223,0.00009393748,0.000056190933],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023667687,0.00015853599,0.00039129786,0.0012973866,0.00006966067,0.000062976804,0.00045848705,0.00023174372,0.00022165092],"category_scores_gemma":[0.0012997242,0.00011267782,0.00008457925,0.00088343787,0.00014404736,0.00040850462,0.00009138185,0.00019551079,0.00022596367],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004735236,0.00006389892,0.3209398,1.806437e-7,0.000002155037,0.000016194654,0.0000922061,0.000007174206,0.000037497342,0.000010769935,0.057621606,0.620735],"study_design_scores_gemma":[0.0027322927,0.0002026889,0.45589444,0.00023382805,0.0000072818416,0.000023242234,0.00034552912,0.0006731452,0.000027392205,0.5094231,0.030180015,0.0002571025],"about_ca_topic_score_codex":0.000021644544,"about_ca_topic_score_gemma":0.00029942818,"teacher_disagreement_score":0.62047786,"about_ca_system_score_codex":0.0002500559,"about_ca_system_score_gemma":0.000020020709,"threshold_uncertainty_score":0.4594868},"labels":[],"label_agreement":null},{"id":"W2299773574","doi":"10.3390/risks4010008","title":"Optimal Insurance for a Minimal Expected Retention: The Case of an Ambiguity-Seeking Insurer","year":2016,"lang":"en","type":"article","venue":"Risks","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Georgia State University","keywords":"Expected utility hypothesis; Deductible; Ambiguity; Constraint (computer-aided design); Indemnity; Actuarial science; Distortion (music); Schedule; Equivalence (formal languages); Insurance policy; Mathematics; Arrow; Economics; Mathematical economics; Computer science; Discrete mathematics","score_opus":0.2717739886010315,"score_gpt":0.44497642256905096,"score_spread":0.17320243396801943,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2299773574","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99126756,0.000053978136,0.0072815716,0.00029114587,0.00046484603,0.00022100346,0.00016989728,0.000029999705,0.00021998354],"genre_scores_gemma":[0.9950033,0.000004762157,0.004519112,0.00004406018,0.00012880276,0.000028188284,0.0000013635871,0.000013919032,0.00025652372],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9980937,0.00016286469,0.0007184558,0.00046150672,0.00033181236,0.00023166352],"domain_scores_gemma":[0.9967897,0.0014627795,0.00043071294,0.0008343017,0.00039744086,0.00008507183],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023291882,0.00013139832,0.00028524984,0.00013330577,0.0002442765,0.00015785251,0.0006683897,0.00008436561,0.00016125473],"category_scores_gemma":[0.0018753293,0.00006527018,0.00019659051,0.00029932577,0.00017988245,0.00041305993,0.00011243121,0.000083147155,0.00005403582],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027505792,0.00012529649,0.00984634,0.0000020396974,0.000011743604,0.00010588436,0.00061184145,0.00008456455,0.0027258932,0.00024842788,0.0014268486,0.98453605],"study_design_scores_gemma":[0.0117759295,0.0035472931,0.6989269,0.00050184067,0.0002433216,0.004905343,0.013527962,0.026194569,0.018195288,0.15710957,0.06274009,0.0023318916],"about_ca_topic_score_codex":0.00013245946,"about_ca_topic_score_gemma":0.00021173777,"teacher_disagreement_score":0.9822042,"about_ca_system_score_codex":0.000030284767,"about_ca_system_score_gemma":0.0000528699,"threshold_uncertainty_score":0.26616406},"labels":[],"label_agreement":null},{"id":"W2308591296","doi":"10.5465/ambpp.2015.11521abstract","title":"How Incidental Confidence Influences Self-Interested Behaviors? A Double-Edged Sword","year":2015,"lang":"en","type":"article","venue":"Academy of Management Proceedings","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Self-confidence; Prosocial behavior; Psychology; Dictator game; Affect (linguistics); Social psychology; SWORD; Dictator; Outcome (game theory); Mechanism (biology); Economics; Computer science; Microeconomics; Political science; Communication","score_opus":0.20082159718368908,"score_gpt":0.40763385010852415,"score_spread":0.20681225292483507,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2308591296","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9900678,0.000118369986,0.00007319668,0.0022890442,0.00033458034,0.00057195796,0.0000052562154,0.0001736479,0.0063661556],"genre_scores_gemma":[0.9945386,0.000048631886,0.0026480048,0.0003961735,0.00008840418,0.00004895524,0.0000013351492,0.00002422216,0.0022056792],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99529904,0.000028937562,0.0011644976,0.000960817,0.0020685978,0.00047813004],"domain_scores_gemma":[0.99778914,0.0001635831,0.0010203458,0.00025304902,0.00043579066,0.00033808794],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0035390663,0.00033880258,0.00058321084,0.0007617214,0.000141443,0.0011256329,0.002569028,0.00022945109,0.00006410775],"category_scores_gemma":[0.00040290586,0.0002785139,0.00018774273,0.0011104872,0.00025838753,0.0026000412,0.0010428313,0.00037772467,0.0002570074],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013217072,0.0010256602,0.25015873,0.00014855785,0.00027970763,0.00006814317,0.007241826,0.00004369544,0.002502303,0.056600925,0.12980099,0.5508078],"study_design_scores_gemma":[0.011995653,0.0013320267,0.19420905,0.0009804462,0.00092964026,0.0002024184,0.06610134,0.001111655,0.022364518,0.32449475,0.373373,0.0029054799],"about_ca_topic_score_codex":0.000027501206,"about_ca_topic_score_gemma":0.0000039526053,"teacher_disagreement_score":0.5479023,"about_ca_system_score_codex":0.00013851635,"about_ca_system_score_gemma":0.000036141344,"threshold_uncertainty_score":0.9999667},"labels":[],"label_agreement":null},{"id":"W2313739240","doi":"10.1080/00207543.2015.1131865","title":"Cournot game with incomplete information based on rank-dependent utility theory under a fuzzy environment","year":2016,"lang":"en","type":"article","venue":"International Journal of Production Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"National Natural Science Foundation of China","keywords":"Cournot competition; Complete information; Mathematical economics; Rank (graph theory); Preference; Game theory; Mathematics; Economics; Ranking (information retrieval); Mathematical optimization; Computer science; Microeconomics; Artificial intelligence","score_opus":0.23536853597053176,"score_gpt":0.4535527530241436,"score_spread":0.21818421705361185,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2313739240","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8609617,0.000017673783,0.10873411,0.026278222,0.0018000836,0.00025646508,0.00004308356,0.000012440158,0.0018962327],"genre_scores_gemma":[0.9978971,0.000027584721,0.0008891703,0.00018931547,0.0003655311,0.000006417118,0.0000020091527,0.000008167726,0.0006147419],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9928085,0.00065763004,0.00096713164,0.00029668352,0.005048836,0.00022118093],"domain_scores_gemma":[0.994675,0.0015747078,0.0006353813,0.00047408434,0.0025026305,0.00013823398],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.015992705,0.00012082627,0.00020412277,0.0012337884,0.00012087481,0.00037015774,0.0010738884,0.00006170456,0.001772004],"category_scores_gemma":[0.0035727078,0.000063586915,0.00011402898,0.00023242667,0.00028815938,0.0012499385,0.00010105939,0.00039235904,0.0007398481],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0050530625,0.00037606453,0.0039066565,0.000001878361,0.000066511246,0.0000331984,0.00020470963,0.012527131,0.002715863,0.0020010832,0.0042054164,0.9689084],"study_design_scores_gemma":[0.0060417987,0.0023238305,0.05635714,0.0004974477,0.00003160276,0.00046592747,0.0022995092,0.0021422165,0.012448857,0.74617195,0.17071313,0.00050656527],"about_ca_topic_score_codex":0.000007939454,"about_ca_topic_score_gemma":0.0000045598235,"teacher_disagreement_score":0.96840185,"about_ca_system_score_codex":0.00051546306,"about_ca_system_score_gemma":0.00029746417,"threshold_uncertainty_score":0.9991405},"labels":[],"label_agreement":null},{"id":"W2322436276","doi":"10.1037/a0023586","title":"\"Hindsight bias from 3 to 95 years of age\": Correction to Bernstein et al. (2011).","year":2011,"lang":"en","type":"article","venue":"Journal of Experimental Psychology Learning Memory and Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kwantlen Polytechnic University","funders":"","keywords":"Hindsight bias; Psychology; Bernstein polynomial; Mathematics; Cognitive psychology; Applied mathematics","score_opus":0.22009332300850729,"score_gpt":0.4338916762259025,"score_spread":0.21379835321739524,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2322436276","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99199426,0.00024428035,0.00084300013,0.0002972268,0.0022405842,0.00008935585,0.0000045920924,0.0000096963295,0.004276997],"genre_scores_gemma":[0.9950304,0.000028878581,0.0019499639,0.0026891488,0.00006158895,0.000003017929,0.0000028743443,0.000012034297,0.00022206921],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9981073,0.00033529298,0.00074777554,0.00031172202,0.0003642083,0.0001336963],"domain_scores_gemma":[0.99849325,0.00039685544,0.000593311,0.00017193565,0.0001727975,0.00017183108],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0016815672,0.000117053,0.00033109123,0.0003733605,0.000074375625,0.000060441624,0.0002450972,0.00007976202,0.00131614],"category_scores_gemma":[0.000540965,0.0001037649,0.00011617064,0.00015718864,0.00007592025,0.0003024146,0.00007214204,0.00031945168,0.00031921305],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022644291,0.00070890086,0.004401678,6.069187e-7,0.000051250496,0.0001553051,0.011388677,0.00009047682,0.26535505,0.000012560863,0.040002905,0.67556816],"study_design_scores_gemma":[0.0076477304,0.019528082,0.45896003,0.00069622655,0.00021161116,0.0013823521,0.046388958,0.00011422649,0.3420833,0.02245853,0.099186786,0.0013421874],"about_ca_topic_score_codex":0.000043060125,"about_ca_topic_score_gemma":0.000010898779,"teacher_disagreement_score":0.674226,"about_ca_system_score_codex":0.000022091972,"about_ca_system_score_gemma":0.00002086009,"threshold_uncertainty_score":0.9995968},"labels":[],"label_agreement":null},{"id":"W2323260661","doi":"10.1509/jmkr.48.4.755","title":"Multiple Routes to Self- versus Other-Expression in Consumer Choice","year":2011,"lang":"en","type":"article","venue":"Journal of Marketing Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":41,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Priming (agriculture); Expression (computer science); Set (abstract data type); Psychology; Compromise; Consumer choice; Social psychology; Dimension (graph theory); Identification (biology); Risk-seeking; Cognitive psychology; Computer science; Microeconomics; Economics; Sociology; Mathematics","score_opus":0.44221241319001503,"score_gpt":0.4996332879537894,"score_spread":0.05742087476377439,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2323260661","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9928178,0.0001121481,0.000057482954,0.0002597915,0.00065293553,0.00013400539,0.0000035618148,0.000009805073,0.005952462],"genre_scores_gemma":[0.9902208,0.000029098353,0.009222316,0.00004160422,0.00015273348,0.0000033462534,8.3220804e-8,0.000017478385,0.0003125277],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9939411,0.0020284578,0.0011486787,0.00034947952,0.0019953242,0.0005369546],"domain_scores_gemma":[0.96686447,0.030493533,0.00044770315,0.00054120156,0.0013244429,0.00032864598],"candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.06229349,0.00012058306,0.00035394274,0.0013111986,0.00016765355,0.00027880233,0.0014296952,0.00011264856,0.0009117258],"category_scores_gemma":[0.08291305,0.00008435148,0.00013520244,0.0009755984,0.00007886277,0.00039974196,0.00041776654,0.0008160267,0.00037306012],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0072105657,0.0004768912,0.57802105,0.0000061260143,0.000017202545,0.00009405393,0.0021353795,0.000054513566,0.0025143044,0.0000074933278,0.022141399,0.38732103],"study_design_scores_gemma":[0.004967421,0.0010816532,0.7004812,0.0007899189,0.000014610031,0.000042503474,0.00631572,0.0009525992,0.0036192115,0.0048878547,0.2764044,0.0004428934],"about_ca_topic_score_codex":0.00013190506,"about_ca_topic_score_gemma":0.00022857076,"teacher_disagreement_score":0.38687813,"about_ca_system_score_codex":0.00019884389,"about_ca_system_score_gemma":0.00023356848,"threshold_uncertainty_score":0.9982758},"labels":[],"label_agreement":null},{"id":"W2331725338","doi":"10.1037/a0034887","title":"Base rates: Both neglected and intuitive.","year":2013,"lang":"en","type":"article","venue":"Journal of Experimental Psychology Learning Memory and Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":160,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Psychology; Neglect; Base (topology); Social psychology; Information processing; Cognition; Salient; Cognitive psychology; Statistics; Developmental psychology; Artificial intelligence; Computer science; Mathematics","score_opus":0.10049814131948827,"score_gpt":0.4264947180489293,"score_spread":0.32599657672944105,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2331725338","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99422574,0.00074973586,0.00039564667,0.0004079087,0.00036858473,0.00008591319,0.000001014574,0.000010828659,0.0037546314],"genre_scores_gemma":[0.9982821,0.00007860988,0.0005542558,0.00077536714,0.00009060147,0.0000042293773,0.000001597532,0.000009195698,0.00020403873],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99842566,0.00032158647,0.0006004273,0.00026504393,0.0002407034,0.00014657516],"domain_scores_gemma":[0.9985609,0.0004671052,0.00050419953,0.00010205475,0.0002203667,0.00014537796],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007652903,0.00012350218,0.00027717388,0.00028327535,0.00018886087,0.00022314275,0.00013942098,0.00010262123,0.001264853],"category_scores_gemma":[0.00052496005,0.00009407761,0.00006673924,0.00015145673,0.00020412647,0.0006410817,0.000051530023,0.000360878,0.00011518565],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00042533266,0.00035190038,0.0039096144,0.0000018372143,0.000035573197,0.000067488385,0.0016119662,0.000013257988,0.36932907,0.00003524857,0.0042427354,0.619976],"study_design_scores_gemma":[0.022169445,0.0183494,0.4298777,0.00074171665,0.00029887672,0.012077424,0.116161816,0.0023071826,0.15081593,0.22936776,0.015679205,0.002153533],"about_ca_topic_score_codex":0.000003837976,"about_ca_topic_score_gemma":5.3135597e-7,"teacher_disagreement_score":0.61782247,"about_ca_system_score_codex":0.00001526135,"about_ca_system_score_gemma":0.000017737986,"threshold_uncertainty_score":0.99964815},"labels":[],"label_agreement":null},{"id":"W2332905537","doi":"10.2139/ssrn.2577967","title":"Optimal Insurance with Heterogeneous Beliefs and Disagreement About Zero-Probability Events","year":2015,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Zero (linguistics); Actuarial science; Economics; Econometrics; Philosophy; Linguistics","score_opus":0.06863502844397323,"score_gpt":0.3397318518995336,"score_spread":0.27109682345556035,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2332905537","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9892407,0.0014976603,0.008227315,0.00039340655,0.0002823855,0.00015433446,0.000009497157,0.00001984759,0.0001748757],"genre_scores_gemma":[0.997944,0.0003109679,0.0011038014,0.0000749923,0.000110421126,0.0000054719,0.0000011067565,0.00001789301,0.00043137086],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9960135,0.00017721942,0.0007083815,0.0005410384,0.0011084483,0.0014513754],"domain_scores_gemma":[0.99828583,0.0001618206,0.00039277406,0.00048696215,0.0003384571,0.00033418034],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0064093405,0.00022926652,0.00036725745,0.00013793407,0.0002599807,0.00031125586,0.00070950633,0.00008178096,0.000027637792],"category_scores_gemma":[0.00043282314,0.00014858446,0.0001062008,0.0002604777,0.00013573402,0.00044610683,0.0001540267,0.000873509,0.000102951926],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00053419685,0.00029130012,0.20488301,0.0000017019433,0.000079164434,0.000026069272,0.00050683395,0.0076053897,0.000025330346,0.0016310253,0.00021896354,0.78419703],"study_design_scores_gemma":[0.0018502597,0.0017602566,0.017537303,0.000038285787,0.000027545539,0.0020864313,0.0008029818,0.0003711369,0.000046842637,0.97204846,0.0030507674,0.00037975388],"about_ca_topic_score_codex":0.00004244848,"about_ca_topic_score_gemma":0.00061796035,"teacher_disagreement_score":0.9704174,"about_ca_system_score_codex":0.0007278413,"about_ca_system_score_gemma":0.0012520284,"threshold_uncertainty_score":0.6059098},"labels":[],"label_agreement":null},{"id":"W2333026799","doi":"10.1037/a0030906","title":"Direct evidence for a dual process model of deductive inference.","year":2012,"lang":"en","type":"article","venue":"Journal of Experimental Psychology Learning Memory and Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Counterexample; Inference; Statistical inference; Heuristic; Frequentist inference; Computer science; Mathematics; Algorithm; Artificial intelligence; Statistics; Discrete mathematics; Bayesian inference","score_opus":0.3929391790820133,"score_gpt":0.5409938992105198,"score_spread":0.14805472012850646,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2333026799","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9928208,0.0010982471,0.0039122417,0.00008190684,0.00043575902,0.00010465973,0.0000037152406,0.000005410565,0.0015372622],"genre_scores_gemma":[0.9983128,0.00003699246,0.0013344389,0.00010492628,0.00013071227,0.000009152169,8.804878e-7,0.0000075653006,0.000062552004],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9985245,0.00016212893,0.00065843243,0.00019042034,0.00030054158,0.00016399306],"domain_scores_gemma":[0.9975585,0.0009988023,0.0008461269,0.00009610121,0.0003963425,0.000104166786],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022971237,0.00010638229,0.0003212624,0.00022617028,0.000121199664,0.000040551073,0.00015679402,0.00009281059,0.00008374247],"category_scores_gemma":[0.0018542598,0.000081912694,0.00011753964,0.00012458484,0.00016750256,0.0009388907,0.000031408723,0.00019785175,0.0000074989002],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005832265,0.0019499876,0.015875716,0.000022089389,0.00011662994,0.0000080114,0.01796646,0.0033593145,0.6192803,0.00018984967,0.000895501,0.33450392],"study_design_scores_gemma":[0.008523186,0.010348135,0.016954096,0.0011897662,0.00048777927,0.0012137641,0.06940611,0.0072302767,0.76235,0.12052689,0.0006050246,0.001164936],"about_ca_topic_score_codex":5.3882553e-7,"about_ca_topic_score_gemma":1.8567901e-7,"teacher_disagreement_score":0.33333898,"about_ca_system_score_codex":0.000018140148,"about_ca_system_score_gemma":0.000046420777,"threshold_uncertainty_score":0.33403027},"labels":[],"label_agreement":null},{"id":"W2336257582","doi":"10.14288/1.0105712","title":"The application of statistical decision theory to a perceptual decision-making problem","year":2011,"lang":"en","type":"article","venue":"cIRcle (University of British Columbia)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Decision theory; Evidential decision theory; Decision analysis; Perception; Causal decision theory; Computer science; Evidential reasoning approach; Business decision mapping; Cognitive psychology; Artificial intelligence; Psychology; Mathematics; Epistemology; Mathematical economics; Statistics; Philosophy","score_opus":0.035489589474884474,"score_gpt":0.28122507006767294,"score_spread":0.24573548059278846,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2336257582","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.68067336,0.000029016906,0.31735036,0.000014519905,0.00013413386,0.00027145605,0.00012905571,0.000021687083,0.0013763923],"genre_scores_gemma":[0.9371818,0.000018449002,0.06259871,0.000033645254,0.000015428945,0.0000015703565,0.000002115595,0.000013683139,0.00013459998],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99726844,0.00017633452,0.0006188546,0.0006774496,0.0009645802,0.00029431828],"domain_scores_gemma":[0.99394697,0.0038706223,0.00041520342,0.0009031322,0.0006820347,0.00018204763],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030873613,0.000071775656,0.00040969366,0.00013930429,0.0005048006,0.0002297355,0.0016822178,0.00013138502,0.00053870125],"category_scores_gemma":[0.0017007663,0.0001406533,0.00018686992,0.0006957096,0.00053555897,0.00034564905,0.0005462503,0.00015445185,0.0002945388],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016351721,0.00012861135,0.004712453,0.0000024400017,0.000009590504,0.000019675404,0.00074430445,0.000024188923,0.000038372997,0.00020950218,0.0031182237,0.9908291],"study_design_scores_gemma":[0.00028546472,0.00015657846,0.6901856,0.00011403776,0.000024453537,0.000027532911,0.005043223,0.00045506595,5.7152243e-7,0.30187094,0.0016873613,0.00014913939],"about_ca_topic_score_codex":0.006584229,"about_ca_topic_score_gemma":0.07914935,"teacher_disagreement_score":0.99068,"about_ca_system_score_codex":0.00007526834,"about_ca_system_score_gemma":0.00011834099,"threshold_uncertainty_score":0.99534285},"labels":[],"label_agreement":null},{"id":"W2340771183","doi":"10.3819/ccbr.2016.110002","title":"When Humans and Other Animals Behave Irrationally","year":2016,"lang":"en","type":"article","venue":"Comparative Cognition & Behavior Reviews","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Comparative cognition; Animal behavior; Psychology; Cognitive psychology; Neuroscience; Developmental psychology; Biology; Cognition; Zoology","score_opus":0.5234870141353815,"score_gpt":0.49228622357067914,"score_spread":0.03120079056470232,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2340771183","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98431134,0.0028687434,0.0037445722,0.0004540994,0.0003480605,0.0012248354,0.0002710757,0.000063332176,0.0067139617],"genre_scores_gemma":[0.994304,0.00030106504,0.0023122586,0.0006387316,0.00012304542,0.00036323958,0.0000129578175,0.000022337985,0.0019223525],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99632007,0.00049788516,0.0014349971,0.00084555085,0.00062188436,0.00027958574],"domain_scores_gemma":[0.9971438,0.0007779939,0.0007120877,0.00058423437,0.00057255063,0.00020934016],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0021392438,0.00032408012,0.0008346024,0.00026296542,0.0002858319,0.00038378843,0.0004915529,0.0001072949,0.006813087],"category_scores_gemma":[0.0005976176,0.00019137442,0.00023859998,0.00023837645,0.00033005673,0.0005576842,0.00014780414,0.00013284483,0.005230528],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000057382764,0.00032397907,0.030074773,0.0000044801336,0.000011489093,0.00001148197,0.0009932596,2.0242499e-7,0.014569957,0.0019943744,0.039605226,0.9123534],"study_design_scores_gemma":[0.0010617375,0.00029207152,0.07440095,0.00034562775,0.00020130382,0.000042911106,0.00035216106,0.000009879337,0.0011514772,0.059305638,0.86218256,0.000653684],"about_ca_topic_score_codex":0.0000056506797,"about_ca_topic_score_gemma":0.00010702461,"teacher_disagreement_score":0.9116997,"about_ca_system_score_codex":0.00005876753,"about_ca_system_score_gemma":0.000050104674,"threshold_uncertainty_score":0.995544},"labels":[],"label_agreement":null},{"id":"W2340876148","doi":"10.4213/tvp5029","title":"Последовательные $\\delta$-оптимальные потребление и инвестирование для финансовых рынков со стохастической волатильностью при неизвестных параметрах","year":2015,"lang":"ru","type":"article","venue":"Теория вероятностей и ее применения","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"Russian Science Foundation","keywords":"Delta; Geology; Physics","score_opus":0.3719890601196676,"score_gpt":0.44925162661847495,"score_spread":0.07726256649880736,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2340876148","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8575869,0.009679811,0.004308564,0.009131802,0.032051183,0.0034924315,0.0024548832,0.0018209232,0.079473466],"genre_scores_gemma":[0.942747,0.0010279184,0.005247052,0.004156578,0.0049466556,0.00027713113,0.00041615567,0.00083708006,0.040344443],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9653973,0.002751959,0.008924159,0.007662,0.009151801,0.006112803],"domain_scores_gemma":[0.96978295,0.0055534383,0.004409324,0.009850076,0.0043781423,0.0060260496],"candidate_categories":["metaresearch","metaepi_narrow","sts","scholarly_communication","open_science","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"category_scores_codex":[0.016444586,0.004378156,0.0058485037,0.0037004105,0.0024113143,0.0068585733,0.011463938,0.0034820023,0.009981769],"category_scores_gemma":[0.011504477,0.004101864,0.0031610955,0.006898285,0.0025471342,0.004960527,0.0045996155,0.004620342,0.05084996],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013898562,0.002483777,0.017782321,0.00010463654,0.00048565032,0.0013504252,0.0050885985,0.0020631622,0.0005841093,0.0021162243,0.4156875,0.55086374],"study_design_scores_gemma":[0.010191791,0.003119911,0.0070415167,0.0011803472,0.0012500903,0.0008653654,0.012644691,0.012643228,0.001384845,0.09034755,0.85151106,0.007819607],"about_ca_topic_score_codex":0.0028793116,"about_ca_topic_score_gemma":0.0019799233,"teacher_disagreement_score":0.5430441,"about_ca_system_score_codex":0.0026079796,"about_ca_system_score_gemma":0.0050659473,"threshold_uncertainty_score":0.9988874},"labels":[],"label_agreement":null},{"id":"W2343277410","doi":"10.1080/08959285.2016.1157595","title":"Intrinsic motivation, external reward, and their effect on overall motivation and performance","year":2016,"lang":"en","type":"article","venue":"Human Performance","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":168,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Psychology; Contrast (vision); Intrinsic motivation; Cognitive evaluation theory; Payment; Motivation theory; Cognition; Social psychology; Cognitive psychology; Selection (genetic algorithm); Goal theory; Self-determination theory; Economics; Computer science","score_opus":0.07796442960559502,"score_gpt":0.32064013492874555,"score_spread":0.24267570532315053,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2343277410","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99840844,0.00004150183,0.00022908417,0.00011419953,0.00022617509,0.00017638406,0.0000062106483,0.000045684483,0.0007523154],"genre_scores_gemma":[0.9986979,0.00009281657,0.000044664896,0.00015814166,0.0001477236,0.000012843304,0.000001404578,0.000016573696,0.0008279284],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99816936,0.00007575418,0.0005198224,0.00056802254,0.00040713782,0.00025988647],"domain_scores_gemma":[0.99800295,0.000987314,0.00025791023,0.0005059301,0.00014104281,0.000104833685],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001462182,0.00023455122,0.00029874712,0.000288356,0.0004139725,0.0002493735,0.00032866182,0.00008864711,0.00012295213],"category_scores_gemma":[0.0005692762,0.00012667735,0.000047656325,0.0001591832,0.00017077792,0.0010195563,0.0001494072,0.00014514633,0.00016944692],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000079543024,0.000016665921,0.32023963,0.0000057501848,0.0000024827018,6.5340276e-7,0.0001383306,0.00000817808,0.0018757116,0.00009405626,0.0001401364,0.67739886],"study_design_scores_gemma":[0.000886547,0.0010514841,0.9841726,0.00022008213,0.000004454395,0.000022828446,0.000015962374,0.00041994252,0.005948989,0.0052005122,0.0018296733,0.00022691906],"about_ca_topic_score_codex":0.0000036103202,"about_ca_topic_score_gemma":0.0000037570956,"teacher_disagreement_score":0.67717195,"about_ca_system_score_codex":0.000066120054,"about_ca_system_score_gemma":0.0000150216365,"threshold_uncertainty_score":0.5165752},"labels":[],"label_agreement":null},{"id":"W2343550067","doi":"10.1287/mnsc.2015.2360","title":"Optimal Time-Inconsistent Beliefs: Misplanning, Procrastination, and Commitment","year":2016,"lang":"en","type":"article","venue":"Management Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"York University; University of Cyprus; Northwestern University; Purdue University; National Science Foundation; Yale University; Princeton University; Alfred P. Sloan Foundation","keywords":"Procrastination; Incentive; Heuristics; Dynamic inconsistency; Overconfidence effect; Context (archaeology); Optimism; Consistency (knowledge bases); Economics; Psychology; Social psychology; Time consistency; Preference; Temptation; Microeconomics; Computer science; Actuarial science","score_opus":0.06130036716212591,"score_gpt":0.36102389068397983,"score_spread":0.29972352352185394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2343550067","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96400493,0.000033558452,0.008042204,0.003035199,0.00036634933,0.00035202125,0.000008372228,0.00006747186,0.024089882],"genre_scores_gemma":[0.97701025,0.000013105165,0.0107789505,0.00028168372,0.000027688293,0.000021723687,4.4818924e-7,0.0000069167177,0.011859231],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9970158,0.00004101003,0.0004810299,0.00083109224,0.0012763862,0.00035469927],"domain_scores_gemma":[0.99848306,0.0003145693,0.00020903925,0.00063151855,0.0001872707,0.00017454565],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003949088,0.00014457837,0.00017876149,0.00047580287,0.0004806142,0.0006350241,0.0011136231,0.000025794034,0.00026724895],"category_scores_gemma":[0.00053434545,0.000084574654,0.00004384228,0.0006918102,0.0006435451,0.0005397982,0.0008005615,0.00004115108,0.0011350217],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011814828,0.00007560339,0.009459436,0.0000021907892,0.0000052055675,0.000019549678,0.00013606959,0.000087051194,0.00064185105,0.0023401305,0.007137379,0.9800837],"study_design_scores_gemma":[0.0039963573,0.0009935906,0.40886465,0.00074802135,0.00011959864,0.00013133837,0.0023088437,0.016816799,0.003943514,0.097245395,0.46289474,0.0019371661],"about_ca_topic_score_codex":0.000003184458,"about_ca_topic_score_gemma":0.0000023702905,"teacher_disagreement_score":0.97814655,"about_ca_system_score_codex":0.00011495823,"about_ca_system_score_gemma":0.000033502907,"threshold_uncertainty_score":0.9996427},"labels":[],"label_agreement":null},{"id":"W2346103795","doi":"10.1177/0956797616640705","title":"More Similar but Less Satisfying","year":2016,"lang":"en","type":"article","venue":"Psychological Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Quest University Canada","funders":"","keywords":"Psychology; Stimulus (psychology); Cognitive psychology; Social psychology; Brand names; Advertising; Business","score_opus":0.36448613647690453,"score_gpt":0.5170243418813324,"score_spread":0.15253820540442786,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2346103795","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97563666,0.00002181209,0.006804648,0.005197622,0.0010136168,0.00009300047,0.000012481686,0.00008043205,0.011139746],"genre_scores_gemma":[0.9944183,0.000013978207,0.0035840047,0.0011520017,0.000079766156,0.000006995985,9.825643e-8,0.000005326321,0.00073950354],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9959465,0.00007954179,0.0005945306,0.0012683151,0.0015438742,0.0005672035],"domain_scores_gemma":[0.9969607,0.0012081368,0.00020508729,0.0010466878,0.00024512032,0.0003342944],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0050118538,0.00015988285,0.00026615208,0.00023870493,0.00043284884,0.0004892754,0.0027735496,0.00010113996,0.0013363537],"category_scores_gemma":[0.005503131,0.000072577306,0.00011649021,0.0013368058,0.00167123,0.00072121364,0.0003967991,0.0001252779,0.0023746963],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013122725,0.00006038078,0.017271738,1.1217105e-7,4.3861624e-7,0.000017016766,0.000044622244,0.000005896054,0.014040458,0.0008565116,0.0016903481,0.96599936],"study_design_scores_gemma":[0.00065453537,0.0002934624,0.5435483,0.00004508927,0.000005554513,0.00009292471,0.0006548732,0.00025719125,0.0020165327,0.42372343,0.028140953,0.00056718686],"about_ca_topic_score_codex":0.000008720747,"about_ca_topic_score_gemma":0.0000050219214,"teacher_disagreement_score":0.96543217,"about_ca_system_score_codex":0.000079973055,"about_ca_system_score_gemma":0.000040862862,"threshold_uncertainty_score":0.99957657},"labels":[],"label_agreement":null},{"id":"W2354814473","doi":"10.1016/j.beproc.2016.05.002","title":"Initial examination of priming tasks to decrease delay discounting","year":2016,"lang":"en","type":"article","venue":"Behavioural Processes","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Lethbridge; McMaster University","funders":"National Institute on Minority Health and Health Disparities; National Institute on Drug Abuse; National Institute on Alcohol Abuse and Alcoholism","keywords":"Discounting; Delay discounting; Psychology; Temporal discounting; Randomized controlled trial; Priming (agriculture); Clinical psychology; Developmental psychology; Medicine; Impulsivity; Internal medicine; Economics","score_opus":0.20521748116948638,"score_gpt":0.41767497197417297,"score_spread":0.2124574908046866,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2354814473","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9941506,0.000035104626,0.004168705,0.0003481586,0.00028202558,0.00019264832,0.000059960665,0.000047128386,0.0007156662],"genre_scores_gemma":[0.99764365,0.000003876796,0.0017932485,0.00009718637,0.00007210467,0.000022095095,0.0000040606824,0.000019656909,0.00034413527],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9972674,0.000078303565,0.0009252479,0.0005385729,0.00089038635,0.0003000436],"domain_scores_gemma":[0.99673665,0.0011548569,0.00046641292,0.00044148194,0.00091190764,0.0002886926],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0016350246,0.00018726173,0.0003292341,0.00038126847,0.00015152707,0.00022797131,0.00074840814,0.000092005925,0.00053227716],"category_scores_gemma":[0.013338967,0.00011275397,0.00008817107,0.0006836698,0.00010746257,0.0009936778,0.00022135663,0.000071872586,0.00020139277],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004342301,0.00011544257,0.031111328,0.000008245399,0.0000023660382,0.000014204977,0.00045353902,0.000009768666,0.0040104357,0.00006213573,0.00025967194,0.96390945],"study_design_scores_gemma":[0.003643914,0.0015104024,0.64349,0.0020546857,0.0003437122,0.00026167431,0.006291258,0.00019229854,0.286542,0.042470906,0.010465468,0.0027336592],"about_ca_topic_score_codex":0.000080562575,"about_ca_topic_score_gemma":0.00014413401,"teacher_disagreement_score":0.9611758,"about_ca_system_score_codex":0.00006493563,"about_ca_system_score_gemma":0.00027781693,"threshold_uncertainty_score":0.9949721},"labels":[],"label_agreement":null},{"id":"W238568077","doi":"10.4324/9780203358061-15","title":"Ambiguity made precise: a comparative foundation","year":2004,"lang":"en","type":"book-chapter","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Foundation (evidence); Ambiguity; Computer science; History; Archaeology; Programming language","score_opus":0.35048312759603867,"score_gpt":0.4468497772871338,"score_spread":0.09636664969109515,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W238568077","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008071267,0.000059147464,0.002696023,0.00028493092,0.0012738091,0.0004137559,0.000065135275,0.00011100574,0.9870249],"genre_scores_gemma":[0.14442806,0.000026132937,0.0024984416,0.00022836545,0.00022162523,0.0000089178,0.000051791572,0.000036941823,0.8524997],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9957482,0.000039949115,0.0013851739,0.0011209983,0.0014341759,0.0002714865],"domain_scores_gemma":[0.99637514,0.0007921469,0.0008466024,0.0012392711,0.000554079,0.00019273316],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0013731907,0.0004555458,0.0009411634,0.00049013743,0.00021282685,0.0008543361,0.0011846783,0.00046710996,0.031579066],"category_scores_gemma":[0.0002778181,0.00034391595,0.00041708158,0.00010367255,0.00023998556,0.0004288073,0.000320558,0.00046888113,0.028326973],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000672174,0.00006660211,0.00002738124,0.0000027420515,0.00003412216,0.000022507716,0.0002926,0.00022506336,0.000016477687,0.23039421,0.03150229,0.7373488],"study_design_scores_gemma":[0.00021133103,0.00007125523,0.00015122665,0.00005810055,0.00002690242,0.000009334535,0.00004200819,0.00007882114,0.000034057844,0.6667292,0.3322652,0.00032252743],"about_ca_topic_score_codex":0.000057259458,"about_ca_topic_score_gemma":0.00025748118,"teacher_disagreement_score":0.7370263,"about_ca_system_score_codex":0.00039558244,"about_ca_system_score_gemma":0.00034929023,"threshold_uncertainty_score":0.9999013},"labels":[],"label_agreement":null},{"id":"W2399606725","doi":"10.29173/cais637","title":"Influence of Need for Cognition and Need for Cognitive Closure on Information Behaviour","year":2013,"lang":"fr","type":"article","venue":"Proceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSI","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Cognition; Closure (psychology); Psychology; Humanities; Philosophy; Political science","score_opus":0.04803628603982367,"score_gpt":0.3151716091163965,"score_spread":0.26713532307657284,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2399606725","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99157876,0.00010894751,0.00015283484,0.0025652726,0.000304575,0.0019822726,0.0024485793,0.000017320262,0.00084145856],"genre_scores_gemma":[0.9980241,0.000083918036,0.00092990854,0.0003450184,0.000063651416,0.00017799807,0.000022048389,0.000021531232,0.0003318327],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99698836,0.00003240527,0.0014659988,0.00040430715,0.00065636105,0.00045258485],"domain_scores_gemma":[0.89442563,0.0019187161,0.0025681702,0.00020615864,0.1006916,0.00018970852],"candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0015375563,0.00036676595,0.000803861,0.00042157475,0.00021190563,0.0029027972,0.0011822357,0.00038686214,0.000038078815],"category_scores_gemma":[0.05257775,0.00029167155,0.00031141567,0.00048188298,0.0009509631,0.018788233,0.00034961023,0.0002613388,0.000012876083],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0034228456,0.0009864809,0.24315625,0.0014537367,0.00026448956,4.6461278e-7,0.056016665,0.00015006665,0.014559047,0.017120475,0.010466726,0.65240276],"study_design_scores_gemma":[0.009205805,0.0075444235,0.5021812,0.0063979975,0.0015201989,0.00006742626,0.057207253,0.0059481524,0.11920651,0.26637506,0.022741698,0.0016042973],"about_ca_topic_score_codex":0.00034048237,"about_ca_topic_score_gemma":0.000012743496,"teacher_disagreement_score":0.65079844,"about_ca_system_score_codex":0.00005079365,"about_ca_system_score_gemma":0.00032508344,"threshold_uncertainty_score":0.99995357},"labels":[],"label_agreement":null},{"id":"W2400773071","doi":"10.82308/8080","title":"Suggestion modulates deeply ingrained processes","year":2014,"lang":"en","type":"article","venue":"eScholarship@McGill (McGill)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Automaticity; Suggestibility; Cognitive psychology; Psychology; Cognition; Stroop effect; Hypnosis; Context (archaeology); Automatism (medicine); Reading (process); Perception; Trait; Neuroscience; Computer science; Medicine","score_opus":0.06187368744174021,"score_gpt":0.31557344862210274,"score_spread":0.2536997611803625,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2400773071","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9764332,0.00005944675,0.000030996747,0.00014375342,0.0010168006,0.00028778624,0.0001723264,0.00035336908,0.021502275],"genre_scores_gemma":[0.99450964,0.000024277855,0.002917222,0.00059314666,0.00010275325,0.000038122675,0.000020496613,0.00007925952,0.0017150564],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9942878,0.000500915,0.001465939,0.0014863148,0.0015138366,0.0007452327],"domain_scores_gemma":[0.9936363,0.002679522,0.00069057074,0.0013864136,0.001146925,0.0004602804],"candidate_categories":["metaresearch","metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.005478532,0.0005155314,0.000729543,0.0006612149,0.0012745352,0.0006455893,0.0017081092,0.00030239506,0.0003750394],"category_scores_gemma":[0.023626482,0.00043052158,0.00028341645,0.0016367182,0.00016600624,0.001843285,0.0004613447,0.00062794023,0.002789869],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006968614,0.00017317967,0.001009572,0.000015093391,0.000016064467,0.000013417089,0.000008051081,0.0006722273,0.005352817,0.01714397,0.00004085302,0.9754851],"study_design_scores_gemma":[0.0008633633,0.00026005454,0.0030514558,0.00011886864,0.000051956875,0.000060884064,0.00013222209,0.001251486,0.019928316,0.737875,0.23553236,0.0008740324],"about_ca_topic_score_codex":0.00012255648,"about_ca_topic_score_gemma":0.00037070442,"teacher_disagreement_score":0.97461104,"about_ca_system_score_codex":0.0002684115,"about_ca_system_score_gemma":0.000057338322,"threshold_uncertainty_score":0.9998146},"labels":[],"label_agreement":null},{"id":"W2405516634","doi":"10.4018/978-1-4666-9989-2.ch007","title":"Economic Decision Making, Emotion, and Prefrontal Cortex","year":2016,"lang":"en","type":"book-chapter","venue":"Advances in psychology, mental health, and behavioral studies (APMHBS) book series","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Neuroeconomics; Consumer neuroscience; Prefrontal cortex; Psychology; Self-reference effect; Anterior cingulate cortex; Neuroscience; Social decision making; Posterior parietal cortex; Cognitive psychology; Cognitive science; Cognition","score_opus":0.09175461107323424,"score_gpt":0.4763771090778247,"score_spread":0.3846224980045905,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2405516634","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.36605552,0.50511014,0.00008105375,0.0037473207,0.01776301,0.0031332755,0.0021106822,0.0002577686,0.10174124],"genre_scores_gemma":[0.07460727,0.85402966,0.0030576806,0.0027000157,0.0006188608,0.00013723294,0.000082882594,0.00021259293,0.06455384],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9936936,0.00013226029,0.0024787073,0.002255935,0.0006260469,0.00081344973],"domain_scores_gemma":[0.99658966,0.00057819096,0.0013901856,0.0009282406,0.00014861602,0.00036507926],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0013045855,0.0009603058,0.0019560738,0.00064081413,0.00087327376,0.00018926835,0.0007090526,0.00048847636,0.0006105482],"category_scores_gemma":[0.00007394323,0.0007343617,0.00023600913,0.00007458483,0.0022997684,0.0030526912,0.00069828704,0.00060376705,0.00026911657],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00082774303,0.00010205195,0.0049419287,0.000032493415,0.000029853732,0.000044374934,0.0013918029,6.170166e-7,0.0000042320426,0.0057012695,0.0057460666,0.98117757],"study_design_scores_gemma":[0.001449136,0.0018546631,0.0036859675,0.001184526,0.000042872896,0.00033993716,0.0032627739,0.0000012780007,0.0000015235105,0.20964992,0.777654,0.00087342603],"about_ca_topic_score_codex":0.000020756699,"about_ca_topic_score_gemma":0.003170642,"teacher_disagreement_score":0.9803041,"about_ca_system_score_codex":0.00064970873,"about_ca_system_score_gemma":0.00014979501,"threshold_uncertainty_score":0.99951077},"labels":[],"label_agreement":null},{"id":"W2408398668","doi":"","title":"Decision rules and correlated features","year":2014,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Heuristics; Decision rule; Cognition; Feature (linguistics); Computer science; Artificial intelligence; Machine learning; Psychology; Operations research; Mathematics; Linguistics","score_opus":0.031944881259334125,"score_gpt":0.2860680697399145,"score_spread":0.25412318848058035,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2408398668","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97262454,0.00023149657,0.0011670365,0.0005382368,0.0005208446,0.00015106925,0.00080306653,0.00026346426,0.023700237],"genre_scores_gemma":[0.9935304,0.000017574492,0.0032741337,0.00077199866,0.00013394786,0.0000053183694,0.00011834243,0.000059007096,0.002089308],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9965402,0.0001516042,0.0009527471,0.00094630115,0.0009563664,0.00045278328],"domain_scores_gemma":[0.99529225,0.0029229962,0.00029863266,0.0008904593,0.000098405915,0.0004972384],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0011900051,0.00035689064,0.0005052291,0.00044904326,0.0003001835,0.006602119,0.0011576466,0.00028833447,0.0008410478],"category_scores_gemma":[0.005475512,0.00025732451,0.0002149379,0.0006064707,0.00019870578,0.004429045,0.0006801049,0.0005105169,0.010988593],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012871421,0.000076647135,0.07936343,0.0000019972638,0.0000074103723,0.000016318427,0.000016294114,0.000015596463,0.00002460854,0.0017164493,0.018419439,0.9002131],"study_design_scores_gemma":[0.0004894832,0.00010397168,0.038702957,0.00006224952,0.000011113407,0.000057989902,0.000035643796,0.00052331743,0.00016424368,0.4979944,0.46147454,0.00038009515],"about_ca_topic_score_codex":0.0000020930381,"about_ca_topic_score_gemma":0.000002149037,"teacher_disagreement_score":0.899833,"about_ca_system_score_codex":0.000020958167,"about_ca_system_score_gemma":0.00005318573,"threshold_uncertainty_score":0.9999879},"labels":[],"label_agreement":null},{"id":"W2412317068","doi":"10.1017/s1930297500007269","title":"Backward planning: Effects of planning direction on predictions of task completion time","year":2016,"lang":"en","type":"article","venue":"Judgment and Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Wilfrid Laurier University","funders":"Social Sciences and Humanities Research Council of Canada; University of Cambridge; Wilfrid Laurier University","keywords":"Conceptualization; Task (project management); Situational ethics; Psychology; Plan (archaeology); Process (computing); Cognitive psychology; Cognition; Computer science; Social psychology; Artificial intelligence; Economics","score_opus":0.0784911569911952,"score_gpt":0.3773283579389439,"score_spread":0.29883720094774874,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2412317068","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94038653,0.00014248877,0.056590933,0.000065868546,0.0007802389,0.00020912265,0.000024067587,0.000041965606,0.0017587985],"genre_scores_gemma":[0.9964428,0.000017054917,0.0032117395,0.000048592257,0.00007565066,0.000007882119,0.0000015069187,0.000015169619,0.00017959983],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9970639,0.00010201729,0.001025394,0.00053803064,0.0010549208,0.00021576336],"domain_scores_gemma":[0.9914644,0.0070765987,0.00068117795,0.0004872749,0.00019981874,0.000090745416],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014777394,0.00019441314,0.00051805767,0.00068477035,0.0001783254,0.00009260951,0.0003153578,0.00012943843,0.00015529744],"category_scores_gemma":[0.001838772,0.00012150012,0.00015865892,0.0003922149,0.00011212935,0.00029173068,0.00017338229,0.00009998173,0.00012864928],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00054591545,0.00016852425,0.02070048,0.000010937529,0.000021375083,0.000010633114,0.0003145263,0.0016844977,0.01456526,0.00023732093,0.009422358,0.9523182],"study_design_scores_gemma":[0.006602679,0.003727923,0.57403445,0.012443024,0.00023653723,0.00007361018,0.0006020812,0.027473858,0.01519816,0.32798967,0.030324465,0.0012935343],"about_ca_topic_score_codex":0.0000029824669,"about_ca_topic_score_gemma":7.1239515e-7,"teacher_disagreement_score":0.95102465,"about_ca_system_score_codex":0.00006680903,"about_ca_system_score_gemma":0.000024426125,"threshold_uncertainty_score":0.4954631},"labels":[],"label_agreement":null},{"id":"W2413665923","doi":"10.1097/wnr.0000000000000495","title":"Stimulus-preceding negativity represents a conservative response tendency","year":2015,"lang":"en","type":"article","venue":"Neuroreport","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brock University","funders":"Japan Society for the Promotion of Science; Ministry of Education, Culture, Sports, Science and Technology","keywords":"Psychology; Counterintuitive; Expectancy theory; Dilemma; Negativity effect; Cognitive psychology; Stimulus (psychology); Task (project management); Social psychology; Event-related potential; Anticipation (artificial intelligence); Developmental psychology; Cognition; Neuroscience","score_opus":0.5250364136970371,"score_gpt":0.49850352499600953,"score_spread":0.0265328887010276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2413665923","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97686666,0.0000140749235,0.00072416017,0.001209593,0.0016879252,0.00022497868,0.0000150775795,0.0001271416,0.019130372],"genre_scores_gemma":[0.9921935,0.0000014249706,0.0012199472,0.00049570034,0.000092888375,0.000015011558,0.000002122956,0.000023879069,0.005955532],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9949818,0.0006565576,0.0012369989,0.0010571996,0.0016968836,0.00037056097],"domain_scores_gemma":[0.9937012,0.0026965216,0.0007639011,0.0015360671,0.00085608766,0.00044617642],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.008556711,0.00023328545,0.00047519218,0.00027798672,0.00030446405,0.00082948536,0.00086646416,0.000119805285,0.00016006744],"category_scores_gemma":[0.057049807,0.00018213353,0.00017514525,0.0008705954,0.00020270789,0.0008044368,0.00051272113,0.0003159614,0.0008475048],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0023907656,0.00039362026,0.66939425,0.000001709077,0.000021448577,0.0030782933,0.0016532718,0.0007923307,0.0027269009,0.00012487134,0.152969,0.16645353],"study_design_scores_gemma":[0.0025020537,0.0012239887,0.47885078,0.000069494046,0.000063478445,0.0015447958,0.0029937,0.01056328,0.005112447,0.26081023,0.23504919,0.0012165575],"about_ca_topic_score_codex":0.00013782727,"about_ca_topic_score_gemma":0.000033724704,"teacher_disagreement_score":0.26068535,"about_ca_system_score_codex":0.00010423814,"about_ca_system_score_gemma":0.0005515142,"threshold_uncertainty_score":0.99993044},"labels":[],"label_agreement":null},{"id":"W2414426779","doi":"10.1037/apl0000121","title":"An integrative formal model of motivation and decision making: The MGPM*.","year":2016,"lang":"en","type":"article","venue":"Journal of Applied Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":65,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Australian Research Council","keywords":"PsycINFO; Psychology; Prioritization; Townsend; Goal pursuit; Empirical research; Cognitive psychology; Social psychology; Management science; Statistics","score_opus":0.12308160801237555,"score_gpt":0.4426518321841005,"score_spread":0.3195702241717249,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2414426779","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7647708,0.000019669684,0.23268607,0.00040108027,0.0002579875,0.000060789458,0.0000055958208,0.0000028689174,0.0017951194],"genre_scores_gemma":[0.98456573,0.000037585374,0.0149299735,0.00037268337,0.00007129913,0.0000015274965,1.11565136e-7,0.00000787392,0.000013203909],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9979928,0.000057786532,0.001087733,0.00023554407,0.00046541926,0.00016067894],"domain_scores_gemma":[0.9962294,0.0017642124,0.00116073,0.0004341283,0.00034073734,0.00007077893],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003139292,0.000118482145,0.00035865617,0.0003321034,0.000086509855,0.00006054213,0.00075981335,0.00012221627,0.00008740872],"category_scores_gemma":[0.00046745987,0.00004842837,0.00009825131,0.00020684245,0.00023095049,0.00046398927,0.00006999303,0.00018069443,0.000014139235],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008775732,0.00008446147,0.00084933575,2.789632e-7,0.000008723927,0.0000014787621,0.00058833114,0.00053441967,0.008255009,0.0047410997,0.0020292022,0.9820301],"study_design_scores_gemma":[0.0010197732,0.00049480813,0.012010347,0.000047719153,0.00001747206,0.000083900304,0.0007889303,0.002608161,0.0005088534,0.9814734,0.00085156556,0.00009506482],"about_ca_topic_score_codex":3.6186339e-7,"about_ca_topic_score_gemma":0.0000031982377,"teacher_disagreement_score":0.981935,"about_ca_system_score_codex":0.000024560803,"about_ca_system_score_gemma":0.000047688656,"threshold_uncertainty_score":0.19748516},"labels":[],"label_agreement":null},{"id":"W2417813467","doi":"10.1037/pspa0000058","title":"Revising probability estimates: Why increasing likelihood means increasing impact.","year":2016,"lang":"en","type":"article","venue":"Journal of Personality and Social Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":65,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"University of Toronto","keywords":"PsycINFO; Event (particle physics); Psychology; Social psychology; Cognition; Climate change; Conditional probability; Econometrics; Cognitive psychology; Statistics; Economics; MEDLINE; Mathematics","score_opus":0.17316157277339728,"score_gpt":0.4587315922926804,"score_spread":0.2855700195192831,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2417813467","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9848653,0.00021188665,0.0044175326,0.009304174,0.00049893575,0.000078291996,0.00002683925,0.000013767699,0.00058325083],"genre_scores_gemma":[0.9936574,0.000041353014,0.0046909424,0.0010703894,0.0005176258,6.175709e-7,4.793959e-7,0.0000129328,0.000008264597],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9958896,0.0012247884,0.0013620895,0.00044025868,0.00069438625,0.00038885925],"domain_scores_gemma":[0.99464774,0.0030260643,0.001161671,0.00027399982,0.0006578935,0.00023262919],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.016358178,0.00021294123,0.00078868016,0.0002543885,0.00041578006,0.00030392333,0.0005212847,0.00025426186,0.00039969524],"category_scores_gemma":[0.0065248166,0.00012470022,0.00044703163,0.00027916304,0.0005126381,0.00073299103,0.00009954257,0.00033935727,0.000024433624],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012111908,0.00028024425,0.21906678,0.000009535288,0.0000697859,0.00003346496,0.0027074714,0.0000016971999,0.0041993596,0.0002901696,0.002781346,0.769349],"study_design_scores_gemma":[0.001459486,0.00041130272,0.5434968,0.0001657612,0.00008675955,0.0011496777,0.00084750855,0.000025767744,0.000022061251,0.44659647,0.0054526953,0.00028569502],"about_ca_topic_score_codex":0.0001360139,"about_ca_topic_score_gemma":0.000044619588,"teacher_disagreement_score":0.76906323,"about_ca_system_score_codex":0.00019482481,"about_ca_system_score_gemma":0.00017884052,"threshold_uncertainty_score":0.78112864},"labels":[],"label_agreement":null},{"id":"W2418231525","doi":"10.9778/cmajo.20150071","title":"Attitude to health risk in the Canadian population: a cross-sectional survey","year":2016,"lang":"en","type":"article","venue":"CMAJ Open","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"Centre for Advancing Health Outcomes; University of British Columbia; Simon Fraser University; Vancouver Coastal Health","funders":"Canadian Cancer Society Research Institute; Canadian Centre for Applied Research in Cancer Control","keywords":"Scale (ratio); Population; Numeracy; Cross-sectional study; Risk aversion (psychology); Psychology; Demography; Environmental health; Medicine; Geography; Economics; Literacy","score_opus":0.35684462402325123,"score_gpt":0.5128200314597706,"score_spread":0.1559754074365194,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2418231525","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9935008,0.000009413214,0.00011991115,0.003169615,0.0005478822,0.00039751636,0.00026397963,0.0000056456397,0.0019851958],"genre_scores_gemma":[0.9966093,0.000002008534,0.00032378596,0.0017882059,0.00006127989,0.00002185549,0.000009190502,0.0000066409366,0.0011777586],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99764764,0.000513694,0.0005907981,0.00045828242,0.0005046309,0.0002849352],"domain_scores_gemma":[0.9975258,0.0012230908,0.00017573452,0.0006833321,0.00014625,0.00024579646],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.014007378,0.00008915777,0.00020065611,0.00023106213,0.0005047971,0.0016707795,0.0019915449,0.00006072704,0.0009585617],"category_scores_gemma":[0.0030512058,0.000045716275,0.00004609986,0.00056273077,0.000040470226,0.00040626366,0.00022073889,0.00010338959,0.0020410458],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000150396445,0.00001184961,0.84778666,7.7707526e-8,8.788322e-7,0.0000019643603,0.00012265694,0.00006854193,1.7985134e-7,0.00014129688,0.006658404,0.14519246],"study_design_scores_gemma":[0.00019105237,0.000036796388,0.9508972,0.000007206154,3.3038037e-7,0.000004781177,0.000025435764,0.000011091832,2.890595e-7,0.013273167,0.035473507,0.00007909472],"about_ca_topic_score_codex":0.82558984,"about_ca_topic_score_gemma":0.9896384,"teacher_disagreement_score":0.16404852,"about_ca_system_score_codex":0.00040637422,"about_ca_system_score_gemma":0.00054211536,"threshold_uncertainty_score":0.9999547},"labels":[],"label_agreement":null},{"id":"W2418924742","doi":"10.1111/asap.12119","title":"Goal Framing in Public Issue and Action Decisions","year":2016,"lang":"en","type":"article","venue":"Analyses of Social Issues and Public Policy","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan; Campion College; University of Regina","funders":"","keywords":"Framing (construction); Framing effect; Loss aversion; Social psychology; Psychology; Public economics; Prospect theory; Economics; Public relations; Political science; Microeconomics","score_opus":0.28297419481605923,"score_gpt":0.5105024283733234,"score_spread":0.22752823355726415,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2418924742","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9752762,0.00060852914,0.00020676103,0.021892404,0.00010642555,0.00006374,0.000032398377,0.000019785171,0.0017937587],"genre_scores_gemma":[0.9967265,0.0014047226,0.00025404207,0.00019920201,0.0003969262,0.000004122344,0.000002172065,0.000010724601,0.0010015928],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.997758,0.00016366068,0.0007492685,0.00044556687,0.0005200192,0.00036349692],"domain_scores_gemma":[0.9976449,0.0012590917,0.0003274126,0.00029228747,0.00027707737,0.00019922339],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014581372,0.00016163831,0.00050284225,0.0012221192,0.00025456457,0.0005288851,0.00041037967,0.00017942238,0.00034678399],"category_scores_gemma":[0.00563268,0.00010382899,0.00012458132,0.0011602382,0.00033878986,0.0012245137,0.00026741406,0.000104919,0.000054202203],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010771314,0.000059941867,0.026191607,0.0000012916097,0.000015863876,0.0000017903403,0.00034174952,2.631974e-7,0.00070203404,0.0059489473,0.0026234658,0.96410227],"study_design_scores_gemma":[0.0012085154,0.00015657434,0.32542303,0.000058293008,0.000041174255,0.000012715907,0.0042518904,0.00016191529,0.00036610017,0.31231603,0.35552248,0.0004812807],"about_ca_topic_score_codex":0.006521839,"about_ca_topic_score_gemma":0.0011294669,"teacher_disagreement_score":0.963621,"about_ca_system_score_codex":0.000058676564,"about_ca_system_score_gemma":0.00014514093,"threshold_uncertainty_score":0.98591137},"labels":[],"label_agreement":null},{"id":"W2431859568","doi":"10.1017/s0033291716000866","title":"Steep discounting of delayed monetary and food rewards in obesity: a meta-analysis","year":2016,"lang":"en","type":"review","venue":"Psychological Medicine","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":275,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; Homewood Research Institute; St. Joseph’s Healthcare Hamilton","funders":"National Institute on Drug Abuse; National Institutes of Health","keywords":"Meta-analysis; Publication bias; Meta-regression; Sample size determination; Delay discounting; Obesity; Psychology; Random effects model; Regression analysis; Statistics; Demography; Econometrics; Medicine; Economics; Clinical psychology; Mathematics; Internal medicine; Impulsivity","score_opus":0.5675461112680579,"score_gpt":0.5435027870232559,"score_spread":0.024043324244801934,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2431859568","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00935456,0.98770964,0.0006445982,0.0004355406,0.00027253586,0.0004116893,0.00013384545,0.000019031742,0.0010185613],"genre_scores_gemma":[0.048554454,0.95033205,0.00053706707,0.00016715015,0.000117103256,0.000044744076,0.000016079752,0.000019620082,0.00021175848],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99317163,0.0006105054,0.0032620744,0.0014345477,0.0011606432,0.00036062158],"domain_scores_gemma":[0.9914054,0.005242017,0.0016441008,0.0013571989,0.00015128171,0.00019995244],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0077406242,0.00051332253,0.008138223,0.0015235646,0.000052595133,0.0000491979,0.0012405703,0.00047726987,0.0022256982],"category_scores_gemma":[0.003565518,0.00021071956,0.0018291168,0.0023902236,0.0004920946,0.00012304248,0.00029334472,0.00052680634,0.00008429207],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011919015,0.000113404836,0.000099228055,0.000070310554,0.0049271565,0.000024733965,0.000038934948,7.990205e-7,1.3906185e-7,0.000061262785,0.00031213355,0.99434],"study_design_scores_gemma":[0.0015790277,0.0031161602,0.0026599204,0.0032390489,0.32939628,0.0001577792,0.00033481713,0.000055605105,1.3248754e-7,0.14166516,0.5163495,0.0014466012],"about_ca_topic_score_codex":0.00004117102,"about_ca_topic_score_gemma":0.0000730936,"teacher_disagreement_score":0.9928934,"about_ca_system_score_codex":0.00004013196,"about_ca_system_score_gemma":0.000017901923,"threshold_uncertainty_score":0.9986864},"labels":[],"label_agreement":null},{"id":"W2463671667","doi":"10.1287/mnsc.2016.2547","title":"The Value of Nothing: Asymmetric Attention to Opportunity Costs Drives Intertemporal Decision Making","year":2016,"lang":"en","type":"article","venue":"Management Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":82,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Economic and Social Research Council","keywords":"Opportunity cost; Economics; Value (mathematics); Task (project management); Microeconomics; Intertemporal choice; Nothing; Actuarial science; Public economics; Computer science; Management","score_opus":0.09382239497470354,"score_gpt":0.40470605893728356,"score_spread":0.31088366396258005,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2463671667","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8952591,0.000013972718,0.090393566,0.0018470996,0.001473919,0.00032034251,0.0000051572856,0.000032384203,0.010654486],"genre_scores_gemma":[0.9913613,0.000016744112,0.007174919,0.00033033962,0.000023265327,0.000009943054,1.454687e-7,0.000007999133,0.0010753078],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9954675,0.00010106565,0.0009455378,0.0008056272,0.002250928,0.00042936977],"domain_scores_gemma":[0.99581224,0.0018424869,0.00049887033,0.001287393,0.00033976595,0.00021922337],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011082875,0.00015865533,0.00023484965,0.0012634464,0.00065399054,0.0007552915,0.0033231913,0.000036047564,0.00006468352],"category_scores_gemma":[0.0051994654,0.00007938447,0.00013202125,0.0031911877,0.0005416617,0.00092485006,0.001672998,0.00007149124,0.00044697363],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033842673,0.000041740128,0.01085816,9.292096e-7,0.0000032546227,0.0000057391962,0.00008271098,0.00004261706,0.0005718293,0.007382604,0.001789596,0.97918695],"study_design_scores_gemma":[0.0010115072,0.00052030326,0.7114538,0.0010109856,0.000048964088,0.00001327913,0.0036344798,0.0064137527,0.0016315485,0.18363406,0.08985086,0.0007764457],"about_ca_topic_score_codex":0.000013823764,"about_ca_topic_score_gemma":0.000019850533,"teacher_disagreement_score":0.97841054,"about_ca_system_score_codex":0.0002548915,"about_ca_system_score_gemma":0.000062246014,"threshold_uncertainty_score":0.7283293},"labels":[],"label_agreement":null},{"id":"W2472982715","doi":"10.1016/j.neuropsychologia.2016.07.002","title":"Using future thinking to reduce temporal discounting: Under what circumstances are the medial temporal lobes critical?","year":2016,"lang":"en","type":"article","venue":"Neuropsychologia","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":42,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Mental Health; Canadian Institutes of Health Research; U.S. Department of Veterans Affairs","keywords":"Temporal discounting; Psychology; Intertemporal choice; Cognitive psychology; Task (project management); Contrast (vision); Discounting; Semantic memory; Cognition; Temporal lobe; Social psychology; Developmental psychology; Impulsivity; Neuroscience","score_opus":0.21821238537149978,"score_gpt":0.4535331950295583,"score_spread":0.23532080965805852,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2472982715","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9441063,0.00023535243,0.0039851693,0.03944774,0.011395695,0.00023689325,0.000024596535,0.00011370027,0.00045456117],"genre_scores_gemma":[0.99103963,0.000039595092,0.0019046658,0.0052208933,0.0015853157,0.000009886986,9.686194e-7,0.000041615538,0.00015743724],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9951956,0.00046269628,0.0009893919,0.0012929956,0.0014136046,0.00064569764],"domain_scores_gemma":[0.99528325,0.0022030629,0.0004492981,0.0014616156,0.0003623109,0.00024047046],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0027211385,0.00035852953,0.00047855824,0.00019285499,0.00066165905,0.002247427,0.0023117214,0.00020466189,0.00038264616],"category_scores_gemma":[0.0030917395,0.00017033711,0.00022479013,0.0008679841,0.00053210557,0.0016658737,0.00039441595,0.000389995,0.00060466176],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003772501,0.00032863166,0.12161675,0.000005599361,0.000019211271,0.000311792,0.0013546685,0.0001440905,0.01775919,0.0032989448,0.03324494,0.8215389],"study_design_scores_gemma":[0.0019782179,0.0007460975,0.24809195,0.0010184123,0.00011713313,0.0005503736,0.039689586,0.00018058915,0.001435623,0.56021935,0.14365523,0.0023174465],"about_ca_topic_score_codex":0.000014722538,"about_ca_topic_score_gemma":0.0000654024,"teacher_disagreement_score":0.8192215,"about_ca_system_score_codex":0.00007821252,"about_ca_system_score_gemma":0.00007088083,"threshold_uncertainty_score":0.99878836},"labels":[],"label_agreement":null},{"id":"W2480743960","doi":"10.1017/cbo9780511753855.001","title":"Introduction and Motivation","year":2006,"lang":"en","type":"book-chapter","venue":"Cambridge University Press eBooks","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Las vegas; Sight; Subject (documents); Psychology; Investment (military); Visual arts; History; Art; Art history; Advertising; Media studies; Social psychology; Business; Sociology; Political science; Law; Archaeology; Library science; Computer science; Astronomy; Physics","score_opus":0.07643632243748538,"score_gpt":0.2673435209262421,"score_spread":0.1909071984887567,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2480743960","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015565568,0.000043904736,0.000865564,0.000096111056,0.0006150517,0.00019570829,0.0001336556,0.000073074865,0.9824114],"genre_scores_gemma":[0.008091658,0.000020581854,0.00013564673,0.000028614293,0.0004819586,1.9226157e-7,0.000036441732,0.000023779652,0.99118114],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9981115,0.00004064512,0.0003786066,0.00080625707,0.00049568585,0.00016733221],"domain_scores_gemma":[0.99817246,0.00029711094,0.00043957922,0.00067723094,0.0003077709,0.00010585406],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00045113024,0.00026379316,0.00039514064,0.00042206844,0.00021489238,0.00023392135,0.0004706357,0.00033238647,0.00002351961],"category_scores_gemma":[0.00013030731,0.00026634388,0.0001479377,0.000016024405,0.0002452406,0.0002233026,0.0003351909,0.00030446256,0.00007231469],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000061210136,0.000009889717,0.000029123157,0.0000052719847,0.000018852928,0.000054446013,0.00001662505,0.000030321973,0.000030968014,0.3707369,0.5119878,0.11701861],"study_design_scores_gemma":[0.0002276425,0.00003511352,0.00023946437,0.000024011064,0.00006473872,0.000017988881,0.000023828059,0.00010374388,0.000048512487,0.0009495871,0.99798983,0.0002755308],"about_ca_topic_score_codex":0.000076144715,"about_ca_topic_score_gemma":0.0000033801327,"teacher_disagreement_score":0.48600206,"about_ca_system_score_codex":0.00011967921,"about_ca_system_score_gemma":0.000049813007,"threshold_uncertainty_score":0.9999789},"labels":[],"label_agreement":null},{"id":"W2494441066","doi":"10.1002/bdm.1973","title":"Real‐World Correlates of Performance on Heuristics and Biases Tasks in a Community Sample","year":2016,"lang":"en","type":"article","venue":"Journal of Behavioral Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":74,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; York University","funders":"Social Sciences and Humanities Research Council of Canada; John Templeton Foundation","keywords":"Heuristics; Psychology; Debiasing; Sample (material); Discounting; Cognitive psychology; Social psychology; Computer science","score_opus":0.21325087115341906,"score_gpt":0.44435378110373414,"score_spread":0.23110290995031507,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2494441066","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99728984,0.000060082297,0.0015530656,0.00005242272,0.00071082206,0.0000989575,0.000059829832,0.000008986312,0.0001659729],"genre_scores_gemma":[0.9912536,0.00020456186,0.00838832,0.000032382595,0.000048820093,0.0000012617679,4.4222486e-7,0.000021124932,0.00004945074],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99527943,0.00037620196,0.0024597417,0.00028449748,0.0013042704,0.00029583913],"domain_scores_gemma":[0.9793416,0.0173837,0.0017953849,0.0007064109,0.0006181187,0.00015477554],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005695039,0.0002440949,0.00084194733,0.0016226606,0.00019656646,0.00017779073,0.0010155737,0.00013699214,0.00021248669],"category_scores_gemma":[0.0059580207,0.00014525026,0.00021833277,0.00081150717,0.00023298222,0.0006412604,0.00033100543,0.0006039002,0.000026173886],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045512337,0.00028335283,0.33620015,0.0000019994006,0.0000026226057,0.000034873712,0.00021473863,0.00025326558,0.0003448673,0.00005740661,0.00026673378,0.66188484],"study_design_scores_gemma":[0.002306911,0.002585849,0.9012395,0.0047700517,0.00007737722,0.00018042649,0.001210247,0.00096665137,0.000686003,0.08404859,0.0014699824,0.00045837878],"about_ca_topic_score_codex":0.0000970184,"about_ca_topic_score_gemma":0.00038659395,"teacher_disagreement_score":0.6614265,"about_ca_system_score_codex":0.00016594099,"about_ca_system_score_gemma":0.00010575041,"threshold_uncertainty_score":0.71327376},"labels":[],"label_agreement":null},{"id":"W2497821641","doi":"10.1257/jel.20191074","title":"Measuring Time Preferences","year":2020,"lang":"en","type":"article","venue":"Journal of Economic Literature","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":342,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Quest University Canada","funders":"National Institute on Aging; National Institutes of Health","keywords":"Economics; Econometrics","score_opus":0.21924297714334431,"score_gpt":0.35869804835454944,"score_spread":0.13945507121120512,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2497821641","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99048525,0.00071723614,0.00008033329,0.0028400943,0.00096080615,0.000046745197,0.00002845357,0.000011216948,0.004829845],"genre_scores_gemma":[0.99642426,0.000028603507,0.0013699037,0.000702859,0.0010065723,3.871342e-7,0.0000011409396,0.000011041699,0.00045524916],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9978883,0.000098174394,0.0012287277,0.0002805362,0.0003386857,0.00016552495],"domain_scores_gemma":[0.9977612,0.0004594363,0.0009846863,0.0002566509,0.00026326513,0.00027477328],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0015614458,0.00014909527,0.00051047973,0.00021794684,0.000064918466,0.0010892814,0.0010874307,0.00011793875,0.0012127982],"category_scores_gemma":[0.00094688614,0.000099589124,0.0003091875,0.00020040103,0.000035522797,0.001139407,0.00010134114,0.00038792266,0.0014129729],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006747645,0.00012458429,0.016002145,0.000014369296,0.00015170574,0.00028648056,0.008168517,0.0053275344,0.0030100937,0.00082845724,0.26956663,0.6958447],"study_design_scores_gemma":[0.0027576704,0.0015178969,0.0073460266,0.0005236446,0.000120111516,0.0010070838,0.001169503,0.009468748,0.0026615623,0.3430354,0.62927675,0.0011156134],"about_ca_topic_score_codex":5.9080054e-7,"about_ca_topic_score_gemma":0.0000010364446,"teacher_disagreement_score":0.69472915,"about_ca_system_score_codex":0.000068184985,"about_ca_system_score_gemma":0.00015771721,"threshold_uncertainty_score":0.99994767},"labels":[],"label_agreement":null},{"id":"W2507592882","doi":"10.1080/17470218.2016.1220608","title":"The Role of Memory in Distinguishing Risky Decisions from Experience and Description","year":2016,"lang":"en","type":"article","venue":"Quarterly Journal of Experimental Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":61,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Alberta Gambling Research Institute, University of Calgary; Natural Sciences and Engineering Research Council of Canada","keywords":"Psychology; Preference; Social psychology; Cognitive psychology; Contrast (vision); Computer science; Economics; Artificial intelligence","score_opus":0.09820338050898196,"score_gpt":0.42284477524123165,"score_spread":0.3246413947322497,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2507592882","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9951855,0.0019139932,0.00076888036,0.000247969,0.0011435896,0.00005820632,0.000007674626,0.0000033653798,0.0006708445],"genre_scores_gemma":[0.99871355,0.000053351938,0.0010603092,0.00005131765,0.00008968762,0.000003204235,1.4651188e-7,0.000007864796,0.000020568323],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9974626,0.00025190625,0.0013412948,0.00029750433,0.0004479402,0.00019880716],"domain_scores_gemma":[0.99636185,0.0021161397,0.00085138937,0.00041579225,0.00014420296,0.00011060075],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016131705,0.00012271237,0.00034568048,0.00022384708,0.000118704505,0.00013867742,0.0007755173,0.00008485029,0.00010278108],"category_scores_gemma":[0.0008906885,0.00006324907,0.00011402823,0.00016444939,0.00035484234,0.0005345736,0.000052278116,0.00014519479,0.00002136804],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026931992,0.0001252744,0.018742431,4.5113985e-8,0.0000052530886,0.000015410738,0.005362306,5.4899385e-7,0.16342664,0.00012110455,0.00021425557,0.8117174],"study_design_scores_gemma":[0.004525223,0.0036941175,0.20392933,0.00033320964,0.000019383402,0.00046773104,0.12205543,0.00011754027,0.03437473,0.621723,0.008316336,0.00044396557],"about_ca_topic_score_codex":0.000060257094,"about_ca_topic_score_gemma":0.000042084364,"teacher_disagreement_score":0.81127346,"about_ca_system_score_codex":0.000050224065,"about_ca_system_score_gemma":0.000024697065,"threshold_uncertainty_score":0.25792223},"labels":[],"label_agreement":null},{"id":"W2509303870","doi":"10.1007/s40614-016-0070-9","title":"Automating Scoring of Delay Discounting for the 21- and 27-Item Monetary Choice Questionnaires","year":2016,"lang":"en","type":"article","venue":"The Behavior Analyst","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":221,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Delay discounting; Discounting; Psychology; Computer science; Actuarial science; Information retrieval; Econometrics; Economics; Finance","score_opus":0.1248767971500037,"score_gpt":0.4031964225730444,"score_spread":0.2783196254230407,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2509303870","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99341923,0.0003693885,0.004676789,0.0006831653,0.00039745728,0.0003341339,0.000036417357,0.000034795194,0.00004859642],"genre_scores_gemma":[0.998653,0.00002185519,0.0006745484,0.0000346928,0.0001269122,0.00005815619,0.0000011006036,0.00001615946,0.00041355373],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9978689,0.00011480708,0.0008416365,0.00038856632,0.0005357546,0.00025034224],"domain_scores_gemma":[0.99166685,0.006710062,0.00055878307,0.0007867196,0.00021689603,0.00006065988],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034769694,0.00016465681,0.00032820716,0.00015460723,0.00050519157,0.0002659106,0.00088676537,0.00005889742,0.00005138366],"category_scores_gemma":[0.0024435564,0.00006685248,0.00020546459,0.00033884292,0.00027315452,0.00039290625,0.00022353065,0.00009702849,0.00002263794],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013767498,0.0000292862,0.30817345,0.0000026634568,0.000015722837,0.000001471119,0.00019725965,0.00009248805,0.0032788904,0.000116623,0.00023411842,0.6878443],"study_design_scores_gemma":[0.00057720294,0.00009426659,0.9771618,0.00029338713,0.00066617463,0.000036985864,0.0011765865,0.011044555,0.001287843,0.0061188615,0.0012154746,0.00032685802],"about_ca_topic_score_codex":0.00045420742,"about_ca_topic_score_gemma":0.00041588448,"teacher_disagreement_score":0.6875174,"about_ca_system_score_codex":0.000036007776,"about_ca_system_score_gemma":0.00003536462,"threshold_uncertainty_score":0.38855764},"labels":[],"label_agreement":null},{"id":"W2514022131","doi":"10.1177/0956797616660292","title":"Overcorrection for Social-Categorization Information Moderates Impact Bias in Affective Forecasting","year":2016,"lang":"en","type":"article","venue":"Psychological Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Quest University Canada","funders":"","keywords":"Psychology; Categorization; Social psychology; Plural; Contrast (vision); Cognitive psychology; Artificial intelligence","score_opus":0.40417393064927354,"score_gpt":0.5095409729379052,"score_spread":0.1053670422886317,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2514022131","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8680869,0.0000021255773,0.12905361,0.00037078833,0.0005623659,0.0002553481,0.000013990848,0.00003426653,0.0016206213],"genre_scores_gemma":[0.9989188,0.0000025739723,0.0008422946,0.00011111067,0.00005564926,0.00003476441,0.0000016167837,0.0000031687825,0.000030027517],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9979493,0.00008012978,0.0005429081,0.00049130927,0.00057689735,0.0003594611],"domain_scores_gemma":[0.99758124,0.0014264376,0.00031849623,0.00020097879,0.00038691907,0.000085947395],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0050559025,0.00012059314,0.00019462025,0.00043415284,0.00037601372,0.0005165968,0.00053378573,0.00010232722,0.00011104616],"category_scores_gemma":[0.00941455,0.000061034963,0.0001028437,0.0015564944,0.0002603469,0.0028149984,0.000074600364,0.000074679025,0.0001411357],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007827911,0.000053173222,0.01341495,2.7537152e-7,5.1354635e-7,2.9393104e-7,0.00026926605,0.00041904842,0.0018317696,0.0005136865,0.00035223176,0.9830665],"study_design_scores_gemma":[0.0010326466,0.0006039671,0.42805833,0.000026686892,0.0000037412299,0.000017902623,0.0004096755,0.048343267,0.00101018,0.51941013,0.0007613406,0.00032215755],"about_ca_topic_score_codex":0.00002507253,"about_ca_topic_score_gemma":0.000018473418,"teacher_disagreement_score":0.98274434,"about_ca_system_score_codex":0.0002855514,"about_ca_system_score_gemma":0.000051071675,"threshold_uncertainty_score":0.99892956},"labels":[],"label_agreement":null},{"id":"W2516226452","doi":"10.2139/ssrn.2819538","title":"Revisiting Risk Aversion and Incentive Effects","year":2016,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Incentive; Risk aversion (psychology); Economics; Inequity aversion; Business; Actuarial science; Microeconomics; Financial economics; Expected utility hypothesis; Mathematics","score_opus":0.023165262412725034,"score_gpt":0.3248897808150281,"score_spread":0.3017245184023031,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2516226452","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97221875,0.0010131024,0.025338307,0.00059261767,0.00034106773,0.000069119895,0.0000030634662,0.000016934117,0.0004070549],"genre_scores_gemma":[0.9950325,0.0035954542,0.00029255147,0.00004973604,0.00023689649,8.9659926e-7,1.398695e-7,0.0000113791975,0.00078043237],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9971832,0.0002932874,0.00046614482,0.00036809247,0.0005190242,0.0011702727],"domain_scores_gemma":[0.99726266,0.001701477,0.00049033895,0.00025505936,0.00016048504,0.00013000745],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0073127304,0.00013736298,0.00025256752,0.00021821371,0.00040835488,0.00024775634,0.00043287664,0.00007498644,0.000065897715],"category_scores_gemma":[0.0029151163,0.000074790914,0.0001275488,0.00020674335,0.00007716809,0.00053169456,0.00014658293,0.0007336855,0.00037303616],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004093702,0.000009939735,0.024572294,4.4963545e-7,0.0000135732935,0.0000058665155,0.000045515404,0.0000017841729,0.00031440577,0.0030896722,0.0001100919,0.9717955],"study_design_scores_gemma":[0.00087235984,0.00022431342,0.0073705246,0.00009708097,0.000030304707,0.00019036178,0.0006590591,0.00006460288,0.00015284689,0.9859978,0.004176779,0.00016394228],"about_ca_topic_score_codex":0.000014548915,"about_ca_topic_score_gemma":0.00003950323,"teacher_disagreement_score":0.9829081,"about_ca_system_score_codex":0.000506138,"about_ca_system_score_gemma":0.00037564512,"threshold_uncertainty_score":0.47947496},"labels":[],"label_agreement":null},{"id":"W2518772759","doi":"10.1002/cb.1602","title":"Prey positions as consumers' behavioural patterns: Exploratory evidence from an<i>f</i>MRI study","year":2016,"lang":"en","type":"article","venue":"Journal of Consumer Behaviour","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Sainte-Anne","funders":"","keywords":"Predation; Position (finance); Predator; Exploratory research; Economics; Psychology; Ecology; Biology; Sociology; Finance","score_opus":0.19337469025723347,"score_gpt":0.4288435930485069,"score_spread":0.23546890279127342,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2518772759","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.993467,0.0006749963,0.0020319251,0.00078925386,0.0022897022,0.00040350851,0.00027572128,0.000048066544,0.000019872541],"genre_scores_gemma":[0.99836904,0.00018868891,0.00083056814,0.00021624866,0.0001411707,0.0000214842,0.0000031306406,0.00005046233,0.00017921082],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99246734,0.0010308645,0.0027995424,0.0008412366,0.0023403834,0.00052060036],"domain_scores_gemma":[0.99091405,0.0027887584,0.002072696,0.0015227715,0.001939757,0.00076196034],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0040919795,0.00045940367,0.0010032458,0.00075983687,0.00032141578,0.00077276706,0.0022164432,0.00021655987,0.0027652876],"category_scores_gemma":[0.0015938497,0.00028875808,0.00051488687,0.00039990075,0.00026664592,0.0039055268,0.00030099586,0.0005395455,0.0011341133],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023703008,0.0011260938,0.8979089,5.387128e-7,0.0000548423,0.00053990923,0.0013030244,0.0000025000131,0.001445137,0.0000033608337,0.0015319958,0.09584663],"study_design_scores_gemma":[0.0028106575,0.0018851586,0.9790863,0.0005717681,0.000796407,0.00046188384,0.00739817,0.000006482801,0.0017723404,0.003936234,0.00057972624,0.00069491874],"about_ca_topic_score_codex":0.00046091023,"about_ca_topic_score_gemma":0.0007293182,"teacher_disagreement_score":0.09515171,"about_ca_system_score_codex":0.00022720685,"about_ca_system_score_gemma":0.00068932236,"threshold_uncertainty_score":0.9999564},"labels":[],"label_agreement":null},{"id":"W2519771210","doi":"","title":"Implicit conflict detection during decision making","year":2007,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"York University","keywords":"Judgement; Normative; Heuristic; Psychology; Dual process theory (moral psychology); Heuristics; Computer science; Process (computing); Epistemology; Social psychology; Artificial intelligence","score_opus":0.04811611547224001,"score_gpt":0.3239436281433746,"score_spread":0.2758275126711346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2519771210","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9697716,0.00009992801,0.012568478,0.00008651118,0.0007516463,0.00025714113,0.00046875468,0.00042878505,0.015567154],"genre_scores_gemma":[0.99662954,0.000006238706,0.0019212342,0.00038119362,0.00032698756,0.0000066350663,0.000028320912,0.000093471535,0.0006063845],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99464864,0.00007990972,0.0017820596,0.0011671582,0.0014525698,0.0008696752],"domain_scores_gemma":[0.9953119,0.0023463797,0.000543079,0.0011534214,0.0001584406,0.00048678758],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002273564,0.00044336976,0.000540685,0.0009833701,0.0005246113,0.0056289993,0.0015383607,0.00033599875,0.0012236018],"category_scores_gemma":[0.0033297974,0.00036572161,0.0004394579,0.0015393035,0.00012610965,0.006374737,0.0007358297,0.00066135917,0.011590957],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048609133,0.000103497216,0.087721474,0.000003976593,0.000011157135,0.00011452154,0.000027802667,0.00003735264,0.0014843524,0.00013783126,0.000567406,0.90930456],"study_design_scores_gemma":[0.0016274333,0.00024744874,0.24030098,0.0002867133,0.00003249967,0.00038204854,0.00037607222,0.00041663097,0.026077727,0.27524745,0.4534507,0.001554297],"about_ca_topic_score_codex":0.0000020915954,"about_ca_topic_score_gemma":0.00001032799,"teacher_disagreement_score":0.90775025,"about_ca_system_score_codex":0.00012630089,"about_ca_system_score_gemma":0.0000684163,"threshold_uncertainty_score":0.9998795},"labels":[],"label_agreement":null},{"id":"W2521607795","doi":"10.1002/jeab.221","title":"Syntax for calculation of discounting indices from the monetary choice questionnaire and probability discounting questionnaire","year":2016,"lang":"en","type":"article","venue":"Journal of the Experimental Analysis of Behavior","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":123,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; Homewood Research Institute; St. Joseph’s Healthcare Hamilton","funders":"National Institute on Drug Abuse; National Institutes of Health","keywords":"Discounting; Syntax; Delay discounting; Psychology; Computer science; Econometrics; Statistics; Natural language processing; Mathematics; Economics","score_opus":0.06276410873205995,"score_gpt":0.38243569543229355,"score_spread":0.3196715867002336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2521607795","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9970786,0.0007593551,0.0008594939,0.0007082431,0.00030979837,0.00021135202,0.00006664625,0.0000034758284,0.000003038265],"genre_scores_gemma":[0.9991577,0.0000073031933,0.00067549665,0.000020249578,0.00009969063,0.000010160014,0.0000016985086,0.000007973424,0.000019675732],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9969847,0.0001911927,0.0015349002,0.00027831263,0.0008775721,0.00013329966],"domain_scores_gemma":[0.99545884,0.0009889927,0.002612652,0.00048077808,0.00040081594,0.000057929174],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023456782,0.00015278827,0.00058529066,0.00022900251,0.00023974177,0.00012223561,0.0007755235,0.000072456816,0.000037310703],"category_scores_gemma":[0.001282894,0.00006497435,0.0006589067,0.0005118612,0.00035138975,0.0007450519,0.00019509901,0.000103689075,7.2233985e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000068382404,0.00023116759,0.9285955,0.0000019986664,0.00015604014,5.1003417e-7,0.00073929346,0.00025730705,0.03189085,0.00004147034,0.000042259595,0.03797523],"study_design_scores_gemma":[0.00037105408,0.00009565419,0.9769625,0.00028022428,0.0014992321,0.0000047420103,0.0011976009,0.00070031045,0.016352843,0.0024005987,0.000025399042,0.00010982417],"about_ca_topic_score_codex":0.0006971487,"about_ca_topic_score_gemma":0.00044262648,"teacher_disagreement_score":0.048367027,"about_ca_system_score_codex":0.000107428124,"about_ca_system_score_gemma":0.000055004068,"threshold_uncertainty_score":0.26495773},"labels":[],"label_agreement":null},{"id":"W2522022217","doi":"","title":"Issues in Reasoning about Iffy Propositions: Reasoning Times in the Syntactic-Semantic Counter-Example Prompted Probabilistic Thinking and Reasoning Engine","year":2006,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Vlaamse regering","keywords":"Semantic reasoner; Psychology of reasoning; Context (archaeology); Antecedent (behavioral psychology); Probabilistic logic; Relation (database); Computer science; Notation; Inference; Epistemology; Cognitive science; Artificial intelligence; Natural language processing; Psychology; Linguistics; Philosophy; Knowledge representation and reasoning; Model-based reasoning; Social psychology","score_opus":0.028542884892998943,"score_gpt":0.2890227040419,"score_spread":0.26047981914890106,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2522022217","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98916936,0.00088103133,0.00018769172,0.0010037743,0.00011603571,0.00079226046,0.00023321569,0.00020161952,0.0074149966],"genre_scores_gemma":[0.99388033,0.000020640153,0.005014096,0.000239805,0.00013471808,0.00007500446,0.0001820677,0.000070987175,0.00038233612],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.995078,0.00043608897,0.0014867815,0.0011192686,0.0011419482,0.0007379101],"domain_scores_gemma":[0.9963312,0.0022245005,0.00036489725,0.00084202905,0.00010832806,0.00012902668],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.003306405,0.00047092358,0.00066216465,0.000672207,0.00042935315,0.008076765,0.0012466707,0.0002221218,0.0001872176],"category_scores_gemma":[0.0045375577,0.00033623475,0.00014812981,0.0015610545,0.00021294376,0.0056820777,0.0004048599,0.00088009244,0.0003678461],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021873381,0.000742158,0.9425754,0.000060069084,0.000020198595,0.00041244295,0.0008821703,0.0010278785,0.00007351008,0.015402565,0.001509935,0.03707497],"study_design_scores_gemma":[0.0020646597,0.00035289454,0.33258814,0.0044665434,0.00008026733,0.0004956621,0.002061805,0.02673511,0.00032506578,0.5752764,0.053729933,0.0018235493],"about_ca_topic_score_codex":0.0002799403,"about_ca_topic_score_gemma":0.00013699455,"teacher_disagreement_score":0.60998726,"about_ca_system_score_codex":0.00011419461,"about_ca_system_score_gemma":0.00014463624,"threshold_uncertainty_score":0.999909},"labels":[],"label_agreement":null},{"id":"W2523751968","doi":"10.1007/s40473-016-0091-4","title":"Age-Related Changes in Decision Making","year":2016,"lang":"en","type":"article","venue":"Current Behavioral Neuroscience Reports","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":28,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada; Ontario Ministry of Research, Innovation and Science; Canada Research Chairs","keywords":"Cognition; Gratification; Valuation (finance); Social decision making; Temporal discounting; Psychology; Fluid and crystallized intelligence; Cognitive psychology; Gerontology; Developmental psychology; Medicine; Fluid intelligence; Social psychology; Impulsivity; Economics; Working memory; Neuroscience; Finance","score_opus":0.21978105729145067,"score_gpt":0.46111105725226886,"score_spread":0.2413299999608182,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2523751968","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9883472,0.00013300491,0.0008893914,0.00034156805,0.00961037,0.00034200778,0.000013104722,0.0001200821,0.0002033089],"genre_scores_gemma":[0.99917305,0.00007182394,0.00027405718,0.000073501586,0.00005949711,0.000030330844,0.0000011386786,0.000028260949,0.0002883261],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9930528,0.00017390918,0.0018988405,0.0019391703,0.0021086787,0.0008266098],"domain_scores_gemma":[0.99630344,0.00063837896,0.0009710125,0.0015724186,0.00021952475,0.0002952291],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0037231646,0.00037135667,0.00058639236,0.0011322813,0.00025229994,0.00059571373,0.0012321385,0.00015553663,0.00036396176],"category_scores_gemma":[0.003329845,0.00022983392,0.00022436048,0.0020572129,0.0005227836,0.0010467601,0.0006289888,0.00031155228,0.0002128528],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013027463,0.00024124538,0.1315216,6.847637e-7,1.4847112e-7,0.0013813379,0.00006511873,0.000024000328,0.008339426,0.000027970525,0.00053029595,0.85785514],"study_design_scores_gemma":[0.0011115209,0.00060559274,0.7189625,0.0014961322,0.00004250718,0.00207686,0.00015282661,0.0004189253,0.0025096368,0.17672804,0.09420223,0.0016932597],"about_ca_topic_score_codex":0.000013194637,"about_ca_topic_score_gemma":0.00018327909,"teacher_disagreement_score":0.8561619,"about_ca_system_score_codex":0.00021007002,"about_ca_system_score_gemma":0.00015775757,"threshold_uncertainty_score":0.93723553},"labels":[],"label_agreement":null},{"id":"W2524837122","doi":"10.1037/lhb0000219","title":"Fair lineups are better than biased lineups and showups, but not because they increase underlying discriminability.","year":2016,"lang":"en","type":"article","venue":"Law and Human Behavior","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":73,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Psychology; Receiver operating characteristic; Cognitive psychology; Response bias; Social psychology; Statistics; Mathematics","score_opus":0.20282528885544238,"score_gpt":0.39262399924833863,"score_spread":0.18979871039289625,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2524837122","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9974229,0.000032308664,0.000057456862,0.0011871895,0.00025746855,0.00034301946,0.00027332632,0.00009736914,0.00032898763],"genre_scores_gemma":[0.9970401,0.000010114175,0.00025803677,0.0008186941,0.00015317451,0.00005347285,0.000010269656,0.00004098918,0.0016151551],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99672425,0.00018394872,0.00089479884,0.0011164725,0.0006137742,0.0004667708],"domain_scores_gemma":[0.9970379,0.0009290905,0.0003406962,0.0010927411,0.00019731224,0.0004022634],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012410268,0.00038527095,0.0006034204,0.00021939432,0.00070607936,0.0008391213,0.00059680175,0.00021790045,0.0003305309],"category_scores_gemma":[0.0003003748,0.00023514687,0.00017940364,0.00010238002,0.00055609184,0.0007140349,0.00043147415,0.0002342986,0.00009538571],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018396962,0.0007259486,0.66759574,0.000018592402,0.000018005163,0.00024099254,0.00077309855,7.7439125e-7,0.020604625,0.008542583,0.0007291426,0.30056655],"study_design_scores_gemma":[0.0022020836,0.00046841343,0.9267458,0.00021926154,0.00031385117,0.00008644763,0.0013982437,0.000014526544,0.0023017642,0.057351682,0.00783036,0.0010676074],"about_ca_topic_score_codex":0.0011384176,"about_ca_topic_score_gemma":0.0064514466,"teacher_disagreement_score":0.29949895,"about_ca_system_score_codex":0.000059984217,"about_ca_system_score_gemma":0.000035689536,"threshold_uncertainty_score":0.9589011},"labels":[],"label_agreement":null},{"id":"W2525468836","doi":"10.1111/caje.12272","title":"Applying behavioural economics to public policy in Canada","year":2017,"lang":"en","type":"article","venue":"Canadian Journal of Economics/Revue canadienne d économique","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Behavioural economics; Behavioral economics; Government (linguistics); Public policy; Public economics; Field (mathematics); Economics; Behavioural sciences; Point (geometry); Positive economics; Term (time); Sociology; Social science; Economic growth; Microeconomics","score_opus":0.39801464866439673,"score_gpt":0.2939995836760854,"score_spread":0.10401506498831131,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2525468836","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9810196,0.000051912582,0.000020903808,0.012690552,0.0037192074,0.00044406846,0.00038651668,0.0000037679722,0.0016634812],"genre_scores_gemma":[0.99637884,0.000038284656,0.00051647733,0.0019489904,0.0006487571,0.000042805284,0.00000555637,0.00006726427,0.00035303194],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9948697,0.00010564472,0.0026522188,0.0008306176,0.000014143113,0.001527692],"domain_scores_gemma":[0.9902449,0.00052406604,0.002233574,0.001940667,0.00043155774,0.0046251956],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0032265084,0.0004617268,0.0013161423,0.002790905,0.000725542,0.0022310626,0.004734302,0.00022837849,0.00038902985],"category_scores_gemma":[0.004492949,0.0005176339,0.00034580668,0.00026169885,0.00020323881,0.0017622921,0.0002008978,0.0006166866,0.00010476193],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":true,"study_design_scores_codex":[0.00006582049,0.000018196646,0.5040379,0.000004342755,0.000046177494,0.00052914076,0.00048607012,0.01222946,0.000004118084,0.065863736,0.002289159,0.41442585],"study_design_scores_gemma":[0.0018611442,0.0003386864,0.13896978,0.00013557715,0.000037892412,0.0011177585,0.0027892536,0.003522213,0.00007240938,0.6489805,0.20051381,0.0016609952],"about_ca_topic_score_codex":0.9964626,"about_ca_topic_score_gemma":0.99999493,"teacher_disagreement_score":0.58311677,"about_ca_system_score_codex":0.015340846,"about_ca_system_score_gemma":0.036306378,"threshold_uncertainty_score":0.99972755},"labels":[],"label_agreement":null},{"id":"W2529127485","doi":"","title":"A Comparison of Survey and Incentivized-Based Risk Attitude Elicitation","year":2016,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Loss aversion; Survey data collection; Risk aversion (psychology); Dimension (graph theory); Contrast (vision); Survey instrument; Actuarial science; Sample (material); Order (exchange); Survey research; Economics; Psychology; Marketing; Business; Expected utility hypothesis; Microeconomics; Computer science; Financial economics; Applied psychology; Statistics; Finance; Mathematics","score_opus":0.26478450062057535,"score_gpt":0.49810771106326446,"score_spread":0.2333232104426891,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2529127485","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9928365,0.00013120579,0.00019281321,0.00012951862,0.0005507807,0.0005361949,0.000549979,0.000018780436,0.0050542303],"genre_scores_gemma":[0.9975525,0.0009342353,0.0010865706,0.00001815808,0.0000600935,0.000050130548,0.000039339266,0.00003808694,0.00022085913],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99313194,0.0018478897,0.0021094715,0.0014513527,0.0008789409,0.0005803855],"domain_scores_gemma":[0.9827203,0.01343314,0.0013094052,0.0016448168,0.0006726008,0.00021970987],"candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.019196482,0.0003313302,0.0012537696,0.0013345846,0.0001852065,0.00043274008,0.0014738282,0.00051783805,0.00012606503],"category_scores_gemma":[0.009456538,0.00027171892,0.00022805191,0.00030010636,0.0007084679,0.00018801009,0.0014477068,0.0011685765,0.0000454581],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015896976,0.00013474339,0.4657134,0.000011253457,0.000014885287,0.0000017794337,0.00012429092,0.0016857681,0.000039188682,0.00001637515,0.00009233623,0.532007],"study_design_scores_gemma":[0.0017637225,0.00027858955,0.8640975,0.00045840506,0.000018528686,0.0000016233216,0.0006373296,0.06311684,0.000445399,0.062411875,0.006059145,0.00071106094],"about_ca_topic_score_codex":0.0004204324,"about_ca_topic_score_gemma":0.0030158944,"teacher_disagreement_score":0.5312959,"about_ca_system_score_codex":0.0005010861,"about_ca_system_score_gemma":0.0007217967,"threshold_uncertainty_score":0.9999735},"labels":[],"label_agreement":null},{"id":"W2529875532","doi":"10.1007/s40881-016-0028-4","title":"Simulating power of economic experiments: the powerBBK package","year":2016,"lang":"en","type":"article","venue":"Journal of the Economic Science Association","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":41,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"R package; Computer science; Statistical power; Nonparametric statistics; Power (physics); Binary number; Sample (material); Sample size determination; Parametric statistics; Design of experiments; Statistics; Mathematics; Programming language; Arithmetic","score_opus":0.0701657254449491,"score_gpt":0.3999832397105319,"score_spread":0.3298175142655828,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2529875532","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9900738,0.000026331469,0.0001305094,0.0035218745,0.004405742,0.00008824971,0.000014075085,0.0000038031453,0.0017356152],"genre_scores_gemma":[0.99883157,0.000008098342,0.00017811281,0.00014405666,0.00014185376,7.8872813e-7,2.984615e-8,0.000007382232,0.0006880848],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99701625,0.00017181186,0.001503376,0.00026588663,0.00076635997,0.0002763259],"domain_scores_gemma":[0.9917915,0.002662499,0.0044797105,0.000668571,0.00031514594,0.000082587896],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0144469235,0.0001171998,0.0003443444,0.00024825113,0.00033922493,0.00036396578,0.0025590728,0.00006911344,0.0004548065],"category_scores_gemma":[0.0054028253,0.000050728395,0.00034092835,0.00022870845,0.00029032497,0.0015718675,0.0002964342,0.00013409335,0.0003074697],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019063732,0.0001963966,0.59849954,0.000001483588,0.00015815887,0.000002995078,0.006582078,0.023781622,0.07858515,0.0049794093,0.036535323,0.25048718],"study_design_scores_gemma":[0.004603321,0.0007606058,0.45899686,0.00034857736,0.00014488373,0.00010318484,0.01162669,0.009990905,0.11032167,0.37449473,0.027578216,0.0010303621],"about_ca_topic_score_codex":0.000016434704,"about_ca_topic_score_gemma":0.000016353524,"teacher_disagreement_score":0.3695153,"about_ca_system_score_codex":0.0025775686,"about_ca_system_score_gemma":0.0007035027,"threshold_uncertainty_score":0.67402524},"labels":[],"label_agreement":null},{"id":"W2530427207","doi":"10.1037/xap0000103","title":"Where are you? The effect of uncertainty and its visual representation on location judgments in GPS-like displays.","year":2016,"lang":"en","type":"article","venue":"Journal of Experimental Psychology Applied","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Glyph (data visualization); Visualization; Computer science; Global Positioning System; Task (project management); Consistency (knowledge bases); Representation (politics); Artificial intelligence; Function (biology); Data mining; Statistics; Mathematics","score_opus":0.07382892655086758,"score_gpt":0.45521778432738835,"score_spread":0.38138885777652076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2530427207","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99746,0.00033863238,0.00010076759,0.00066159386,0.0006220324,0.0002129167,0.0000035114651,0.0000029832108,0.0005975479],"genre_scores_gemma":[0.999635,0.00004210429,0.00002344286,0.00017236726,0.00005768107,0.000011618739,4.5224513e-7,0.00000825768,0.000049089853],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9980065,0.00023510825,0.00085277687,0.0003046651,0.00045991,0.00014099253],"domain_scores_gemma":[0.9977196,0.0009733707,0.00090063404,0.0002643538,0.00007908201,0.00006296688],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018185275,0.00013597184,0.00038317998,0.00023829137,0.00006245578,0.000037697515,0.0003832404,0.00010583312,0.000110584464],"category_scores_gemma":[0.00018890423,0.000065841785,0.000081427264,0.00024293295,0.0001349782,0.00018090794,0.000062261475,0.00014907608,0.000049616825],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.012394707,0.001197145,0.09256288,0.000008594267,0.00008322788,0.000048467133,0.0016440906,0.00093805074,0.49155086,0.00046779242,0.011299636,0.38780457],"study_design_scores_gemma":[0.03274566,0.012053969,0.4756652,0.0010265566,0.00011732713,0.00041102,0.01016686,0.00085946254,0.4446801,0.016964015,0.004347174,0.00096265745],"about_ca_topic_score_codex":0.0000031906277,"about_ca_topic_score_gemma":0.0000066829402,"teacher_disagreement_score":0.3868419,"about_ca_system_score_codex":0.00007343161,"about_ca_system_score_gemma":0.000013886381,"threshold_uncertainty_score":0.268495},"labels":[],"label_agreement":null},{"id":"W2552328639","doi":"10.1037/xhp0000295","title":"I saw mine first: A prior-entry effect for newly acquired ownership.","year":2016,"lang":"en","type":"article","venue":"Journal of Experimental Psychology Human Perception & Performance","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":39,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Psychology; Cognitive psychology; Construal level theory; Set (abstract data type); Perception; Task (project management); Salient; Prioritization; PsycINFO; Social psychology; Computer science; Artificial intelligence","score_opus":0.12476146052057435,"score_gpt":0.44907770091408916,"score_spread":0.3243162403935148,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2552328639","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99466777,0.00018121667,0.00080269313,0.0011148412,0.0020228056,0.00028942947,0.000009886458,0.000024278514,0.0008871],"genre_scores_gemma":[0.99541205,0.000066595014,0.001447258,0.00059876015,0.00070853235,0.000024334826,0.0000024446883,0.0000308828,0.0017091633],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99664146,0.00015351195,0.0015577631,0.0005437407,0.0006742359,0.0004293073],"domain_scores_gemma":[0.9972254,0.0005206213,0.0011223981,0.00061362615,0.0002870957,0.00023087562],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0025906174,0.0003020482,0.00064508815,0.0005220328,0.00043754894,0.00015483075,0.0010602998,0.0002283515,0.0027035146],"category_scores_gemma":[0.000250535,0.00017386656,0.0004843022,0.00020549966,0.00033869018,0.0011481759,0.00009506577,0.00016042312,0.000568137],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0030079605,0.00073684007,0.040451884,0.000008977585,0.000048883874,0.000017409997,0.0015235767,0.000023979863,0.50434613,0.00003652505,0.07594489,0.37385297],"study_design_scores_gemma":[0.043742545,0.0378534,0.6477795,0.0012315435,0.00022698691,0.002730095,0.0039315387,0.00059796765,0.0572416,0.008290157,0.19397281,0.0024018066],"about_ca_topic_score_codex":0.0000019033281,"about_ca_topic_score_gemma":0.0000056068134,"teacher_disagreement_score":0.60732764,"about_ca_system_score_codex":0.00025677617,"about_ca_system_score_gemma":0.000038556635,"threshold_uncertainty_score":0.99820817},"labels":[],"label_agreement":null},{"id":"W2565010868","doi":"10.5539/ijef.v9n1p32","title":"Risk Aversion and Emotions in DoND","year":2016,"lang":"en","type":"article","venue":"International Journal of Economics and Finance","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Risk aversion (psychology); Context (archaeology); Order (exchange); Reading (process); Face (sociological concept); Psychology; Cognition; Test (biology); Social psychology; Arrow; Cognitive psychology; Economics; Computer science; Expected utility hypothesis; Sociology; Financial economics; Political science; Finance","score_opus":0.05538877908435775,"score_gpt":0.33752805195733837,"score_spread":0.28213927287298063,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2565010868","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9953223,0.00010653563,0.00039478418,0.0030365426,0.00077238685,0.000018602397,0.000036416244,7.343418e-7,0.00031169388],"genre_scores_gemma":[0.9909225,0.0077312426,0.00097554986,0.00006767632,0.00008435585,2.1391278e-7,1.3413694e-7,0.0000031561153,0.00021514289],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9991485,0.000022543207,0.00050704816,0.00015637338,0.00009442555,0.00007110291],"domain_scores_gemma":[0.9987036,0.00047318335,0.00053167075,0.00009356665,0.00016302678,0.00003494254],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010250839,0.000059506954,0.00016160653,0.00027814176,0.000031074123,0.00013447579,0.00030931324,0.00003980284,0.00003501992],"category_scores_gemma":[0.00045534375,0.00003855724,0.00005253618,0.00003979499,0.00006744342,0.0004981765,0.000091152775,0.00007440808,0.00002372275],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000064101834,0.000028857441,0.033887524,1.14985326e-7,0.000007700117,0.000014741454,0.00008045006,0.0005285526,0.000029098306,0.0050733914,0.0005271176,0.95975834],"study_design_scores_gemma":[0.0017551751,0.00013509938,0.2397475,0.00009480148,0.0000070303017,0.0002452383,0.00013508009,0.0039402745,0.000077754106,0.58785886,0.16584498,0.00015820927],"about_ca_topic_score_codex":0.00001163567,"about_ca_topic_score_gemma":0.00006449263,"teacher_disagreement_score":0.95960015,"about_ca_system_score_codex":0.000055514196,"about_ca_system_score_gemma":0.00003554706,"threshold_uncertainty_score":0.15723185},"labels":[],"label_agreement":null},{"id":"W2566721998","doi":"10.3758/s13421-016-0680-1","title":"When fast logic meets slow belief: Evidence for a parallel-processing model of belief bias","year":2016,"lang":"en","type":"article","venue":"Memory & Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":92,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Max-Planck-Institut für Bildungsforschung; Max-Planck-Gesellschaft; University of Saskatchewan","keywords":"Syllogism; Psychology; Cognitive psychology; Converse; Deductive reasoning; Social psychology; Artificial intelligence; Computer science; Epistemology","score_opus":0.4927859558913508,"score_gpt":0.43612724901111766,"score_spread":0.05665870688023317,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2566721998","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.76266193,0.0002900914,0.23254749,0.0020114246,0.00027636244,0.00044352596,0.00012794486,0.0000699046,0.0015713054],"genre_scores_gemma":[0.9772819,0.000052812888,0.020551063,0.00041865298,0.000096515825,0.00006530379,0.0000072453927,0.000022760856,0.0015037342],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9969544,0.00011149414,0.0010289446,0.0007450933,0.00081861054,0.00034144984],"domain_scores_gemma":[0.995587,0.0021341052,0.00068554276,0.0005418253,0.00092366984,0.0001278437],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027470617,0.00022440832,0.0004601049,0.00031474006,0.00022690988,0.0001926004,0.0006720089,0.00015417693,0.00025105223],"category_scores_gemma":[0.0042095277,0.00014427547,0.00024502297,0.0002428439,0.00019215651,0.0011048482,0.00014443435,0.00008460495,0.00029389779],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024907617,0.00012177203,0.00014234222,0.000015864245,0.0000067359015,0.0000026105904,0.00031771924,0.0007654529,0.019586518,0.00013282643,0.0022570707,0.976402],"study_design_scores_gemma":[0.0022574367,0.00053656084,0.00090866967,0.0015515917,0.00016578234,0.000021896598,0.0006159454,0.04673519,0.013097506,0.931781,0.0016577772,0.0006706224],"about_ca_topic_score_codex":0.000008528769,"about_ca_topic_score_gemma":0.000033047305,"teacher_disagreement_score":0.9757314,"about_ca_system_score_codex":0.000065449676,"about_ca_system_score_gemma":0.00016526385,"threshold_uncertainty_score":0.5883383},"labels":[],"label_agreement":null},{"id":"W2566905302","doi":"10.1093/ije/dyw303","title":"Commentary: Delay discounting and smoking: robust correlation, but uncertain causation","year":2016,"lang":"en","type":"letter","venue":"International Journal of Epidemiology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; St. Joseph’s Healthcare Hamilton; Homewood Research Institute","funders":"Economic and Social Research Council; Medical Research Council; National Institute on Drug Abuse; British Heart Foundation; Cancer Research UK","keywords":"Causation; Delay discounting; Correlation; Discounting; Econometrics; Medicine; Psychology; Economics; Mathematics; Philosophy; Epistemology","score_opus":0.22101501544916968,"score_gpt":0.43657620373116784,"score_spread":0.21556118828199816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2566905302","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.042679902,0.0003922082,0.047385752,0.8996303,0.009310068,0.000092118025,0.0001635883,0.000010396768,0.00033567348],"genre_scores_gemma":[0.06590355,0.00043808483,0.006568301,0.909813,0.015861686,0.000005568626,0.00017530056,0.00005314684,0.0011813727],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99352586,0.0012181196,0.003278372,0.0005519459,0.0010509974,0.00037473178],"domain_scores_gemma":[0.9722463,0.020720862,0.0049676215,0.00036952956,0.00158684,0.00010885001],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01226342,0.0003096946,0.0010304465,0.0009689103,0.00012384552,0.00019702499,0.001572639,0.00067732355,0.0005880012],"category_scores_gemma":[0.01820505,0.0001995036,0.00034452742,0.00011326413,0.00032917465,0.00063669006,0.0002977363,0.001401248,0.00006556702],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000049696515,0.000011466737,0.036227804,0.0000013956769,0.00012218677,0.00027820343,0.000048830774,0.0010945476,0.000003842412,0.00020027482,0.82514924,0.13681252],"study_design_scores_gemma":[0.0004762936,0.00009214365,0.0021881263,0.00020149621,0.00005979074,0.001091506,0.000062289524,0.0012246573,0.0000018310614,0.14250606,0.8518825,0.00021330106],"about_ca_topic_score_codex":0.00015128955,"about_ca_topic_score_gemma":0.000022199341,"teacher_disagreement_score":0.14230579,"about_ca_system_score_codex":0.0004324531,"about_ca_system_score_gemma":0.0001486454,"threshold_uncertainty_score":0.99006504},"labels":[],"label_agreement":null},{"id":"W2567193265","doi":"10.32469/10355/48706","title":"A new measure of economic voting : priority heuristic theory and combining sociotropic and egocentric evaluations","year":2015,"lang":"en","type":"dissertation","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Voting; Ideology; Positive economics; Construct (python library); Dimension (graph theory); Scale (ratio); Economics; Public economics; Politics; Microeconomics; Computer science; Political science","score_opus":0.11540770507840299,"score_gpt":0.44780017047485926,"score_spread":0.3323924653964563,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2567193265","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99104434,0.0017179265,0.0008805876,0.000053481195,0.0009164405,0.0002654166,0.000028179236,0.00002784009,0.0050657624],"genre_scores_gemma":[0.99363697,0.000055286037,0.00135694,0.000017161683,0.000080359954,0.000003848125,0.00004160516,0.000023367833,0.004784464],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9970548,0.0003344912,0.0010838389,0.0006545416,0.000664918,0.0002073923],"domain_scores_gemma":[0.995753,0.0023209844,0.00088040205,0.00038446684,0.00043981004,0.00022134029],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00556073,0.00025919752,0.0007133775,0.00043768738,0.00018917218,0.00034173473,0.00039878782,0.00028092545,0.00042294466],"category_scores_gemma":[0.004373397,0.00021267188,0.00011033673,0.00018560703,0.000070164846,0.00024024732,0.00010259208,0.00028584205,0.00009501551],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000101809885,0.00002867486,0.009574615,0.000017360246,0.000031496507,0.0000016708407,0.0018963903,0.000048298087,0.000028287728,0.008269646,0.0032998663,0.97670186],"study_design_scores_gemma":[0.0015644514,0.0002010114,0.06554463,0.00023546009,0.00040166083,0.000019541098,0.011139541,0.003911846,0.00004133029,0.91546226,0.00085788604,0.0006203614],"about_ca_topic_score_codex":0.00015951386,"about_ca_topic_score_gemma":0.00071267085,"teacher_disagreement_score":0.97608155,"about_ca_system_score_codex":0.00013737827,"about_ca_system_score_gemma":0.0009652329,"threshold_uncertainty_score":0.86725074},"labels":[],"label_agreement":null},{"id":"W2570591202","doi":"10.1509/jmr.15.0277","title":"Seller Beware: How Bundling Affects Valuation","year":2017,"lang":"en","type":"article","venue":"Journal of Marketing Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":37,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Booth University College","funders":"","keywords":"Valuation (finance); Bundle; Gestalt psychology; Psychology; Microeconomics; Business; Social psychology; Perception; Marketing; Economics","score_opus":0.5843134779325335,"score_gpt":0.5673092169627209,"score_spread":0.017004260969812668,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2570591202","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9863304,0.00012659101,0.00042694525,0.006808351,0.0010638373,0.00010928393,0.0000016468972,0.0000063593607,0.0051265773],"genre_scores_gemma":[0.99493283,0.00008006661,0.0016083702,0.000023807743,0.0006197592,0.0000014312658,1.9558459e-7,0.000015930682,0.0027175986],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99207705,0.0024405767,0.0006855603,0.0003398495,0.003954531,0.0005024328],"domain_scores_gemma":[0.97718644,0.017364092,0.001367878,0.0010191974,0.0028281207,0.00023425712],"candidate_categories":["metaresearch","sts","scholarly_communication"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.18024287,0.000115352894,0.00036504216,0.0007874623,0.0013621184,0.0037403544,0.0023839183,0.000102601814,0.0003117149],"category_scores_gemma":[0.16223383,0.00008085715,0.00022835331,0.0002898972,0.00021310594,0.0010372975,0.00054237526,0.00095161254,0.00015953218],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005096624,0.00007823361,0.046679214,0.0000062380564,0.000016799982,0.000109784625,0.00019464183,0.00010574043,0.0010570897,0.00003278816,0.042571567,0.90863824],"study_design_scores_gemma":[0.0026937623,0.0010102106,0.642108,0.0011643561,0.000052092055,0.00050664315,0.004888393,0.011749212,0.0014161872,0.16262154,0.17118813,0.0006014404],"about_ca_topic_score_codex":0.000010622515,"about_ca_topic_score_gemma":0.000017722172,"teacher_disagreement_score":0.9080368,"about_ca_system_score_codex":0.00017694588,"about_ca_system_score_gemma":0.0003791897,"threshold_uncertainty_score":0.99993795},"labels":[],"label_agreement":null},{"id":"W2572242965","doi":"","title":"Explicit Bayesian Reasoning with Frequencies, Probabilities, and Surprisals","year":2011,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Prior probability; Bayes' theorem; Bayesian probability; Conditional probability; Bayes factor; Posterior probability; Bayesian inference; Frequentist probability; Statistics; Bayesian statistics; Prime (order theory); Mathematics; Marginal likelihood; Psychology; Econometrics; Combinatorics","score_opus":0.07400849366733225,"score_gpt":0.27318333325891253,"score_spread":0.19917483959158028,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2572242965","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94426346,0.00017208495,0.0007804688,0.00016673472,0.000110790796,0.000292536,0.0008302497,0.00027637786,0.053107314],"genre_scores_gemma":[0.9866104,0.000009281597,0.011305978,0.00033990582,0.000065463275,0.000026921694,0.00005361053,0.000074869706,0.0015135729],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9964299,0.00013710563,0.00095851324,0.0010453345,0.0008427731,0.0005863612],"domain_scores_gemma":[0.9972479,0.00072538276,0.0003496333,0.0010194045,0.00011883403,0.0005388456],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0010903125,0.00040160294,0.0005357041,0.00033162825,0.0002645705,0.0036893275,0.0011064936,0.00018929584,0.00150545],"category_scores_gemma":[0.0015672831,0.0002796279,0.00014076961,0.0007417212,0.00029197076,0.007056711,0.0004372292,0.0004130861,0.001321464],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023667133,0.0001914478,0.800419,0.00001038837,0.000023620867,0.00011085409,0.00037509386,0.0000023564567,0.000023635399,0.006372282,0.0022247725,0.19000992],"study_design_scores_gemma":[0.00094837765,0.00060207205,0.051854745,0.0002772436,0.000038171715,0.0002444724,0.0014835298,0.00014531518,0.0014427428,0.7512561,0.19032802,0.0013791781],"about_ca_topic_score_codex":0.000023429428,"about_ca_topic_score_gemma":0.0000141210685,"teacher_disagreement_score":0.7485642,"about_ca_system_score_codex":0.00004215945,"about_ca_system_score_gemma":0.00020652624,"threshold_uncertainty_score":0.9999656},"labels":[],"label_agreement":null},{"id":"W2580805489","doi":"10.19041/apstract/2016/2-3/1","title":"Some uses, underuses, and misuses of the findings of disparities between people’s valuations of gains and losses","year":2016,"lang":"en","type":"article","venue":"Applied Studies in Agribusiness and Commerce","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Value (mathematics); Economics; Econometrics; Psychology; Actuarial science; Statistics; Mathematics","score_opus":0.28973642566281477,"score_gpt":0.4267223325905648,"score_spread":0.13698590692775003,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2580805489","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99653655,0.0016176599,0.00010869432,0.0013463384,0.00008293279,0.00014862779,0.00008923129,0.000003926854,0.00006605685],"genre_scores_gemma":[0.99741304,0.0023583733,0.00011003975,0.00004742137,0.000017991499,0.000008044535,5.8734156e-7,0.0000057799357,0.000038717393],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986189,0.000053819545,0.0006386204,0.0002534824,0.00030000132,0.00013519653],"domain_scores_gemma":[0.9954306,0.0037382997,0.0003056466,0.0003013817,0.00019674329,0.000027315591],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008105012,0.00013247546,0.00058613194,0.0001281008,0.00012866929,0.000029135426,0.0002751355,0.00005464255,0.000004534012],"category_scores_gemma":[0.0006983612,0.000067567315,0.000035996145,0.00033934542,0.0010064975,0.00014421035,0.00057657313,0.00005337635,4.4641084e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022013637,0.000051753173,0.9316914,0.000053313997,0.000034225937,1.516689e-7,0.0010349479,0.0000069479624,0.0003862402,0.016307268,0.00035637603,0.05005534],"study_design_scores_gemma":[0.00042717368,0.000024058607,0.89866054,0.00017333252,0.000044983848,0.0000012421556,0.0030658233,0.0000033960175,0.00043796914,0.09684432,0.00022165611,0.00009549907],"about_ca_topic_score_codex":0.00018423233,"about_ca_topic_score_gemma":0.00056278636,"teacher_disagreement_score":0.08053706,"about_ca_system_score_codex":0.000014114625,"about_ca_system_score_gemma":0.000029599225,"threshold_uncertainty_score":0.3708482},"labels":[],"label_agreement":null},{"id":"W2586922569","doi":"","title":"Equivalence: A Novel Basis for Model Analysis","year":2007,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Task (project management); Equivalence (formal languages); Social psychology; Psychology; Cognition; Computer science; Cognitive psychology; Mathematical economics; Artificial intelligence; Mathematics; Engineering; Discrete mathematics","score_opus":0.11280445299712455,"score_gpt":0.35401476574929164,"score_spread":0.2412103127521671,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2586922569","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.732021,0.000049354454,0.24968116,0.000417478,0.00019055445,0.00028600055,0.0068672714,0.00021109487,0.010276097],"genre_scores_gemma":[0.96987975,0.0000031897182,0.02527594,0.00086598546,0.00013879778,0.000019545501,0.00021267607,0.00006527644,0.0035388463],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99511266,0.000033366156,0.0015992435,0.0011816147,0.0012495739,0.0008235729],"domain_scores_gemma":[0.9947555,0.0027379086,0.0004765872,0.0011958673,0.00023911532,0.0005949865],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0031061592,0.00039437378,0.00072083814,0.0013311007,0.0003035656,0.004284654,0.0019353658,0.00027559747,0.0007500705],"category_scores_gemma":[0.0041530035,0.00031474035,0.0010845226,0.0030003812,0.00015017451,0.005347062,0.0004941092,0.0003391904,0.0020806892],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010194664,0.0012118795,0.29979095,0.000018608378,0.00040479787,0.000040636965,0.00012998605,0.0075100544,0.0007663329,0.008357907,0.013531665,0.66721773],"study_design_scores_gemma":[0.0017180672,0.00028534862,0.012836925,0.000076810495,0.00058120186,0.000021180482,0.00041454917,0.108952984,0.0032381353,0.5973239,0.27262446,0.0019264292],"about_ca_topic_score_codex":0.0000018055595,"about_ca_topic_score_gemma":0.0000063360994,"teacher_disagreement_score":0.6652913,"about_ca_system_score_codex":0.00007362259,"about_ca_system_score_gemma":0.00017633267,"threshold_uncertainty_score":0.99993044},"labels":[],"label_agreement":null},{"id":"W2588156857","doi":"10.1037/xlm0000372","title":"Rule-based reasoning is fast and belief-based reasoning can be slow: Challenging current explanations of belief-bias and base-rate neglect.","year":2017,"lang":"en","type":"article","venue":"Journal of Experimental Psychology Learning Memory and Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":112,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Belief revision; Dual process theory (moral psychology); Neglect; Cognitive psychology; Analytic reasoning; Psychology; Psychology of reasoning; Dual (grammatical number); Verbal reasoning; Base (topology); False belief; Process (computing); Knowledge base; Reasoning system; Computer science; Artificial intelligence; Cognition; Mathematics; Theory of mind","score_opus":0.15385164640687782,"score_gpt":0.4257448882145097,"score_spread":0.27189324180763186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2588156857","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99376875,0.0021536308,0.0012692071,0.00125576,0.00045548473,0.00010486305,0.000018169087,0.000012409605,0.00096173625],"genre_scores_gemma":[0.9980968,0.00018872204,0.0011454335,0.0004068634,0.00009405701,0.000005844049,0.000008358822,0.000018311797,0.00003556133],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.997733,0.00035773974,0.000819299,0.00045443338,0.00039928243,0.00023625512],"domain_scores_gemma":[0.99701566,0.0006322567,0.0015865074,0.00028175703,0.0002844604,0.0001993828],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022419228,0.00022121586,0.0004772726,0.00046246158,0.0009920223,0.0003365327,0.00026767657,0.00013363485,0.000107799075],"category_scores_gemma":[0.0011317512,0.0001961219,0.00011787247,0.000100671336,0.00037223424,0.00048356157,0.00007764098,0.00051573635,0.0000030840354],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011215768,0.0008101353,0.03527855,0.00003198312,0.000098595905,0.00012043585,0.005227183,0.00074021815,0.07492024,0.00013048967,0.00079226604,0.8807283],"study_design_scores_gemma":[0.050006654,0.01403058,0.4636022,0.010098228,0.0012466948,0.002941495,0.073326774,0.07369333,0.2795924,0.018691914,0.008574893,0.004194854],"about_ca_topic_score_codex":0.000015467129,"about_ca_topic_score_gemma":0.000007338868,"teacher_disagreement_score":0.87653345,"about_ca_system_score_codex":0.000032767253,"about_ca_system_score_gemma":0.00006816093,"threshold_uncertainty_score":0.79976183},"labels":[],"label_agreement":null},{"id":"W2591092602","doi":"10.3758/s13423-017-1242-7","title":"Dunning–Kruger effects in reasoning: Theoretical implications of the failure to recognize incompetence","year":2017,"lang":"en","type":"article","venue":"Psychonomic Bulletin & Review","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":230,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Psychology; Cognitive psychology; Cognitive science","score_opus":0.06192809353097678,"score_gpt":0.41030064360943,"score_spread":0.34837255007845325,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2591092602","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.78331906,0.008561391,0.0006432442,0.1797468,0.0020470335,0.002607168,0.000034697052,0.000042065298,0.022998545],"genre_scores_gemma":[0.98539686,0.0016858397,0.008393236,0.003984178,0.00007869366,0.00014416584,8.884846e-7,0.000024645626,0.00029148225],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9969936,0.00033015088,0.0012780849,0.00075960474,0.00033036378,0.000308212],"domain_scores_gemma":[0.9939721,0.0015423131,0.0009266399,0.0031866117,0.00017818791,0.00019411127],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.004489049,0.00021940948,0.0007671303,0.00011416975,0.00029283183,0.0002619242,0.0034719892,0.0000967874,0.0015276991],"category_scores_gemma":[0.014094295,0.0001381231,0.00039183788,0.0002947458,0.00036927746,0.00008516807,0.000574472,0.00029562265,0.0020595698],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028142076,0.0001310279,0.024616752,0.00014626674,0.000009208172,0.0000021687188,0.00009398486,0.000011906677,0.00010202451,0.017311525,0.10249417,0.8550528],"study_design_scores_gemma":[0.0005245999,0.00007788647,0.22532323,0.0114933625,0.000068488975,0.000031616175,0.00003952543,0.000025027732,0.00006165516,0.102110736,0.65981644,0.00042742834],"about_ca_topic_score_codex":0.000028286262,"about_ca_topic_score_gemma":0.00003712807,"teacher_disagreement_score":0.8546254,"about_ca_system_score_codex":0.00006152649,"about_ca_system_score_gemma":0.00008837417,"threshold_uncertainty_score":0.99938506},"labels":[],"label_agreement":null},{"id":"W2592762265","doi":"10.1037/xhp0000405","title":"Auditory hindsight bias: Fluency misattribution versus memory reconstruction.","year":2017,"lang":"en","type":"article","venue":"Journal of Experimental Psychology Human Perception & Performance","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kwantlen Polytechnic University","funders":"Canada Research Chairs","keywords":"Hindsight bias; Cognitive psychology; Psychology; Processing fluency; Fluency; Misattribution of memory; Priming (agriculture); Expectancy theory; Recall; PsycINFO; False memory; Experimental psychology; Response bias; Cognition; Social psychology; Neuroscience","score_opus":0.3307181532794316,"score_gpt":0.49911886581021503,"score_spread":0.16840071253078343,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2592762265","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9774799,0.0001659787,0.00008133273,0.00037135283,0.014097073,0.00010435076,0.00000641504,0.000021260852,0.007672337],"genre_scores_gemma":[0.9965781,0.00010594481,0.00087077275,0.00017848094,0.0016611429,0.0000055476726,0.000002991209,0.000019099887,0.00057793123],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9965711,0.00017612657,0.0015914735,0.00050570193,0.00083239353,0.00032320223],"domain_scores_gemma":[0.9956224,0.00013383372,0.0024177546,0.0011267344,0.00049350224,0.00020580152],"candidate_categories":["sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0024975021,0.00026237144,0.0005243815,0.0005247953,0.0015193489,0.00047022922,0.0016083854,0.00026185985,0.0045236163],"category_scores_gemma":[0.00039222513,0.00021225627,0.00035786402,0.000113933274,0.000695868,0.0025318328,0.00014087284,0.0005459339,0.0010352286],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018306838,0.00080588897,0.027816841,0.000004052702,0.00006964087,0.00004388295,0.0018923772,0.000083183986,0.27611515,0.000050513794,0.06815271,0.6231351],"study_design_scores_gemma":[0.009784702,0.0044288635,0.93278974,0.00020695233,0.00008335166,0.0017734095,0.0062343706,0.00036377728,0.011214226,0.0037746972,0.028408166,0.00093775475],"about_ca_topic_score_codex":0.0000070150086,"about_ca_topic_score_gemma":0.00000575007,"teacher_disagreement_score":0.9049729,"about_ca_system_score_codex":0.0003400246,"about_ca_system_score_gemma":0.00007489929,"threshold_uncertainty_score":0.99978054},"labels":[],"label_agreement":null},{"id":"W2593606402","doi":"10.1016/j.jcps.2017.03.001","title":"The satiating effect of pricing: The influence of price on enjoyment over time","year":2017,"lang":"en","type":"article","venue":"Journal of Consumer Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Consumption (sociology); Economics; Microeconomics","score_opus":0.0704521657958546,"score_gpt":0.4577020623484072,"score_spread":0.3872498965525526,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2593606402","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9955401,0.00016776557,0.00005317253,0.0013320118,0.00070744986,0.00011305797,0.000002601431,0.0000017009486,0.0020821549],"genre_scores_gemma":[0.99943197,0.00006358413,0.00012696133,0.00022636834,0.00004539581,0.0000011877406,3.120608e-8,0.000006230802,0.00009826942],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99727625,0.00045630708,0.0012541002,0.00017288471,0.00066943915,0.0001710291],"domain_scores_gemma":[0.9871761,0.0074396664,0.0038611065,0.0010925285,0.00037624507,0.00005430923],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008780281,0.000116189425,0.0004626946,0.00013772592,0.00031014366,0.00013423685,0.0018832829,0.00007812558,0.00008415556],"category_scores_gemma":[0.007103926,0.000049645834,0.00021087739,0.000106226915,0.0004777315,0.00017781339,0.00012813607,0.00030772344,0.00007270227],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010899907,0.00014333206,0.1916847,0.000004286639,0.00011961282,0.000017686376,0.00052129565,0.00056068983,0.01345866,0.00022213804,0.008322305,0.7838553],"study_design_scores_gemma":[0.0014038463,0.0014853508,0.96493953,0.00013723898,0.00007078712,0.00011912293,0.00004268884,0.00010999357,0.002447785,0.008918395,0.020215955,0.000109327666],"about_ca_topic_score_codex":0.000009560369,"about_ca_topic_score_gemma":0.0000026595817,"teacher_disagreement_score":0.783746,"about_ca_system_score_codex":0.00002090097,"about_ca_system_score_gemma":0.00006373529,"threshold_uncertainty_score":0.8504576},"labels":[],"label_agreement":null},{"id":"W2597445068","doi":"10.1093/schbul/sbx022.030","title":"M31. An Investigation of Feedback-Guided Decision-Making in Schizophrenia","year":2017,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"The Scarborough Hospital; University of Toronto; Centre for Addiction and Mental Health","funders":"","keywords":"Iowa gambling task; Psychology; Schizophrenia (object-oriented programming); Context (archaeology); Task (project management); Cognition; Cognitive psychology; Developmental psychology; Psychiatry","score_opus":0.09005656534234753,"score_gpt":0.38287103744871165,"score_spread":0.29281447210636413,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2597445068","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99452186,0.0000917043,0.00041796116,0.0012855349,0.0012773862,0.00034596535,0.00004558481,0.00007177341,0.0019422418],"genre_scores_gemma":[0.9520983,0.000015203906,0.04722278,0.00018132075,0.00023729265,0.000020327656,0.000007595475,0.000052322357,0.0001648634],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99367034,0.00036983125,0.0023686269,0.0013838996,0.0016140301,0.00059325265],"domain_scores_gemma":[0.99183464,0.0017634047,0.0018708777,0.003629951,0.00056536315,0.00033578346],"candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0060217623,0.0004570001,0.0009948846,0.0010323365,0.00072416215,0.0014005164,0.0039683883,0.00035920707,0.0020065533],"category_scores_gemma":[0.009050271,0.00039315282,0.00030405322,0.00054288167,0.00060420774,0.0009061113,0.0008210055,0.0005389325,0.0019175352],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016736675,0.00014809567,0.046042867,0.0000065597496,0.000011796956,0.000061597966,0.00044018446,0.00053912186,0.0010803881,0.0016414615,0.0079444125,0.94040984],"study_design_scores_gemma":[0.004260172,0.00025636735,0.49535447,0.0006809844,0.000033440738,0.000054830205,0.0004224726,0.0020977801,0.0010688959,0.48931557,0.0055722115,0.0008828207],"about_ca_topic_score_codex":0.00029884174,"about_ca_topic_score_gemma":0.00081373466,"teacher_disagreement_score":0.93952703,"about_ca_system_score_codex":0.000117333686,"about_ca_system_score_gemma":0.0003033752,"threshold_uncertainty_score":0.99985206},"labels":[],"label_agreement":null},{"id":"W2597723177","doi":"10.1002/bdm.554","title":"Inventor perseverance after being told to quit: the role of cognitive biases","year":2007,"lang":"en","type":"preprint","venue":"Journal of Behavioral Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; University of Toronto","funders":"","keywords":"Overconfidence effect; Optimism; Pessimism; Procrastination; Sunk costs; Cognitive bias; Psychology; Regret; Population; Optimism bias; Economics; Social psychology; Cognition; Actuarial science; Microeconomics; Demography; Sociology","score_opus":0.14771364963490355,"score_gpt":0.4587705466139139,"score_spread":0.3110568969790104,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2597723177","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9874369,0.0014878147,0.0059826653,0.00013714578,0.0038236352,0.0005348146,0.00017414235,0.00001813496,0.000404747],"genre_scores_gemma":[0.98746127,0.00006029763,0.011284539,0.00041442335,0.0005982816,0.000016443344,0.0000019926129,0.0000694749,0.0000932865],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.988763,0.00040007403,0.0047872667,0.000984351,0.0044106212,0.0006547036],"domain_scores_gemma":[0.98023254,0.0100514535,0.004591722,0.0013759241,0.0033366517,0.0004117381],"candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.009518945,0.0006606486,0.0017988292,0.0022377241,0.00026348673,0.0010681645,0.0033775426,0.0005853419,0.000829159],"category_scores_gemma":[0.009855664,0.00043063107,0.0015891021,0.0011846767,0.00026554358,0.000639882,0.0024730614,0.0018162942,0.00015187806],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016208371,0.00037899264,0.024764488,0.0000045510815,0.00003509909,0.00034309307,0.0037803585,0.0019381017,0.00023633265,0.000022867282,0.0008733047,0.966002],"study_design_scores_gemma":[0.0037449151,0.0036725807,0.21948399,0.051087696,0.0024928597,0.0015556662,0.047475815,0.0024306881,0.0051439316,0.6395569,0.019407999,0.003947001],"about_ca_topic_score_codex":0.000064758075,"about_ca_topic_score_gemma":0.00015749747,"teacher_disagreement_score":0.96205497,"about_ca_system_score_codex":0.00034646087,"about_ca_system_score_gemma":0.0004781076,"threshold_uncertainty_score":0.9999688},"labels":[],"label_agreement":null},{"id":"W2601457172","doi":"10.1016/j.actpsy.2017.03.006","title":"Reaching reveals that best-versus-rest processing contributes to biased decision making","year":2017,"lang":"en","type":"article","venue":"Acta Psychologica","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Killam Trusts","keywords":"Outcome (game theory); Rest (music); Psychology; Probabilistic logic; Contrast (vision); Task (project management); Social psychology; Cognitive psychology; Economics; Computer science; Medicine; Artificial intelligence; Microeconomics","score_opus":0.4123001231186652,"score_gpt":0.5160188737696465,"score_spread":0.1037187506509813,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2601457172","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97065616,0.00014389538,0.0044274544,0.0036290884,0.0025580192,0.00038157805,0.000028875284,0.000109353416,0.018065585],"genre_scores_gemma":[0.98531616,0.000022136186,0.012507006,0.0015022021,0.00017370244,0.000025497071,0.0000023622283,0.000030424399,0.00042051834],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99565566,0.00017657473,0.0010338626,0.0014420158,0.001020273,0.0006715933],"domain_scores_gemma":[0.9921327,0.0032854937,0.0011373822,0.0028521873,0.0003376647,0.00025457612],"candidate_categories":["metaresearch","metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0051637874,0.00036714133,0.000707271,0.0004701553,0.001967676,0.0041130753,0.0039645876,0.0003136663,0.00034304406],"category_scores_gemma":[0.020058883,0.00025734786,0.00024450177,0.00038043762,0.00021039463,0.0011259194,0.00076939294,0.00041308303,0.0013200395],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006898831,0.00014288303,0.024435561,0.0000013033278,0.00000979362,0.000048253172,0.00018354079,0.000019764871,0.0014856394,0.0000739565,0.01911822,0.9537912],"study_design_scores_gemma":[0.0038111508,0.0008685831,0.63250804,0.0011416465,0.00011063989,0.0000559981,0.0016803428,0.00045711463,0.00031257005,0.18769372,0.17004624,0.0013139446],"about_ca_topic_score_codex":0.000019584942,"about_ca_topic_score_gemma":0.00006416612,"teacher_disagreement_score":0.9524773,"about_ca_system_score_codex":0.00012245208,"about_ca_system_score_gemma":0.00005107163,"threshold_uncertainty_score":0.9999879},"labels":[],"label_agreement":null},{"id":"W2604203227","doi":"10.3389/fnbeh.2017.00068","title":"Testosterone and Cortisol Jointly Predict the Ambiguity Premium in an Ellsberg-Urns Experiment","year":2017,"lang":"en","type":"article","venue":"Frontiers in Behavioral Neuroscience","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Simon Fraser University; Università degli Studi di Trento","keywords":"Ambiguity; Testosterone (patch); Economics; Econometrics; Endocrinology; Computer science; Medicine","score_opus":0.19263602092197116,"score_gpt":0.43236210533602665,"score_spread":0.2397260844140555,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2604203227","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9946573,0.00008786633,0.00034510138,0.00045973895,0.0037606426,0.00045947943,0.00003884586,0.000029296783,0.00016173348],"genre_scores_gemma":[0.99786884,0.000035380086,0.0014766334,0.00018927483,0.0000420361,0.000042669417,0.0000010847267,0.000017772327,0.00032632993],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99595934,0.00022598793,0.00091629836,0.0012684464,0.001029842,0.00060007727],"domain_scores_gemma":[0.9969623,0.0001014116,0.0005210608,0.002074657,0.00008503323,0.00025552214],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.002089232,0.00028192767,0.00046738476,0.00035000392,0.00081954966,0.0019163399,0.003202521,0.00012563031,0.000020215444],"category_scores_gemma":[0.00083785347,0.00019958775,0.000075323005,0.0003687461,0.0013725347,0.0019195841,0.0008838539,0.0004429379,0.0000111119825],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004387655,0.00032572774,0.84595734,6.9774944e-7,1.9433513e-7,0.00006901974,0.00059648923,0.00006636401,0.00764409,0.000010978742,0.0010322165,0.14425299],"study_design_scores_gemma":[0.00056405354,0.0005899499,0.98684055,0.000031980813,0.00000835598,0.000026543035,0.0008333521,0.005131086,0.0013308034,0.003286997,0.0010636947,0.00029262062],"about_ca_topic_score_codex":0.00033546638,"about_ca_topic_score_gemma":0.0005459104,"teacher_disagreement_score":0.14396036,"about_ca_system_score_codex":0.00012566856,"about_ca_system_score_gemma":0.00010118039,"threshold_uncertainty_score":0.99911976},"labels":[],"label_agreement":null},{"id":"W2604806010","doi":"10.1002/bdm.2010","title":"On the Counterfactual Nature of Gambling Near‐misses: An Experimental Study","year":2017,"lang":"en","type":"article","venue":"Journal of Behavioral Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":39,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Medical Research Council; Directorate for Biological Sciences; Wellcome; Shenzhen University; National Natural Science Foundation of China; University of Cambridge; Wellcome Trust","keywords":"Counterfactual thinking; Luck; Counterfactual conditional; Regret; Near miss; Psychology; Social psychology; Task (project management); Cognitive psychology; Economics; Statistics; Mathematics","score_opus":0.2653274951832202,"score_gpt":0.5239354939175626,"score_spread":0.25860799873434237,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2604806010","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9961399,0.000112829155,0.0005138987,0.00009424404,0.002612593,0.00027460902,0.000016487564,0.0000102892245,0.00022513683],"genre_scores_gemma":[0.9969981,0.0000031966904,0.0026212872,0.00012120102,0.00018139924,0.0000026773905,2.3476488e-7,0.000034179717,0.00003775758],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9931187,0.00031084332,0.002307181,0.0005469516,0.003378592,0.0003377515],"domain_scores_gemma":[0.9899243,0.0028083373,0.0038075575,0.0021461465,0.0011138915,0.00019974602],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0075874496,0.0003391054,0.00087525015,0.0004887624,0.0012293584,0.0029266954,0.004412923,0.0002564524,0.0008654739],"category_scores_gemma":[0.0038478442,0.00019221808,0.0004959135,0.00025233979,0.00029648875,0.0016443665,0.0005470603,0.0011142349,0.000064913234],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0033764048,0.008362226,0.062891014,0.000001951464,0.00005156107,0.0008225817,0.0075733135,0.0026711666,0.0048534377,0.00041179603,0.004929761,0.90405476],"study_design_scores_gemma":[0.0153159285,0.05570191,0.4302086,0.004237016,0.0009794192,0.0020914446,0.21940374,0.011809428,0.019182352,0.22933334,0.008097368,0.0036394433],"about_ca_topic_score_codex":0.000022404727,"about_ca_topic_score_gemma":0.00003890173,"teacher_disagreement_score":0.90041536,"about_ca_system_score_codex":0.00013558392,"about_ca_system_score_gemma":0.00018381517,"threshold_uncertainty_score":0.9981084},"labels":[],"label_agreement":null},{"id":"W2605235294","doi":"10.1037/xge0000306","title":"Impact bias or underestimation? Outcome specifications predict the direction of affective forecasting errors.","year":2017,"lang":"en","type":"article","venue":"Journal of Experimental Psychology General","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":48,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Quest University Canada","funders":"","keywords":"PsycINFO; Outcome (game theory); Event (particle physics); Psychology; Specification; Affect (linguistics); Econometrics; Discounting; Economics","score_opus":0.625639811081489,"score_gpt":0.5659165674122808,"score_spread":0.059723243669208226,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2605235294","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99212766,0.00012269788,0.0014261326,0.0007591609,0.0024676765,0.00013673079,0.000016992873,0.000006161809,0.0029368089],"genre_scores_gemma":[0.9964438,0.00000853883,0.0027968518,0.00009254802,0.0003551936,0.00000407277,9.973743e-7,0.000011981819,0.00028603282],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9975756,0.00026645357,0.0012326656,0.0002518674,0.00049368915,0.00017972777],"domain_scores_gemma":[0.9955324,0.0007107359,0.0025543135,0.0007712305,0.00031134402,0.00011999777],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026022333,0.0001517317,0.00040901802,0.00026978727,0.0005972439,0.00025107892,0.0011209903,0.000097717304,0.0005903538],"category_scores_gemma":[0.002956539,0.000078159195,0.00032273965,0.00016709062,0.00035319134,0.00058386644,0.00010883579,0.0002807814,0.000024942754],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002269993,0.0019703289,0.5908171,0.0000022339432,0.00030401628,0.00008329706,0.0028318965,0.0034387633,0.06679684,0.0004978778,0.04553276,0.2854549],"study_design_scores_gemma":[0.0021520392,0.002112122,0.96701854,0.000040616662,0.000060721344,0.0012163239,0.0019438587,0.0037012945,0.007394429,0.012860138,0.0012614297,0.00023850088],"about_ca_topic_score_codex":0.00003323866,"about_ca_topic_score_gemma":0.000029355935,"teacher_disagreement_score":0.37620142,"about_ca_system_score_codex":0.00011946972,"about_ca_system_score_gemma":0.00009500506,"threshold_uncertainty_score":0.64639604},"labels":[],"label_agreement":null},{"id":"W2608037399","doi":"10.1177/0146167217702613","title":"Motivated Use of Numerical Anchors for Judgments Relevant to the Self","year":2017,"lang":"en","type":"article","venue":"Personality and Social Psychology Bulletin","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Anchoring; Psychology; Pessimism; Social psychology; Incentive; Futures contract; Cognitive psychology; Epistemology; Economics; Microeconomics","score_opus":0.28544397354384066,"score_gpt":0.46370496511472986,"score_spread":0.1782609915708892,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2608037399","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92322654,0.000012256188,0.0010281036,0.07448234,0.0005018954,0.00023320121,0.00010865353,0.000013151478,0.0003938352],"genre_scores_gemma":[0.9936977,0.000008569432,0.00198841,0.003541938,0.00014710953,0.000018181032,0.0000025236352,0.00000840736,0.0005871616],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99836326,0.00019301141,0.0004484492,0.0004700166,0.0002985908,0.00022665884],"domain_scores_gemma":[0.9979981,0.00088267826,0.00034966946,0.0005053519,0.0001878754,0.00007627774],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022616722,0.000115719246,0.00035032976,0.00004883894,0.00097464235,0.00026054907,0.0007042269,0.00015039575,0.0002680271],"category_scores_gemma":[0.0020971817,0.0000775219,0.00015526278,0.00006383208,0.00030007501,0.000069260335,0.00015108753,0.00014522295,0.00012320993],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008617943,0.00065270753,0.07969157,0.000010004152,0.00009964348,0.000004835135,0.008452632,0.000009912454,0.00017224859,0.0020844615,0.536978,0.3709822],"study_design_scores_gemma":[0.00043750007,0.000113599905,0.38960615,0.000006034272,0.000019100042,0.0000030824601,0.00031874081,0.000045575784,0.000007283118,0.008176341,0.6011584,0.000108225104],"about_ca_topic_score_codex":0.0001165455,"about_ca_topic_score_gemma":0.00002313493,"teacher_disagreement_score":0.37087396,"about_ca_system_score_codex":0.000016849179,"about_ca_system_score_gemma":0.000020903915,"threshold_uncertainty_score":0.749626},"labels":[],"label_agreement":null},{"id":"W2612135801","doi":"10.1111/bioe.12356","title":"The Voluntary Nature of Decision‐Making in Addiction: Static Metaphysical Views <i>Versus</i> Epistemologically Dynamic Views","year":2017,"lang":"en","type":"article","venue":"Bioethics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Clinical Research Institute","funders":"Fonds de Recherche du Québec - Santé; Social Sciences and Humanities Research Council of Canada","keywords":"Metaphysics; Epistemology; Addiction; Psychology; Philosophy; Psychiatry","score_opus":0.2596064784580862,"score_gpt":0.49851130015426964,"score_spread":0.23890482169618343,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2612135801","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97944397,0.002142843,0.0030938922,0.0052525755,0.0053575695,0.0005126138,0.000120605546,0.000041362928,0.004034578],"genre_scores_gemma":[0.9917105,0.00044687738,0.0070484863,0.00043181755,0.000078303594,0.000016757838,0.0000040634905,0.00001811351,0.00024510015],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9953351,0.00050201645,0.0016150101,0.00075279473,0.0014048213,0.00039027908],"domain_scores_gemma":[0.98358476,0.012060611,0.0013902307,0.0024205155,0.0004355056,0.00010838314],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.008768773,0.00027698276,0.0007363569,0.00019249547,0.00097361504,0.00074632216,0.003082002,0.00054932793,0.000102921396],"category_scores_gemma":[0.013739171,0.00015798275,0.00040702408,0.0004049807,0.0013940427,0.00046052737,0.0006909219,0.0013636339,0.00018565053],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044182682,0.0001284927,0.002497896,0.000004343684,0.000022185382,0.0000393319,0.00027446906,0.00010913693,0.000047838308,0.0044053793,0.0032720834,0.988757],"study_design_scores_gemma":[0.0022332347,0.000692735,0.12100529,0.00062841224,0.00013819849,0.000038021586,0.001787495,0.016335998,0.000101103426,0.545335,0.31085482,0.00084972364],"about_ca_topic_score_codex":0.00006376333,"about_ca_topic_score_gemma":0.004700419,"teacher_disagreement_score":0.9879073,"about_ca_system_score_codex":0.00011987493,"about_ca_system_score_gemma":0.00020481202,"threshold_uncertainty_score":0.9945685},"labels":[],"label_agreement":null},{"id":"W2613965546","doi":"10.1111/psyp.12883","title":"Brain activities associated with learning of the Monty Hall Dilemma task","year":2017,"lang":"en","type":"article","venue":"Psychophysiology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brock University","funders":"Japan Society for the Promotion of Science; Waseda University; Ministry of Education, Culture, Sports, Science and Technology","keywords":"Counterintuitive; Psychology; Dilemma; Negativity effect; Task (project management); Cognitive psychology; Prisoner's dilemma; Probabilistic logic; Social psychology; Stimulus (psychology); Anticipation (artificial intelligence); Artificial intelligence; Computer science","score_opus":0.08796086872876036,"score_gpt":0.3825776006635094,"score_spread":0.294616731934749,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2613965546","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99374634,0.0000087708195,0.000066544664,0.0011923698,0.0007338487,0.000093764735,0.000019949812,0.000019500427,0.004118905],"genre_scores_gemma":[0.9977498,0.0000033658757,0.00006357824,0.00019391882,0.00005900387,0.000007479992,0.0000018895712,0.0000124568305,0.0019085207],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99831605,0.00028494198,0.00038271098,0.00042097855,0.00035654422,0.00023874769],"domain_scores_gemma":[0.9960829,0.0014969009,0.0010019034,0.0012270475,0.00014398768,0.000047247046],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00091717695,0.0001414642,0.00040034216,0.00007514994,0.00057505025,0.00017417166,0.001557244,0.00012332098,0.00010271538],"category_scores_gemma":[0.0037806742,0.00007666622,0.0001576045,0.00011938441,0.00053175545,0.0002555911,0.00025369023,0.0002779084,0.0000632357],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00085502636,0.00059716555,0.1999611,0.0000048009706,0.00016421614,0.000020283025,0.0016197853,0.0030412409,0.1555305,0.00089644635,0.022728393,0.61458105],"study_design_scores_gemma":[0.0010810599,0.0004903318,0.8808615,0.00006600883,0.000024215859,0.00000750643,0.0004758502,0.0010295707,0.0012075589,0.10505319,0.00941092,0.00029229186],"about_ca_topic_score_codex":0.00017748533,"about_ca_topic_score_gemma":0.0002445786,"teacher_disagreement_score":0.6809004,"about_ca_system_score_codex":0.000024327825,"about_ca_system_score_gemma":0.00004738825,"threshold_uncertainty_score":0.45260933},"labels":[],"label_agreement":null},{"id":"W2614358634","doi":"10.7202/1039873ar","title":"La décision en ambiguïté : modèles et évaluations expérimentales","year":2016,"lang":"fr","type":"article","venue":"L Actualité économique","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Humanities; Political science; Philosophy","score_opus":0.21867981843231107,"score_gpt":0.4279624490384634,"score_spread":0.20928263060615235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2614358634","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94733703,0.0010607208,0.010903079,0.020403747,0.0026303376,0.00042011958,0.00049138145,0.000120539815,0.016633015],"genre_scores_gemma":[0.9516659,0.0011601417,0.007893881,0.0014053243,0.00034173313,0.000071462775,0.000015340216,0.00007471404,0.037371527],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99367094,0.0022075004,0.0017268667,0.0013104291,0.0004120863,0.0006721994],"domain_scores_gemma":[0.9830731,0.014236288,0.00057795236,0.0014403355,0.0002439416,0.00042835384],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.007674421,0.00055190705,0.0008005829,0.00047483528,0.00028222016,0.00088772655,0.00140317,0.00070433214,0.006112119],"category_scores_gemma":[0.0035541975,0.00039437684,0.00051804516,0.00033221202,0.0006272929,0.0019309998,0.0006583403,0.00038032045,0.008697039],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006979288,0.0003479095,0.0009298918,0.0000058717783,0.0000378501,0.000025758261,0.0018962726,0.00015107557,0.0026031244,0.07207875,0.005915736,0.91593796],"study_design_scores_gemma":[0.0010782684,0.00020045567,0.004630815,0.00045303497,0.00006158302,0.000101297985,0.0014569057,0.000703597,0.0039859107,0.4466964,0.5399643,0.0006674173],"about_ca_topic_score_codex":0.000735754,"about_ca_topic_score_gemma":0.00071177783,"teacher_disagreement_score":0.91527057,"about_ca_system_score_codex":0.00061971525,"about_ca_system_score_gemma":0.00067045947,"threshold_uncertainty_score":0.9998508},"labels":[],"label_agreement":null},{"id":"W2614504113","doi":"10.7202/1039872ar","title":"Quels déterminants de la prise de risque? Les réponses de l’économie expérimentale","year":2017,"lang":"fr","type":"article","venue":"L Actualité économique","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Humanities; Gynecology; Political science; Philosophy; Medicine","score_opus":0.1444700066093883,"score_gpt":0.42920512677652395,"score_spread":0.28473512016713565,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2614504113","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9716942,0.0011904349,0.0016741616,0.003985786,0.001555859,0.00041072312,0.0002933865,0.00009225211,0.019103227],"genre_scores_gemma":[0.9575944,0.0008447969,0.015166052,0.001537611,0.00065847364,0.00009302076,0.000005607626,0.00009849442,0.024001557],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.994268,0.0013504341,0.0015087696,0.001296863,0.0001781211,0.0013977845],"domain_scores_gemma":[0.9892803,0.005733072,0.0014024458,0.0025999052,0.00013621892,0.00084808347],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0076827216,0.00067541946,0.0010697659,0.0003091046,0.0015017535,0.0040720035,0.003261575,0.0010913075,0.002000652],"category_scores_gemma":[0.005601924,0.0006879877,0.0006088092,0.00008872904,0.0016963062,0.0018374927,0.0009470528,0.000763279,0.0013538123],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024472267,0.0005648168,0.07528898,0.000031372205,0.00007301568,0.0003726114,0.0025554483,0.00024207581,0.0020551018,0.008093866,0.008186753,0.90229124],"study_design_scores_gemma":[0.0020616115,0.00030920753,0.076103985,0.00059951504,0.00019258793,0.00097626325,0.0023546962,0.006346941,0.040734567,0.40997782,0.45877743,0.001565385],"about_ca_topic_score_codex":0.012955276,"about_ca_topic_score_gemma":0.001196871,"teacher_disagreement_score":0.90072584,"about_ca_system_score_codex":0.0019671728,"about_ca_system_score_gemma":0.002254014,"threshold_uncertainty_score":0.9997982},"labels":[],"label_agreement":null},{"id":"W2615603793","doi":"10.5465/ambpp.2015.15206abstract","title":"Performance-based Reward: How You Get Paid Shapes How You Value Money","year":2015,"lang":"en","type":"article","venue":"Academy of Management Proceedings","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Reward system; Valuation (finance); Task (project management); Value (mathematics); Psychology; Economics; Computer science; Finance; Neuroscience; Management; Machine learning","score_opus":0.14413686062110284,"score_gpt":0.3465430737658902,"score_spread":0.20240621314478738,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2615603793","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9670674,0.000106141735,0.00024003751,0.01814424,0.00028604502,0.0005244189,0.000013272581,0.0001491952,0.01346923],"genre_scores_gemma":[0.9846518,0.00009695172,0.005951647,0.0010707098,0.00018311101,0.00004768235,0.0000033445872,0.000040309864,0.0079544205],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.995244,0.000034482066,0.00082640134,0.0010637479,0.0022221508,0.00060919847],"domain_scores_gemma":[0.9980139,0.00015794218,0.0008704085,0.00026867725,0.00034532498,0.00034375777],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.005747407,0.0003951605,0.00064175075,0.000843872,0.00019276068,0.0007846677,0.0022429598,0.00027358448,0.0000660685],"category_scores_gemma":[0.0007882952,0.00031736286,0.0002350895,0.001004489,0.00022253703,0.0018869842,0.0006562034,0.00038868128,0.00026245514],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022914381,0.00021316115,0.048950233,0.00013885809,0.00008368082,0.000007708511,0.0009590007,0.00063555746,0.00020357042,0.003432177,0.27709156,0.66805536],"study_design_scores_gemma":[0.0031338108,0.00071900385,0.033462707,0.00038988361,0.00027907503,0.000013804159,0.009257517,0.042446505,0.0033643995,0.04027203,0.8654157,0.0012455521],"about_ca_topic_score_codex":0.0000052942314,"about_ca_topic_score_gemma":1.9419271e-7,"teacher_disagreement_score":0.6668098,"about_ca_system_score_codex":0.00013103765,"about_ca_system_score_gemma":0.00004013097,"threshold_uncertainty_score":0.9999278},"labels":[],"label_agreement":null},{"id":"W2618131751","doi":"10.1073/pnas.1706530115","title":"Personal bests as reference points","year":2018,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Set (abstract data type); Psychology; Loss aversion; Social psychology; Computer science; Economics; Microeconomics","score_opus":0.25346569360984345,"score_gpt":0.45103619010263934,"score_spread":0.1975704964927959,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2618131751","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94677216,0.000017562761,9.1474436e-7,0.0032509633,0.00006947418,0.0000793863,0.000019589364,0.000009279395,0.049780652],"genre_scores_gemma":[0.9968887,0.0000048482198,0.0016559539,0.0006171067,0.00012687634,0.0000025655158,4.056363e-8,0.0000032246253,0.0007006651],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99562967,0.000012209387,0.0006452437,0.00045875658,0.0030644296,0.0001897145],"domain_scores_gemma":[0.997352,0.0005502116,0.0007978027,0.000018391642,0.0012147976,0.00006681077],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0054569934,0.000107433574,0.00021376339,0.00032026749,0.00036653155,0.0001385978,0.0024438698,0.000103595,0.0003625357],"category_scores_gemma":[0.0049337144,0.00006200698,0.000111353176,0.0013270119,0.002040271,0.0008161297,0.00036785105,0.00016831982,0.00018380418],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024979527,0.0004917628,0.12697515,0.000026767219,0.00003960503,6.5246965e-8,0.0040307534,0.000028547502,0.23842709,0.31994942,0.0652453,0.24453576],"study_design_scores_gemma":[0.00013967698,0.00015586508,0.08892711,0.00007076346,0.000007207421,0.000023671371,0.0006241333,0.0008669799,0.056239188,0.8487851,0.0040374417,0.00012284784],"about_ca_topic_score_codex":0.000015549429,"about_ca_topic_score_gemma":4.4049688e-7,"teacher_disagreement_score":0.5288357,"about_ca_system_score_codex":0.000036137102,"about_ca_system_score_gemma":0.00008254963,"threshold_uncertainty_score":0.75174636},"labels":[],"label_agreement":null},{"id":"W2618377127","doi":"10.7202/1039885ar","title":"Confiance, métacognition et perception","year":2017,"lang":"fr","type":"article","venue":"L Actualité économique","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Humanities; Philosophy","score_opus":0.3244306942793855,"score_gpt":0.4631897662369568,"score_spread":0.1387590719575713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2618377127","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90059584,0.00024604506,0.0026108602,0.020470826,0.0068593877,0.0003786017,0.00034048065,0.000072695446,0.06842524],"genre_scores_gemma":[0.95164007,0.0007494425,0.002992564,0.0036278178,0.0008212042,0.00003692477,0.000035436202,0.00005135227,0.040045172],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9962099,0.00046110887,0.0012826143,0.001164166,0.00026063822,0.00062155037],"domain_scores_gemma":[0.9944875,0.0012543324,0.0012782237,0.0022159687,0.00038826937,0.0003757009],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0039336206,0.000454845,0.0007477908,0.0002445534,0.001097773,0.0043635266,0.0018297707,0.00063529116,0.011317453],"category_scores_gemma":[0.0029597462,0.00044763787,0.0004428389,0.0000895868,0.0007815691,0.0033882556,0.00048506653,0.00056990143,0.014164188],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000080452504,0.00019295719,0.002119998,0.000012301952,0.000023649765,0.000030085253,0.0009947662,0.00004675749,0.00040450812,0.03241295,0.0083102,0.9553714],"study_design_scores_gemma":[0.0009087404,0.00018156022,0.035003956,0.00027814918,0.00006451772,0.00008257317,0.0010233736,0.0020333636,0.00038284934,0.41114375,0.54822755,0.0006695975],"about_ca_topic_score_codex":0.0015453108,"about_ca_topic_score_gemma":0.00097133795,"teacher_disagreement_score":0.9547018,"about_ca_system_score_codex":0.00030299148,"about_ca_system_score_gemma":0.00040216112,"threshold_uncertainty_score":0.9997975},"labels":[],"label_agreement":null},{"id":"W2621962930","doi":"10.7203/metode.0.6923","title":"The role of the brain in financial decisions: A viewpoint on neuroeconomics","year":2018,"lang":"en","type":"article","venue":"Mètode Revista de difusió de la investigació","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Neuroeconomics; Affect (linguistics); Neuropsychology; Financial market; Behavioral economics; Psychology; Finance; Cognition; Economics; Neuroscience","score_opus":0.04895700461678462,"score_gpt":0.35363930586053594,"score_spread":0.3046823012437513,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2621962930","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9920066,0.00040987658,0.00019388764,0.0029997681,0.00031093613,0.00029972548,0.000031514723,0.000019857414,0.0037278163],"genre_scores_gemma":[0.9935209,0.00013324646,0.0008292099,0.0050880513,0.00016332963,0.000029860223,9.3695326e-7,0.000028678616,0.00020577766],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9959242,0.0010968213,0.0013225522,0.00059556175,0.0005494392,0.00051147287],"domain_scores_gemma":[0.98786277,0.009387842,0.00062991853,0.0017344191,0.0001777369,0.00020729707],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.007817832,0.00025931108,0.0004895148,0.00022278761,0.0004144266,0.00072111853,0.002310856,0.00020150738,0.00007518011],"category_scores_gemma":[0.03755133,0.00015035694,0.00030966883,0.0008257928,0.0011330831,0.00015497029,0.00047789543,0.00052520883,0.00022377823],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001744265,0.00017483425,0.07131449,0.0000039940473,0.000007855163,0.00001783988,0.00096442294,0.00063615723,0.0016387637,0.117921196,0.0154809775,0.791665],"study_design_scores_gemma":[0.00029925047,0.0001106872,0.0600651,0.00017207216,0.000010627335,0.00003299381,0.00016011576,0.004616388,0.00086447696,0.5023667,0.43111432,0.00018725252],"about_ca_topic_score_codex":0.000116766096,"about_ca_topic_score_gemma":0.00052177324,"teacher_disagreement_score":0.7914778,"about_ca_system_score_codex":0.00021267158,"about_ca_system_score_gemma":0.00063163304,"threshold_uncertainty_score":0.9705558},"labels":[],"label_agreement":null},{"id":"W2622504489","doi":"","title":"Applying Cognitive Architectures to Decision-Making: How Cognitive Theory and the Equivalence Measure Triumphed in the Technion Prediction Tournament","year":2009,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Tournament; Equivalence (formal languages); Cognition; Artificial intelligence; Psychology; Variance (accounting); Mathematical economics; Computer science; Econometrics; Machine learning; Cognitive science; Cognitive psychology; Economics; Mathematics; Discrete mathematics","score_opus":0.04117976248640369,"score_gpt":0.3143212163103034,"score_spread":0.2731414538238997,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2622504489","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.970655,0.00035986013,0.017978532,0.0037661584,0.00016801468,0.0021609964,0.0010565204,0.00013209552,0.0037227976],"genre_scores_gemma":[0.99510056,0.000013115606,0.00049402093,0.003951715,0.00013541243,0.00018791988,0.00002087934,0.00003067364,0.00006569656],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9948886,0.001040034,0.00091726927,0.0009509603,0.0016723038,0.00053085486],"domain_scores_gemma":[0.98141265,0.017234407,0.00037715063,0.00058978057,0.00017287949,0.00021314253],"candidate_categories":["metaresearch","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0069522955,0.0004150701,0.00051457685,0.0005960125,0.000503007,0.005712378,0.0014562022,0.00018802346,0.00008992307],"category_scores_gemma":[0.023500625,0.00021759937,0.00025489714,0.001466653,0.00035251872,0.0018948826,0.00039465824,0.00085462653,0.00023945307],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0032776147,0.00015247411,0.00805175,0.0000020506386,0.000013083647,0.000037685604,0.0005416574,0.000034738816,0.000023612743,0.0010594772,0.0004642122,0.98634166],"study_design_scores_gemma":[0.00243027,0.00044660288,0.040279027,0.0010504321,0.0000615083,0.0001311458,0.004805412,0.0002474228,0.0002068009,0.9452415,0.004606723,0.0004931268],"about_ca_topic_score_codex":7.2034646e-7,"about_ca_topic_score_gemma":0.0000027434537,"teacher_disagreement_score":0.9858485,"about_ca_system_score_codex":0.000050082228,"about_ca_system_score_gemma":0.000095223186,"threshold_uncertainty_score":0.9953198},"labels":[],"label_agreement":null},{"id":"W2623297173","doi":"10.1287/moor.2017.0847","title":"Information and Ambiguity: Toward a Foundation of Nonexpected Utility","year":2017,"lang":"en","type":"article","venue":"Mathematics of Operations Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Ambiguity; Class (philosophy); Probabilistic logic; Foundation (evidence); Relation (database); Mathematical economics; Expected utility hypothesis; Computer science; Mathematics; Epistemology; Artificial intelligence; Data mining; Law; Political science","score_opus":0.5213376055904207,"score_gpt":0.5533005944671012,"score_spread":0.031962988876680476,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2623297173","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.983868,0.000008282677,0.009676332,0.0005106958,0.00006544257,0.00028037146,0.000029764873,0.000006866175,0.005554219],"genre_scores_gemma":[0.985467,0.000015586767,0.014314777,0.000003907768,0.000011018809,0.000013481662,0.000006363442,0.0000038108678,0.00016401107],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99755096,0.0001041188,0.000936924,0.00014316863,0.0011242437,0.00014059845],"domain_scores_gemma":[0.9958476,0.00064630643,0.00025437685,0.0011183526,0.0020704232,0.000062986066],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.006343687,0.00007123315,0.00027097343,0.00042944594,0.00055345567,0.0010183649,0.0008010897,0.0000700038,0.00027614736],"category_scores_gemma":[0.015477196,0.000055086766,0.000051016617,0.00023905755,0.0004586398,0.0014343114,0.00041869594,0.0001358923,0.00012061465],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005733464,0.00056998443,0.0059111575,0.00011793852,0.000027093285,9.791216e-7,0.014472507,0.00028676947,0.003909615,0.034674883,0.0011745946,0.9387971],"study_design_scores_gemma":[0.0013984572,0.00046502944,0.082558975,0.000243483,0.000030707422,0.000016540831,0.018926855,0.4144502,0.013590272,0.4644715,0.0034816207,0.00036636903],"about_ca_topic_score_codex":0.00031016933,"about_ca_topic_score_gemma":0.0001686511,"teacher_disagreement_score":0.9384308,"about_ca_system_score_codex":0.000025633426,"about_ca_system_score_gemma":0.00016329382,"threshold_uncertainty_score":0.99281585},"labels":[],"label_agreement":null},{"id":"W2626031197","doi":"10.3758/s13421-017-0723-2","title":"Interactions between inferential strategies and belief bias","year":2017,"lang":"en","type":"article","venue":"Memory & Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Counterexample; Syllogism; Psychology; Premise; Cognition; Cognitive psychology; Statistical inference; Feeling; Statement (logic); Deductive reasoning; Social psychology; Artificial intelligence; Epistemology; Computer science; Mathematics; Statistics","score_opus":0.4022683191648455,"score_gpt":0.4707955966057211,"score_spread":0.06852727744087561,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2626031197","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9644181,0.000012676869,0.0013238385,0.00035678825,0.0006858145,0.00009577829,0.000046460787,0.00003789415,0.03302266],"genre_scores_gemma":[0.9987749,0.000010225848,0.00022999858,0.000051887437,0.0002668533,0.000007427118,0.000020115283,0.000008603993,0.00063001504],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9986156,0.00008274248,0.0004281982,0.00037068766,0.00035020735,0.00015256177],"domain_scores_gemma":[0.99811953,0.0006407189,0.00037554148,0.0005429752,0.0002276965,0.0000935052],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0009631536,0.000121740406,0.00022235644,0.00019625798,0.00075933867,0.0030642916,0.00040164712,0.00007614836,0.0007149529],"category_scores_gemma":[0.0014004159,0.00010013583,0.00007974185,0.00006105494,0.00019615331,0.0020034795,0.00019669095,0.00018273063,0.0007146197],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016887352,0.000036011024,0.004707626,0.0000014081107,0.000009384851,0.000005502627,0.00015234153,0.000004279265,0.00046885293,0.00016153867,0.00078971375,0.99364644],"study_design_scores_gemma":[0.0010241471,0.00022688325,0.51669014,0.00010822241,0.00015167079,0.000032505028,0.003977414,0.00029184265,0.0023589015,0.454132,0.020540537,0.0004657621],"about_ca_topic_score_codex":0.00006576668,"about_ca_topic_score_gemma":0.00026298926,"teacher_disagreement_score":0.9931807,"about_ca_system_score_codex":0.000017786115,"about_ca_system_score_gemma":0.000056337292,"threshold_uncertainty_score":0.99797064},"labels":[],"label_agreement":null},{"id":"W2655825240","doi":"10.3758/s13423-017-1333-5","title":"Mind, rationality, and cognition: An interdisciplinary debate","year":2017,"lang":"en","type":"article","venue":"Psychonomic Bulletin & Review","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":79,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Economic and Social Research Council; Engineering and Physical Sciences Research Council; University of Oxford","keywords":"Rationality; Heuristics; Psychology; Ecological rationality; Situational ethics; Perception; Epistemology; Cognition; Great Rationality Debate; Argument (complex analysis); Bounded rationality; Cognitive science; Cognitive psychology; Social psychology; Philosophy; Computer science","score_opus":0.22239935141937298,"score_gpt":0.5053916825700152,"score_spread":0.28299233115064226,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2655825240","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8540845,0.022059182,0.00045263092,0.0722478,0.0026367144,0.0009468198,0.000102341386,0.000050042643,0.047420003],"genre_scores_gemma":[0.97835845,0.01120932,0.00381492,0.0038322613,0.00043949205,0.00006930305,0.000028645227,0.000031623797,0.0022160043],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9975008,0.0001845789,0.0009856804,0.00081119215,0.0003081639,0.0002096119],"domain_scores_gemma":[0.9969017,0.00036944772,0.0007331505,0.0016147431,0.00017072626,0.00021023599],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0035751855,0.00020887841,0.00054446707,0.00008149281,0.00076352566,0.0009988439,0.0012670951,0.0000772966,0.006087614],"category_scores_gemma":[0.00071624765,0.00016304094,0.00017028282,0.00005330807,0.00025911076,0.0003501096,0.00060732116,0.00016251215,0.005772617],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023784432,0.00006761542,0.0006519891,0.000027055954,0.000007458452,0.0000070691212,0.000039682818,5.460026e-7,0.000008493924,0.000120148856,0.073779464,0.9252667],"study_design_scores_gemma":[0.00046154865,0.00009051535,0.011601815,0.0011128221,0.00006667989,0.00012759153,0.000078452285,0.00006275615,0.000007445756,0.066185996,0.9198714,0.00033297116],"about_ca_topic_score_codex":0.000009557938,"about_ca_topic_score_gemma":0.000031616233,"teacher_disagreement_score":0.92493373,"about_ca_system_score_codex":0.000026313868,"about_ca_system_score_gemma":0.000036765963,"threshold_uncertainty_score":0.9950015},"labels":[],"label_agreement":null},{"id":"W2727626161","doi":"10.1016/j.jneb.2017.05.149","title":"Not State Self-Control, but Time Predicts Unhealthy Food Purchases","year":2017,"lang":"en","type":"article","venue":"Journal of Nutrition Education and Behavior","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Control (management); Self-control; Environmental health; State (computer science); Business; Food science; Psychology; Computer science; Medicine; Chemistry; Social psychology; Artificial intelligence","score_opus":0.07805513205981113,"score_gpt":0.394339339560027,"score_spread":0.31628420750021585,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2727626161","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9932029,0.0002507879,0.00009893227,0.0038243528,0.0020990486,0.00027083614,0.00011007243,0.000017559607,0.00012548172],"genre_scores_gemma":[0.9960237,0.00020371145,0.0021758217,0.00040813026,0.0005603152,0.00003156259,0.0000035063642,0.000012978344,0.0005802461],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9975693,0.00012240576,0.0011091568,0.00027230827,0.000725972,0.00020082734],"domain_scores_gemma":[0.9960114,0.00033395746,0.0017736957,0.00050403376,0.0010315195,0.0003453938],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017355962,0.00015452855,0.00040701436,0.00045779088,0.0005380144,0.0010325547,0.0006467386,0.000100600264,0.0002740824],"category_scores_gemma":[0.00086209766,0.00012053379,0.00017411035,0.00009651716,0.00010998217,0.0012385077,0.00005195961,0.00023655083,0.00010985447],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017388024,0.009948804,0.015474457,0.000014773341,0.000019733696,0.000019205483,0.00041689264,0.000002494088,0.001967071,0.000042084463,0.015970862,0.9559497],"study_design_scores_gemma":[0.008255685,0.0038595423,0.80762476,0.00044010335,0.00058262167,0.0015311835,0.002808884,0.00018848051,0.0025419972,0.033174846,0.13828917,0.0007027496],"about_ca_topic_score_codex":0.000011907049,"about_ca_topic_score_gemma":0.000007813168,"teacher_disagreement_score":0.955247,"about_ca_system_score_codex":0.00009416622,"about_ca_system_score_gemma":0.0004088204,"threshold_uncertainty_score":0.9956949},"labels":[],"label_agreement":null},{"id":"W2732999591","doi":"10.1371/journal.pone.0180585","title":"Alternation between different types of evidence attenuates judgments of severity","year":2017,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Event (particle physics); Cognition; Alternation (linguistics); Cognitive psychology; Psychology; Event-related potential; Affect (linguistics); Social psychology; Computer science; Communication; Neuroscience","score_opus":0.6949334082849977,"score_gpt":0.45942206338715563,"score_spread":0.2355113448978421,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2732999591","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99899846,0.00003376632,0.000083219355,0.00031563587,0.00009619353,0.00009698124,0.000040406452,0.0000071469904,0.00032816804],"genre_scores_gemma":[0.9987145,0.000039335402,0.00077568676,0.00000939442,0.000049889033,0.000002469767,0.0000015048836,0.0000050414887,0.00040219238],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99818534,0.00004887985,0.000542622,0.00024576118,0.00087557157,0.000101812606],"domain_scores_gemma":[0.99736977,0.0006330436,0.0007902242,0.0008365257,0.00031989109,0.000050572507],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00086130295,0.00008098897,0.00038839775,0.00009813679,0.00010015374,0.000116104224,0.0010266477,0.00004862335,0.00013955338],"category_scores_gemma":[0.003123003,0.000053648,0.00007093469,0.000050209434,0.00010922263,0.00039700398,0.00027035462,0.000064937274,0.00010462125],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000210607,0.00032885183,0.8661406,0.000010058888,0.00003580434,5.7580615e-7,0.000075528194,0.0000030488484,0.0068193786,0.000017229686,0.000066401946,0.12648147],"study_design_scores_gemma":[0.00015888773,0.000099139186,0.8684916,0.00036014174,0.00007108249,1.1968028e-7,0.000019787107,0.00048098253,0.112962745,0.01725327,0.000019627332,0.000082608974],"about_ca_topic_score_codex":0.00009714779,"about_ca_topic_score_gemma":0.000025133766,"teacher_disagreement_score":0.12639886,"about_ca_system_score_codex":0.000023177832,"about_ca_system_score_gemma":0.000018535055,"threshold_uncertainty_score":0.3738752},"labels":[],"label_agreement":null},{"id":"W2734855058","doi":"10.3390/admsci7030023","title":"More Dynamic Than You Think: Hidden Aspects of Decision-Making","year":2017,"lang":"en","type":"article","venue":"Administrative Sciences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Ambiguity; Intrapersonal communication; Multitude; Affect (linguistics); Interpersonal communication; Decision field theory; Set (abstract data type); Psychology; Management science; Cognitive psychology; Social psychology; Decision engineering; Business decision mapping; Computer science; Epistemology; Decision support system; Artificial intelligence; Economics","score_opus":0.17762280033523786,"score_gpt":0.4856936516902002,"score_spread":0.3080708513549623,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2734855058","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9361847,0.0001024928,0.00059011846,0.0013305702,0.0012359257,0.00019383186,0.00007945926,0.000034263463,0.060248613],"genre_scores_gemma":[0.98907614,0.000012786668,0.010300066,0.000088284956,0.000057949546,0.0000049326554,0.0000010866256,0.00001139104,0.00044736214],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99508834,0.00011976724,0.0010962908,0.001146625,0.0020768323,0.00047213986],"domain_scores_gemma":[0.99311423,0.002848983,0.0016928453,0.0017453567,0.00044070347,0.00015788493],"candidate_categories":["metaresearch","sts","scholarly_communication"],"consensus_categories":["sts"],"category_scores_codex":[0.004391101,0.000289483,0.0006128558,0.00039183468,0.0018479795,0.001898725,0.0051081106,0.00013703921,0.0005179505],"category_scores_gemma":[0.010529478,0.00020094436,0.00028272925,0.00054677716,0.0030187152,0.0016645083,0.0006372666,0.00022046993,0.00024158992],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008376975,0.00018102968,0.032306597,0.0000027928947,0.000018007426,0.00012373723,0.0020876902,0.000043152366,0.0005936368,0.016460862,0.0008347126,0.947264],"study_design_scores_gemma":[0.00029736807,0.000699979,0.21710211,0.00025689867,0.000023100149,0.00006861563,0.010545582,0.002711793,0.0011068418,0.76559097,0.0011577437,0.0004390137],"about_ca_topic_score_codex":0.000060704417,"about_ca_topic_score_gemma":0.0007047634,"teacher_disagreement_score":0.946825,"about_ca_system_score_codex":0.00005580065,"about_ca_system_score_gemma":0.00076475303,"threshold_uncertainty_score":0.9996945},"labels":[],"label_agreement":null},{"id":"W2743103208","doi":"10.1101/174136","title":"The conflict negativity: A neural correlate of value conflict and indecision during financial decision making","year":2017,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Psychology; Negativity effect; Value (mathematics); Social psychology; Odds; Perception; Cognitive psychology; Logistic regression","score_opus":0.05922746786752679,"score_gpt":0.3283446766854814,"score_spread":0.2691172088179546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2743103208","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9902771,0.002279385,0.0016359787,0.00018356074,0.0044153086,0.00082149304,0.00023946335,0.000121509074,0.000026188936],"genre_scores_gemma":[0.99642795,0.00078543165,0.0021696144,0.0000877475,0.00034870853,0.000054151737,1.1107089e-7,0.000108546556,0.00001773246],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99217296,0.0004645252,0.002414263,0.002083422,0.0020098432,0.0008550079],"domain_scores_gemma":[0.9859902,0.0043732505,0.003472873,0.0044093444,0.0013821208,0.00037218697],"candidate_categories":["metaresearch","metaepi_narrow","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.006700412,0.0008805473,0.0015980365,0.0007177211,0.001695572,0.0029147004,0.0034179469,0.0010156025,0.000035714576],"category_scores_gemma":[0.016658448,0.00066201156,0.0005054875,0.000548165,0.00089209987,0.00064347143,0.003770359,0.0016444846,0.00008267437],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.011891297,0.0024057499,0.40384066,0.0009766722,0.0012739833,0.0030722304,0.0016554845,0.017663796,0.357897,0.012596262,0.012168244,0.17455861],"study_design_scores_gemma":[0.0022024948,0.00022224015,0.94128966,0.0025530485,0.00023886461,0.0000010720901,0.000027782262,0.017565042,0.013518115,0.0019239394,0.018621586,0.0018361374],"about_ca_topic_score_codex":0.00007383492,"about_ca_topic_score_gemma":0.000019370551,"teacher_disagreement_score":0.537449,"about_ca_system_score_codex":0.00022538907,"about_ca_system_score_gemma":0.0007704599,"threshold_uncertainty_score":0.9996041},"labels":[],"label_agreement":null},{"id":"W2744973251","doi":"10.1111/spc3.12341","title":"Wisdom in a complex world: A situated account of wise reasoning and its development","year":2017,"lang":"en","type":"article","venue":"Social and Personality Psychology Compass","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Situated; Set (abstract data type); Psychology; Interpersonal communication; Trait; Motivated reasoning; Empirical evidence; Politics; Situated cognition; State (computer science); Epistemology; Social psychology; Computer science; Political science; Artificial intelligence","score_opus":0.37989780718522864,"score_gpt":0.5021246441080891,"score_spread":0.12222683692286046,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2744973251","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99163413,0.0000966082,0.000029579815,0.0034157569,0.00018930291,0.00010416016,0.000022881353,0.000009890067,0.004497705],"genre_scores_gemma":[0.9988516,0.0000084378335,0.0005295386,0.00036369788,0.000054198452,0.0000059642566,0.000004115196,0.000005671334,0.00017676938],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99826705,0.00015859955,0.0005622948,0.0004797615,0.000305351,0.00022692942],"domain_scores_gemma":[0.9988266,0.00025771858,0.00043263784,0.00026088158,0.00013944178,0.00008268495],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020587079,0.00014148306,0.000502176,0.00018580083,0.00058298325,0.00019070688,0.00048749064,0.00011127223,0.00021625067],"category_scores_gemma":[0.0002869189,0.000120912824,0.000058310925,0.00016201274,0.00044568029,0.00019018186,0.0002074037,0.0001837084,0.00002191901],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039298378,0.0002822319,0.6230793,0.000011197565,0.00003527855,0.000023334602,0.0116846515,0.0000013077796,0.000633246,0.0032865861,0.0040430883,0.35652682],"study_design_scores_gemma":[0.0009006914,0.000021738908,0.9694699,0.000021978864,0.0000068065974,0.000007930627,0.00062429486,0.00024124449,0.000008089282,0.017016744,0.011539412,0.00014118184],"about_ca_topic_score_codex":0.00020047452,"about_ca_topic_score_gemma":0.0023675193,"teacher_disagreement_score":0.35638565,"about_ca_system_score_codex":0.00003032352,"about_ca_system_score_gemma":0.00005445611,"threshold_uncertainty_score":0.4930682},"labels":[],"label_agreement":null},{"id":"W2745910124","doi":"10.1037/xge0000351","title":"Choice as an engine of analytic thought.","year":2017,"lang":"en","type":"article","venue":"Journal of Experimental Psychology General","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"Nanyang Technological University","keywords":"Categorization; Psychology; PsycINFO; Cognition; Perception; Cognitive psychology; Social psychology; Task (project management); Independence (probability theory); Need for cognition; Variety (cybernetics); Computer science","score_opus":0.22992344395955847,"score_gpt":0.5561097500488356,"score_spread":0.3261863060892771,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2745910124","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99058485,0.00036804765,0.00014413997,0.00049665244,0.0027091773,0.00004812434,0.0000055539135,0.000004517728,0.00563891],"genre_scores_gemma":[0.99302435,0.000016861963,0.005120373,0.00043705324,0.0006397977,8.85121e-7,6.949925e-7,0.000013748699,0.0007462161],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99749434,0.00016556832,0.0011958611,0.000332044,0.000593487,0.00021868706],"domain_scores_gemma":[0.9964732,0.00018121343,0.0017333924,0.0011291556,0.00026623707,0.0002167957],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0020687485,0.00016107912,0.0005614729,0.00034144585,0.00023231292,0.00021685279,0.001949314,0.00013340532,0.0009168132],"category_scores_gemma":[0.00076870044,0.00011619845,0.00030738718,0.000103997445,0.00028008065,0.0007998935,0.00013731729,0.00027488818,0.000102149876],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011960682,0.0028638141,0.06838234,0.000001677416,0.00017182302,0.0003586191,0.0012075304,0.0003891972,0.55039424,0.0012699707,0.034478378,0.33928633],"study_design_scores_gemma":[0.012921652,0.012716327,0.43252844,0.000121923535,0.0001971569,0.0040013744,0.0032259054,0.0022247825,0.33943027,0.096353084,0.09490101,0.0013780663],"about_ca_topic_score_codex":0.000031836906,"about_ca_topic_score_gemma":0.000009554923,"teacher_disagreement_score":0.3641461,"about_ca_system_score_codex":0.0000410661,"about_ca_system_score_gemma":0.00006046684,"threshold_uncertainty_score":0.9999965},"labels":[],"label_agreement":null},{"id":"W2748787302","doi":"10.1016/s0065-2601(10)43001-4","title":"The Planning Fallacy","year":2010,"lang":"en","type":"book-chapter","venue":"Advances in experimental social psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":105,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Wilfrid Laurier University","funders":"","keywords":"Fallacy; Generality; Phenomenon; Psychology; Scope (computer science); Epistemology; Empirical research; Prospect theory; Cognition; Cognitive psychology; Management science; Social psychology; Computer science; Economics","score_opus":0.1436415786135078,"score_gpt":0.5189504137256972,"score_spread":0.3753088351121894,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2748787302","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.024499044,0.012717149,0.00007506607,0.0007045365,0.008495508,0.0002818058,0.000021181162,0.000048682414,0.953157],"genre_scores_gemma":[0.7887002,0.0016236418,0.0016046043,0.0032120938,0.0029915343,0.00011468228,0.000031164924,0.00021937258,0.2015027],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9968223,0.00007201201,0.0010939561,0.0009266344,0.00065253006,0.00043259814],"domain_scores_gemma":[0.99749196,0.0009910425,0.0006740797,0.0006890936,0.00007282029,0.0000810116],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001080705,0.00037059386,0.00060891383,0.00021439671,0.00062510185,0.00021451912,0.0016697069,0.0006914062,0.00096120354],"category_scores_gemma":[0.00017644398,0.0002672001,0.00027758148,0.00008808358,0.0009753152,0.00030240705,0.00030251374,0.0010716353,0.0009540908],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020435857,0.00007809691,0.0002303527,6.130014e-7,0.000011365084,0.00006858429,0.0010023086,0.000006321072,0.0006593707,0.041586827,0.005104766,0.95104706],"study_design_scores_gemma":[0.00023890712,0.00006275031,0.00010637111,0.000009913029,0.0000026197013,0.000010589275,0.00033609415,0.0000013387846,0.000062414045,0.38115308,0.61781216,0.00020373642],"about_ca_topic_score_codex":0.0000050513618,"about_ca_topic_score_gemma":0.000104625855,"teacher_disagreement_score":0.9508433,"about_ca_system_score_codex":0.00012234227,"about_ca_system_score_gemma":0.000041737338,"threshold_uncertainty_score":0.999978},"labels":[],"label_agreement":null},{"id":"W2749582780","doi":"10.1002/acp.3342","title":"A Repeated Forced‐choice Line‐up Procedure Provides Suspect Bias Information with No Cost to Accuracy for Older Children and Adults","year":2017,"lang":"en","type":"article","venue":"Applied Cognitive Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Thompson Rivers University; University of Regina","funders":"American Psychology-Law Society","keywords":"Suspect; Psychology; Proxy (statistics); Identification (biology); Witness; Selection (genetic algorithm); Eyewitness identification; Task (project management); Social psychology; Developmental psychology; Artificial intelligence; Data mining; Machine learning; Computer science","score_opus":0.09937085279212711,"score_gpt":0.4285443863926708,"score_spread":0.3291735336005437,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2749582780","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9801833,0.00000838108,0.008392871,0.00085807766,0.0002824771,0.0034091254,0.00021186017,0.00006539005,0.0065885116],"genre_scores_gemma":[0.994561,0.000008038452,0.0015998293,0.0027289193,0.00014364919,0.00062611996,0.000091187336,0.000024613048,0.00021660843],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9976478,0.000036989986,0.00069031824,0.0008846321,0.00033208134,0.00040817764],"domain_scores_gemma":[0.9955044,0.0016155165,0.0008455664,0.00074867485,0.0010901131,0.00019576467],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009578254,0.00028891288,0.00044279534,0.00030611348,0.0005641966,0.00072194764,0.0006813743,0.00019427056,0.00006557637],"category_scores_gemma":[0.007931072,0.00020816497,0.00006763744,0.00020644657,0.00023700832,0.00083032536,0.00018402518,0.00020473373,0.00057306787],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0030192968,0.000079842015,0.013881099,0.0000070932247,0.000035652127,0.0000016021355,0.00090184185,0.000003541584,0.000065025924,0.00021105293,0.0055342936,0.97625965],"study_design_scores_gemma":[0.014923533,0.0019551269,0.9502949,0.00030348435,0.00013859775,0.00014470829,0.0015589175,0.00033242963,0.0010880589,0.011477598,0.016725905,0.0010567443],"about_ca_topic_score_codex":0.000050196366,"about_ca_topic_score_gemma":0.0001852774,"teacher_disagreement_score":0.9752029,"about_ca_system_score_codex":0.000024227043,"about_ca_system_score_gemma":0.000078301025,"threshold_uncertainty_score":0.9494808},"labels":[],"label_agreement":null},{"id":"W2750744528","doi":"10.1016/j.neuroimage.2017.08.071","title":"Neural congruence between intertemporal and interpersonal self-control: Evidence from delay and social discounting","year":2017,"lang":"en","type":"article","venue":"NeuroImage","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":61,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"National Institute on Drug Abuse; National Institute of Mental Health; National Institutes of Health; Foundation for the National Institutes of Health","keywords":"Psychology; Discounting; Temporal discounting; Neurocognitive; Intertemporal choice; Ventromedial prefrontal cortex; Interpersonal communication; Prefrontal cortex; Temporoparietal junction; Functional magnetic resonance imaging; Self-control; Delay discounting; Anterior cingulate cortex; Neural correlates of consciousness; Cognitive psychology; Impulsivity; Developmental psychology; Neuroscience; Cognition; Social psychology; Microeconomics","score_opus":0.16481347699509713,"score_gpt":0.409049675085582,"score_spread":0.24423619809048486,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2750744528","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99574894,0.000070346,0.0004173499,0.0028025738,0.00051837275,0.00011520529,0.000099447905,0.000045155717,0.00018261017],"genre_scores_gemma":[0.9986652,0.000007257559,0.00055338605,0.00039614135,0.0002841868,0.0000033213505,0.0000017359594,0.0000168787,0.000071849274],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9976642,0.0001560084,0.00055940566,0.0008375512,0.0004960101,0.00028678167],"domain_scores_gemma":[0.9969726,0.0016871624,0.00051692233,0.0005807118,0.00011556815,0.00012703497],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0011862417,0.00021799028,0.00044843156,0.00009698699,0.0008337333,0.003096333,0.001009654,0.00008691112,0.000046649748],"category_scores_gemma":[0.0017633003,0.00017221476,0.00009930774,0.000047202695,0.0004638299,0.0020377515,0.00067342166,0.00031850673,0.00005648264],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000057085676,0.000015118595,0.77252716,0.00000232785,0.000009565655,0.00008412173,0.0009537047,5.933764e-7,0.0010166895,0.000011255035,0.00064679014,0.22467558],"study_design_scores_gemma":[0.000619171,0.000096300166,0.98579186,0.00005061394,0.000050263665,0.000026098302,0.0002592094,0.007677884,0.00005216901,0.004132633,0.0009860413,0.00025776675],"about_ca_topic_score_codex":0.00052932266,"about_ca_topic_score_gemma":0.00015181776,"teacher_disagreement_score":0.22441782,"about_ca_system_score_codex":0.000021795955,"about_ca_system_score_gemma":0.00003489921,"threshold_uncertainty_score":0.9979386},"labels":[],"label_agreement":null},{"id":"W2751630361","doi":"10.1016/j.jebo.2017.08.016","title":"Preferred personal equilibrium and simple choices","year":2017,"lang":"en","type":"article","venue":"Journal of Economic Behavior & Organization","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Simple (philosophy); Mathematical economics; Economics; Parametric statistics; Connection (principal bundle); General equilibrium theory; Microeconomics; Mathematics; Epistemology; Statistics","score_opus":0.13365843635847,"score_gpt":0.40148038028014676,"score_spread":0.2678219439216768,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2751630361","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99769473,0.000035486955,0.00012644108,0.00043249136,0.0012947881,0.00009257702,0.000019250734,0.000010684404,0.00029355983],"genre_scores_gemma":[0.99887955,0.000021541038,0.00027726952,0.00004397422,0.00038166388,9.0851364e-7,0.0000049059436,0.000025968491,0.0003642462],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99806327,0.00005100137,0.0010702653,0.00031066898,0.00030490433,0.00019988643],"domain_scores_gemma":[0.9971817,0.00016953135,0.0015300169,0.0005001331,0.0004349876,0.00018359994],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0015354311,0.0001581504,0.00042132204,0.00025509042,0.0003505968,0.0017195162,0.00096058514,0.00012313446,0.0013820571],"category_scores_gemma":[0.0010523505,0.00011633969,0.000105766165,0.00005352341,0.00013340308,0.0020864254,0.0002757342,0.00017150944,0.00022002138],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000047347083,0.00013062105,0.7971525,0.0000023235589,0.000020354293,0.000026835138,0.0006594746,0.00009123263,0.011636434,0.00010401839,0.0026293993,0.18749942],"study_design_scores_gemma":[0.0015251165,0.00028383394,0.9668154,0.000026997897,0.00019160111,0.0005202792,0.00063667865,0.0008650559,0.007976542,0.009850318,0.010885215,0.00042293817],"about_ca_topic_score_codex":0.000027555492,"about_ca_topic_score_gemma":0.00003168795,"teacher_disagreement_score":0.18707648,"about_ca_system_score_codex":0.00015193736,"about_ca_system_score_gemma":0.00013575751,"threshold_uncertainty_score":0.9995308},"labels":[],"label_agreement":null},{"id":"W2751778071","doi":"10.1177/1745691617708630","title":"Constraints on Generality (COG): A Proposed Addition to All Empirical Papers","year":2017,"lang":"en","type":"article","venue":"Perspectives on Psychological Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":987,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"University of Illinois at Urbana-Champaign","keywords":"Generality; Cog; Computer science; Empirical research; Psychology; Programming language; Cognitive science; Artificial intelligence; Mathematics; Statistics","score_opus":0.3898253117507056,"score_gpt":0.564905420205657,"score_spread":0.17508010845495142,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2751778071","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.86475927,0.0000035086005,0.00019699945,0.010414686,0.0009034071,0.00036341348,0.00005929459,0.00006845665,0.12323097],"genre_scores_gemma":[0.9927462,0.0000055466335,0.002173069,0.004576932,0.0001357522,0.00002073975,8.547177e-7,0.000007514778,0.00033341307],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9944537,0.0001769099,0.00051546324,0.0024070237,0.0018267585,0.0006200905],"domain_scores_gemma":[0.9959424,0.0006117315,0.00034268957,0.0021397986,0.00035526155,0.00060808315],"candidate_categories":["metaresearch","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["sts","insufficient_payload"],"category_scores_codex":[0.0042078737,0.00026193107,0.00036792032,0.00030977908,0.0013686264,0.0016534256,0.0034587109,0.00014010543,0.0029986338],"category_scores_gemma":[0.013464925,0.0001613689,0.00019458166,0.0005594496,0.0032736391,0.0004625099,0.00031748522,0.0003628942,0.0027722584],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005037088,0.0014774651,0.002239332,3.4870914e-7,0.000006487783,0.00006325493,0.0014112196,0.00010352958,0.007014561,0.008756673,0.01225412,0.9661693],"study_design_scores_gemma":[0.0009701944,0.0031507513,0.8929378,0.00004053851,0.000010677816,0.000035831286,0.003645456,0.00024992993,0.0006124408,0.08172671,0.01591821,0.00070150435],"about_ca_topic_score_codex":0.000011887976,"about_ca_topic_score_gemma":0.000011966234,"teacher_disagreement_score":0.9654678,"about_ca_system_score_codex":0.00026535382,"about_ca_system_score_gemma":0.00007404015,"threshold_uncertainty_score":0.99993145},"labels":[],"label_agreement":null},{"id":"W2755120453","doi":"10.1002/bdm.2039","title":"Why Improvement Can Trump Consistent Strong Performance: The Role of Effort Perceptions","year":2017,"lang":"en","type":"article","venue":"Journal of Behavioral Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University","funders":"Wilfrid Laurier University","keywords":"Perception; Promotion (chess); Trait; Psychology; Investment (military); Social psychology; Computer science; Political science","score_opus":0.09829980618987051,"score_gpt":0.4108718380136088,"score_spread":0.3125720318237383,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2755120453","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9961573,0.00010860248,0.0008129792,0.0003728289,0.0017571413,0.00022343377,0.000035335248,0.000008568489,0.00052384404],"genre_scores_gemma":[0.99558574,0.000048040565,0.003908225,0.0001537861,0.00019893203,0.0000050825565,6.032844e-7,0.000025732244,0.00007383615],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99397427,0.000089960704,0.0026304754,0.0004125145,0.002478214,0.00041459184],"domain_scores_gemma":[0.9920963,0.0007013901,0.0039297664,0.0017632378,0.001306504,0.0002028263],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0046743006,0.00029622085,0.0008062332,0.00054270856,0.0012304209,0.0011812237,0.0030989654,0.00016016034,0.0006828564],"category_scores_gemma":[0.0007826372,0.00017480567,0.0007559717,0.00022546422,0.00039623346,0.00097244827,0.0006703504,0.0005805074,0.00003955479],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016761376,0.00018930582,0.104556344,0.0000014388925,0.000013758859,0.000019704643,0.00038758692,0.00046858733,0.0017809995,0.000047842153,0.0013257501,0.8910411],"study_design_scores_gemma":[0.0029051306,0.0033591364,0.8791837,0.0012227229,0.0006390121,0.000759557,0.019809216,0.0056731063,0.0028571263,0.05355115,0.0291111,0.0009290085],"about_ca_topic_score_codex":0.00008317038,"about_ca_topic_score_gemma":0.00020950513,"teacher_disagreement_score":0.89011204,"about_ca_system_score_codex":0.00020841237,"about_ca_system_score_gemma":0.00023280732,"threshold_uncertainty_score":0.99985564},"labels":[],"label_agreement":null},{"id":"W2756422654","doi":"10.1111/bjdp.12210","title":"‘Things aren't so bad!’: Preschoolers overpredict the emotional intensity of negative outcomes","year":2017,"lang":"en","type":"article","venue":"British Journal of Developmental Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Psychology; Developmental psychology; Cognition; Neglect; Cognitive psychology; Task (project management)","score_opus":0.10399159574448777,"score_gpt":0.408287172668893,"score_spread":0.30429557692440523,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2756422654","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99097496,0.00007986254,0.0005604701,0.0026659942,0.0026622778,0.00009195614,0.000038089685,0.000005920541,0.0029204572],"genre_scores_gemma":[0.99267834,0.00006976104,0.0054203207,0.0014709773,0.00008768628,0.0000011949353,0.000001079712,0.000010982077,0.0002596274],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.996896,0.00015355114,0.0014606692,0.0003290496,0.0009169795,0.00024372175],"domain_scores_gemma":[0.995905,0.0007012699,0.0020929778,0.0004118172,0.0007454708,0.00014346874],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031792703,0.00015786121,0.0006090503,0.00019160661,0.00067578506,0.0006119334,0.0021509323,0.00013212119,0.00050407945],"category_scores_gemma":[0.005942692,0.000116570256,0.0003102941,0.00011174278,0.0008507281,0.00095935824,0.00036774424,0.0005351356,0.00007880432],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023642657,0.00020041961,0.29514688,0.0000012443172,0.000119700126,0.0002523452,0.00066375954,0.000012362846,0.00024932885,0.000037408347,0.054109775,0.64897037],"study_design_scores_gemma":[0.0010269387,0.00010035153,0.9550061,0.0001288918,0.000016233003,0.003712077,0.00070577813,0.000012547117,0.00013678313,0.034597635,0.0044294107,0.00012724022],"about_ca_topic_score_codex":0.00008967536,"about_ca_topic_score_gemma":0.0000697645,"teacher_disagreement_score":0.65985924,"about_ca_system_score_codex":0.00007742689,"about_ca_system_score_gemma":0.00024600088,"threshold_uncertainty_score":0.7114387},"labels":[],"label_agreement":null},{"id":"W2760371854","doi":"10.1016/j.cognition.2017.09.012","title":"Reasoning strategies modulate gender differences in emotion processing","year":2017,"lang":"en","type":"article","venue":"Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":22,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières; Université du Québec à Montréal","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Counterexample; Psychology; Cognitive psychology; Valence (chemistry); Information processing; Associative property; Cognition; Dual (grammatical number); Context (archaeology); Developmental psychology; Mathematics; Linguistics","score_opus":0.2954358905163347,"score_gpt":0.42821707162867934,"score_spread":0.13278118111234466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2760371854","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97663945,0.00003779877,0.004447819,0.0000958239,0.00027108644,0.00011307471,0.0000061588967,0.000032042066,0.018356765],"genre_scores_gemma":[0.99915016,0.000010402928,0.0006221637,0.00002679826,0.00006526692,0.0000096805925,0.000006348609,0.000007590752,0.000101606856],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9985357,0.00006344123,0.00040768777,0.00040251625,0.000404652,0.00018601511],"domain_scores_gemma":[0.99886024,0.00011505474,0.00039775527,0.00038255283,0.00019465102,0.000049747985],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0010750816,0.00011177353,0.00020038187,0.00019731518,0.00049704715,0.0023607565,0.00046010443,0.00008966844,0.00012736603],"category_scores_gemma":[0.000996269,0.000088734305,0.000052470426,0.00010930409,0.00010452189,0.0017752394,0.0000930646,0.00012930464,0.00019480818],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022118043,0.0000449413,0.034593828,0.0000035968792,0.0000015772746,0.000011931396,0.00037942364,0.00006047438,0.00034819843,0.00022018515,0.000047186033,0.96426654],"study_design_scores_gemma":[0.00026843027,0.000022372511,0.61774296,0.00011169865,0.0000084232415,0.0000064234064,0.0016653418,0.0112669375,0.00018781495,0.36851236,0.00006687848,0.00014038477],"about_ca_topic_score_codex":0.000016620099,"about_ca_topic_score_gemma":0.00007043946,"teacher_disagreement_score":0.96412617,"about_ca_system_score_codex":0.000029244893,"about_ca_system_score_gemma":0.000063623906,"threshold_uncertainty_score":0.99867487},"labels":[],"label_agreement":null},{"id":"W2762465986","doi":"10.1016/j.dcn.2017.09.008","title":"Computational neuroscience across the lifespan: Promises and pitfalls","year":2017,"lang":"en","type":"review","venue":"Developmental Cognitive Neuroscience","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"National Institute on Aging; National Institute of Mental Health; Deutsche Forschungsgemeinschaft","keywords":"Computational model; Popularity; Computational neuroscience; Psychology; Cognitive science; Reinforcement learning; Latent variable; Selection (genetic algorithm); Developmental cognitive neuroscience; Artificial intelligence; Cognitive psychology; Neuroscience; Neuroimaging; Machine learning; Computer science; Functional neuroimaging; Social psychology","score_opus":0.5004399576262732,"score_gpt":0.527927025127613,"score_spread":0.02748706750133978,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2762465986","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.034718044,0.94536924,0.0014886374,0.00050197646,0.0077785784,0.0043865438,0.0018312047,0.00020721239,0.0037185843],"genre_scores_gemma":[0.028728157,0.96554637,0.0005083909,0.0024006972,0.00015068,0.00020918595,0.000024688981,0.000075797645,0.002356024],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9928943,0.0004717337,0.0014436091,0.0023226372,0.002088043,0.00077966135],"domain_scores_gemma":[0.9933881,0.003694863,0.0015165884,0.00065762707,0.000404007,0.00033877668],"candidate_categories":["metaresearch","metaepi_narrow","sts","scholarly_communication"],"consensus_categories":["sts"],"category_scores_codex":[0.0037854959,0.0006803517,0.0013829947,0.00030863463,0.0033789081,0.0049157594,0.0041411836,0.00018488216,0.000029552884],"category_scores_gemma":[0.013082495,0.00040587972,0.00033003237,0.0010161297,0.003359256,0.0011372971,0.0025892,0.0006858811,0.00041597628],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000059149866,0.000048021386,0.00020785378,0.000048297148,0.000002199501,0.000060910505,0.00020022067,0.0000027966464,0.0000015989277,0.000027773422,0.00030472042,0.9990897],"study_design_scores_gemma":[0.00019817406,0.000086627915,0.006214959,0.001360111,0.000053881147,0.0008190209,0.00024189099,0.00016985298,0.000002301923,0.0019317579,0.98827404,0.0006473601],"about_ca_topic_score_codex":0.000008526228,"about_ca_topic_score_gemma":0.000014080566,"teacher_disagreement_score":0.99844235,"about_ca_system_score_codex":0.00009950328,"about_ca_system_score_gemma":0.0012756884,"threshold_uncertainty_score":0.9998393},"labels":[],"label_agreement":null},{"id":"W2765347957","doi":"","title":"Do Evaluation Frames Improve the Quality of Conditional Probability Judgment","year":2007,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Conditional probability; Event (particle physics); Coherence (philosophical gambling strategy); Odds; Psychology; Cognitive psychology; Econometrics; Mathematics; Statistics","score_opus":0.141269675882284,"score_gpt":0.38668109792316613,"score_spread":0.24541142204088212,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2765347957","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.982308,0.00009386778,0.0014649925,0.0008454233,0.00035212975,0.0006287747,0.0027541404,0.00006777966,0.011484904],"genre_scores_gemma":[0.99805474,0.000001449124,0.0009854368,0.00038770575,0.00011746523,0.000022757748,0.00020006382,0.000021815596,0.00020854876],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9939644,0.00038183053,0.001960123,0.0007400471,0.002567943,0.00038570623],"domain_scores_gemma":[0.9935186,0.0038264648,0.0008381584,0.0011350256,0.00045988083,0.0002218892],"candidate_categories":["metaresearch","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.013558525,0.00024836406,0.00041703662,0.000203585,0.00021847243,0.0018108641,0.0012496217,0.00018344645,0.0020759585],"category_scores_gemma":[0.008711497,0.00015439832,0.0003642218,0.0006884928,0.0003766088,0.003111642,0.00039563922,0.00041224752,0.0013811459],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033823558,0.0005783125,0.28710708,0.000011205758,0.000028814851,0.000002948811,0.00007841679,0.00010041806,0.0003582444,0.009948607,0.002900054,0.69854766],"study_design_scores_gemma":[0.0004379283,0.00008679814,0.12622127,0.000018464714,0.000015359192,0.000002852826,0.00021296974,0.00016305513,0.0021075169,0.8402876,0.03022248,0.0002236676],"about_ca_topic_score_codex":0.0000045888573,"about_ca_topic_score_gemma":0.000004972082,"teacher_disagreement_score":0.830339,"about_ca_system_score_codex":0.00009435503,"about_ca_system_score_gemma":0.000269125,"threshold_uncertainty_score":0.99963856},"labels":[],"label_agreement":null},{"id":"W2767238759","doi":"","title":"The Influence of Individual Differences on the Role of Information Quantity in Statistical Inferences","year":2007,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Science Foundation","keywords":"Psychology; Population; Perception; Statistics; Correlation; Social psychology; Cognitive psychology; Mathematics; Demography","score_opus":0.04788384092498254,"score_gpt":0.3046041332229969,"score_spread":0.25672029229801435,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2767238759","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9937487,0.000032196825,0.00014599852,0.0001885616,0.00007183095,0.00017565329,0.0014171309,0.000019799676,0.0042001167],"genre_scores_gemma":[0.9996115,0.000009232041,0.00018312715,0.0001282005,0.000013773688,0.0000045994493,0.000028725823,0.000006767413,0.000014072122],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9964937,0.0001629749,0.0014822904,0.00023047725,0.0013242303,0.00030630268],"domain_scores_gemma":[0.9895762,0.00905754,0.0006247119,0.000505048,0.00012966992,0.000106833715],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0034042373,0.00017316647,0.00030609564,0.00030934816,0.00015932563,0.0016485149,0.0018085975,0.00011253526,0.00011970991],"category_scores_gemma":[0.008055129,0.00008645615,0.00009538778,0.0008454204,0.00048047386,0.0036331748,0.00036014753,0.00039233724,0.00043459918],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001372714,0.00008006447,0.6894341,0.000002109939,0.0000054906127,0.0000011038011,0.000111132125,0.000044795826,0.00001245094,0.036594465,0.000099787816,0.2734772],"study_design_scores_gemma":[0.00011189873,0.00012036352,0.65782666,0.000042309268,0.000003344914,9.953005e-7,0.0008063647,0.000067036264,0.0005820591,0.33300218,0.007335134,0.000101661906],"about_ca_topic_score_codex":0.000018939318,"about_ca_topic_score_gemma":0.000034638317,"teacher_disagreement_score":0.2964077,"about_ca_system_score_codex":0.000014408631,"about_ca_system_score_gemma":0.00013661536,"threshold_uncertainty_score":0.99938786},"labels":[],"label_agreement":null},{"id":"W2769277555","doi":"","title":"Clinging to Beliefs: A Constraint-satisfaction Model","year":2001,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Mental Health; Social Sciences and Humanities Research Council of Canada","keywords":"Psychology; Test (biology); Social psychology; Counterintuitive; Constraint (computer-aided design); Epistemology; Philosophy","score_opus":0.0840805153695391,"score_gpt":0.32985458232491227,"score_spread":0.24577406695537318,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2769277555","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95583117,0.000039930972,0.015192465,0.0014105516,0.0003364024,0.00026742916,0.0011918021,0.0003681312,0.02536211],"genre_scores_gemma":[0.98938364,0.000011203036,0.0065581845,0.0019371525,0.00016710756,0.00001615956,0.000058283396,0.00006599793,0.0018022599],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99604505,0.00007881139,0.001228844,0.000987945,0.0010334668,0.0006258966],"domain_scores_gemma":[0.99729747,0.00074365374,0.00027967777,0.0008832272,0.00012701852,0.0006689321],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0010522872,0.00035475142,0.00046549193,0.0006455571,0.00030149653,0.0053983494,0.0010464455,0.00020141639,0.0012388187],"category_scores_gemma":[0.002435615,0.00030014978,0.00030672987,0.0011937045,0.00011111582,0.0058494615,0.00046855115,0.000460718,0.019077582],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010870889,0.00009747805,0.1857187,0.0000018830577,0.000010185172,0.000057302273,0.000052627634,0.0028705974,0.00013506395,0.00094366854,0.00835426,0.8016495],"study_design_scores_gemma":[0.0008860806,0.00021431367,0.011960215,0.00015699198,0.000023504525,0.0001633476,0.000358442,0.019397894,0.0004826325,0.5651033,0.3999833,0.0012700208],"about_ca_topic_score_codex":0.0000038903167,"about_ca_topic_score_gemma":0.0000057999478,"teacher_disagreement_score":0.8003795,"about_ca_system_score_codex":0.00007100489,"about_ca_system_score_gemma":0.00017106348,"threshold_uncertainty_score":0.99994504},"labels":[],"label_agreement":null},{"id":"W2772399711","doi":"10.1002/bdm.2070","title":"Maximizing Scales Do Not Reliably Predict Maximizing Behavior in Decisions from Experience","year":2017,"lang":"en","type":"article","venue":"Journal of Behavioral Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"National Science Foundation of Sri Lanka; National Science Foundation","keywords":"Maximization; Stochastic game; Utility maximization; Sampling (signal processing); Psychology; Cognitive psychology; Computer science; Econometrics; Social psychology; Microeconomics; Economics; Mathematical economics","score_opus":0.19936453230406184,"score_gpt":0.45244649938424725,"score_spread":0.2530819670801854,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2772399711","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98663306,0.0003798744,0.00679341,0.00019116372,0.005163692,0.00036096244,0.00010449916,0.00004066863,0.0003326544],"genre_scores_gemma":[0.9149145,0.00015056494,0.08424159,0.00012193409,0.0004078764,0.000021591079,0.0000018150345,0.00008048302,0.000059680424],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9871762,0.00032853178,0.0054822857,0.0014287515,0.0046098367,0.0009744418],"domain_scores_gemma":[0.9837966,0.0053599803,0.0053948937,0.0034677903,0.0013822535,0.00059848296],"candidate_categories":["metaresearch","metaepi_narrow","sts","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.00679457,0.0007055794,0.0018653543,0.0021608896,0.0014125076,0.005093642,0.007011964,0.0005605382,0.00083517836],"category_scores_gemma":[0.01268012,0.0005566853,0.0010958329,0.00074640673,0.0004982959,0.0044173556,0.0018302122,0.0014743209,0.00026507757],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007426606,0.00044454806,0.19687238,7.1511624e-7,0.0000071618747,0.0016430716,0.0007321888,0.00040228156,0.0019371577,0.000026430198,0.0007871262,0.7964043],"study_design_scores_gemma":[0.0034641826,0.0006373414,0.9123949,0.002427193,0.00020502023,0.0006899352,0.0050519495,0.0014291904,0.00083765027,0.06753544,0.0041638347,0.0011633754],"about_ca_topic_score_codex":0.00020949401,"about_ca_topic_score_gemma":0.00041818075,"teacher_disagreement_score":0.7952409,"about_ca_system_score_codex":0.0005047213,"about_ca_system_score_gemma":0.00028648123,"threshold_uncertainty_score":0.9998875},"labels":[],"label_agreement":null},{"id":"W2776244342","doi":"10.1037/xge0000377","title":"Hedonic nondurability revisited: A case for two types.","year":2017,"lang":"en","type":"article","venue":"Journal of Experimental Psychology General","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Booth University College","funders":"John Templeton Foundation","keywords":"Happiness; Categorization; Preference; Differential (mechanical device); Psychology; Durability; Adaptation (eye); Differential effects; Econometrics; Social psychology; Economics; Computer science; Microeconomics; Artificial intelligence; Engineering","score_opus":0.2705525379296771,"score_gpt":0.5584231771414976,"score_spread":0.2878706392118205,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2776244342","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9919038,0.0007030333,0.0005930771,0.0011106856,0.0032905922,0.00015562182,0.000023597324,0.0000062521112,0.002213343],"genre_scores_gemma":[0.9899627,0.000008074451,0.008181215,0.00072253484,0.0007229573,0.0000055865785,8.736282e-7,0.000015415102,0.00038067476],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99757016,0.0001653758,0.0012069099,0.0004288403,0.00035563065,0.00027310572],"domain_scores_gemma":[0.99652195,0.00031325084,0.0014432794,0.0011697593,0.00035281898,0.00019895284],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036176788,0.0001740779,0.00054425636,0.00020302762,0.00056861003,0.00041831288,0.0013008252,0.00012362323,0.000573324],"category_scores_gemma":[0.0011326907,0.00012512328,0.0004548921,0.0000704139,0.00026965895,0.0005555599,0.00015562917,0.00027745176,0.000100321966],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0030671426,0.0023300706,0.027743276,0.00000494888,0.00019529417,0.004465148,0.0011658185,0.00014986431,0.19427897,0.0015124255,0.18930773,0.5757793],"study_design_scores_gemma":[0.04299039,0.013006871,0.040845253,0.00020984284,0.0004103216,0.13864489,0.004104466,0.0042320336,0.10182435,0.3248462,0.325919,0.0029663448],"about_ca_topic_score_codex":0.000019033094,"about_ca_topic_score_gemma":0.000014954275,"teacher_disagreement_score":0.572813,"about_ca_system_score_codex":0.000090684975,"about_ca_system_score_gemma":0.0000656575,"threshold_uncertainty_score":0.62774956},"labels":[],"label_agreement":null},{"id":"W2782977396","doi":"10.1007/s00199-020-01319-4","title":"Competitive equilibria in a comonotone market","year":2020,"lang":"en","type":"article","venue":"Economic Theory","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Complete market; Economics; Uniqueness; Mathematical economics; Competitive equilibrium; Incomplete markets; Microeconomics; Allocative efficiency; Mathematics","score_opus":0.11070953149674458,"score_gpt":0.3720336665161265,"score_spread":0.26132413501938195,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2782977396","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8608371,0.000060062128,0.00023147314,0.0015159241,0.00050726894,0.00015198173,0.00006430539,0.000044090764,0.13658777],"genre_scores_gemma":[0.9970706,0.000009098218,0.00035742237,0.0013780714,0.00015102031,0.000008695201,0.000002876759,0.000019158182,0.0010030747],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9977341,0.00034882536,0.0008486279,0.0006524242,0.0001433499,0.00027261517],"domain_scores_gemma":[0.99667716,0.0023703452,0.00024426353,0.00049320975,0.000025592686,0.00018940849],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0031747534,0.00017055357,0.00047893298,0.00017669461,0.00005325639,0.00023359818,0.0009522203,0.0000859622,0.011653878],"category_scores_gemma":[0.00091068755,0.00015254623,0.00015022386,0.00016233808,0.00015195647,0.00037530588,0.0003222354,0.00019720207,0.0076283435],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014314331,0.00014081868,0.01702487,0.000003898877,0.00003134362,0.000102387254,0.0031780547,0.00080052804,0.0004918312,0.32538265,0.045989472,0.6054227],"study_design_scores_gemma":[0.001334392,0.00013864829,0.0132561205,0.000022904977,0.000009535852,0.000013385683,0.0033564153,0.014522843,0.00020759947,0.7570899,0.20958269,0.0004655694],"about_ca_topic_score_codex":0.000015842741,"about_ca_topic_score_gemma":0.00006360334,"teacher_disagreement_score":0.6049571,"about_ca_system_score_codex":0.00012731882,"about_ca_system_score_gemma":0.00010323146,"threshold_uncertainty_score":0.99314433},"labels":[],"label_agreement":null},{"id":"W2787233800","doi":"10.3758/s13423-018-1460-7","title":"Characterizing belief bias in syllogistic reasoning: A hierarchical Bayesian meta-analysis of ROC data","year":2018,"lang":"en","type":"review","venue":"Psychonomic Bulletin & Review","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Max-Planck-Gesellschaft; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Psychology; Syllogism; Meta-analysis; Cognitive psychology; Bayesian probability; Variance (accounting); Artifact (error); Multilevel model; Social psychology; Statistics; Artificial intelligence; Computer science; Epistemology; Mathematics","score_opus":0.6613623943449132,"score_gpt":0.5268100067898177,"score_spread":0.13455238755509547,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2787233800","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000009662018,0.99370134,0.0003385785,0.0013628434,0.00067919545,0.0013807279,0.00126285,0.000036821486,0.0012279747],"genre_scores_gemma":[0.00002652142,0.9936636,0.0035924225,0.0010318612,0.00019575795,0.00019569868,0.0006631435,0.00009729299,0.0005336904],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.98321354,0.0027584096,0.008527794,0.0036006677,0.0011387445,0.00076083554],"domain_scores_gemma":[0.9779924,0.0063332324,0.006062546,0.008985113,0.00025682995,0.00036986702],"candidate_categories":["metaresearch","metaepi_narrow","metaepi_broad","open_science","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.023782331,0.001162203,0.017187802,0.0022093782,0.00012648196,0.00042514008,0.008664771,0.0005521081,0.012989475],"category_scores_gemma":[0.009623731,0.0007778862,0.006511566,0.00400142,0.00039326586,0.00017901066,0.0016472122,0.0010733841,0.003374299],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009114744,0.00017035253,0.000008329263,0.0025878954,0.0113168135,0.000016514274,0.000015354386,0.0000010640917,1.818781e-8,0.00005750778,0.03134284,0.9544742],"study_design_scores_gemma":[0.00008276154,0.00004208707,0.000010255997,0.010264431,0.1592561,0.000030629326,0.0000044480394,0.00007131056,1.0314994e-8,0.00038250384,0.82927513,0.0005803068],"about_ca_topic_score_codex":0.00007885929,"about_ca_topic_score_gemma":0.00008871963,"teacher_disagreement_score":0.9538939,"about_ca_system_score_codex":0.00018952035,"about_ca_system_score_gemma":0.00043206412,"threshold_uncertainty_score":0.9994672},"labels":[],"label_agreement":null},{"id":"W2788076187","doi":"10.1007/978-3-319-72419-5_4","title":"Financialization and Consumer Behavior","year":2018,"lang":"en","type":"book-chapter","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg; Canadian Mennonite University","funders":"","keywords":"Bounded rationality; Financialization; Behavioral economics; Rationality; Debt; Context (archaeology); Heuristics; Consumerism; Consumption (sociology); Homo economicus; Consumer behaviour; Economics; Positive economics; Psychology; Sociology; Microeconomics; Social psychology; Political science; Finance; Social science; Computer science; Geography","score_opus":0.1834089141211341,"score_gpt":0.3944122876004854,"score_spread":0.2110033734793513,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2788076187","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.066261895,0.00031563465,0.0008594336,0.00009489573,0.001747519,0.00037016964,0.00011995479,0.00008596365,0.93014455],"genre_scores_gemma":[0.015613235,0.00012135301,0.0010988222,0.00028687547,0.00021525905,0.0000073074293,0.000018770523,0.000042615324,0.98259574],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9976505,0.000015612672,0.00079722755,0.00074627646,0.0006269413,0.00016344049],"domain_scores_gemma":[0.9979645,0.0003505346,0.00041532828,0.0007201604,0.00042887518,0.000120616394],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0008225263,0.0002709398,0.00047603587,0.0003418795,0.00014301049,0.00042349624,0.0004347589,0.00043251165,0.020213945],"category_scores_gemma":[0.00034668206,0.00020296448,0.00013369716,0.000046509565,0.0003068054,0.00018373739,0.00023820448,0.0001533383,0.0064251046],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001086272,0.00001553469,0.0005623611,0.0000010784224,0.000004997871,0.000018745544,0.000061184226,1.7077818e-7,0.0000045171746,0.024489477,0.12500787,0.8498232],"study_design_scores_gemma":[0.0001025674,0.00005172411,0.00040621572,0.00002512807,0.00004890044,0.000020680904,0.000013914704,0.000018642455,0.0000084409685,0.27866846,0.72038805,0.00024723017],"about_ca_topic_score_codex":0.000011391067,"about_ca_topic_score_gemma":0.00010914358,"teacher_disagreement_score":0.84957594,"about_ca_system_score_codex":0.000037041602,"about_ca_system_score_gemma":0.000090426365,"threshold_uncertainty_score":0.9943485},"labels":[],"label_agreement":null},{"id":"W2789390553","doi":"10.3390/jrfm18100577","title":"External Habit Persistence and Individual Portfolio Choice","year":2025,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Persistence (discontinuity); Portfolio; Habit; Economics; Psychology; Social psychology; Financial economics; Engineering","score_opus":0.0580336189928059,"score_gpt":0.33114800135351635,"score_spread":0.27311438236071045,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2789390553","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9823272,0.0013720249,0.01337539,0.00016681149,0.000770213,0.000066702145,0.0000090045005,0.000003888396,0.001908722],"genre_scores_gemma":[0.9941907,0.0011979815,0.003521722,0.00026151064,0.00011282911,9.983219e-7,1.296185e-7,0.0000032978305,0.0007108255],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99838245,0.000051082865,0.00068508706,0.0002329646,0.00049999054,0.00014844627],"domain_scores_gemma":[0.998775,0.0003381563,0.0004753483,0.0001808045,0.0001402824,0.00009038598],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002110788,0.00010920586,0.0002946145,0.00052324816,0.00019228613,0.00037006597,0.00042634096,0.00005440658,0.000036601807],"category_scores_gemma":[0.0007498532,0.000079916324,0.00011033022,0.00031925584,0.00009066608,0.00028642497,0.0002875631,0.00020123004,0.00000770363],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000453814,0.000039090002,0.10415307,0.0000031860613,0.0000078899975,0.000050113737,0.00013244693,0.000017846884,0.0000022582135,0.0011059293,0.0034442244,0.89099854],"study_design_scores_gemma":[0.00057790114,0.000107997555,0.7505548,0.00009190058,0.00010901767,0.000030195159,0.0005218794,0.000039655155,0.000005895299,0.07950674,0.16836303,0.00009097647],"about_ca_topic_score_codex":0.000016990158,"about_ca_topic_score_gemma":0.000022444527,"teacher_disagreement_score":0.8909076,"about_ca_system_score_codex":0.00002381723,"about_ca_system_score_gemma":0.000038663602,"threshold_uncertainty_score":0.35685548},"labels":[],"label_agreement":null},{"id":"W2789484689","doi":"10.1016/j.neuropsychologia.2018.03.010","title":"Alternative outcomes create biased expectations regarding the received outcome: Evidence from event-related potentials","year":2018,"lang":"en","type":"article","venue":"Neuropsychologia","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Azrieli Foundation","keywords":"Outcome (game theory); Psychology; Negativity effect; Social psychology; Economics","score_opus":0.2839900037486072,"score_gpt":0.4785626881444575,"score_spread":0.1945726843958503,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2789484689","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9857037,0.000065571374,0.0030990432,0.0033458988,0.005103963,0.00032729318,0.000052831907,0.0001456216,0.0021560525],"genre_scores_gemma":[0.9959094,0.00001997816,0.0009347051,0.0013078743,0.00017848262,0.000023175267,0.0000044269777,0.000029765823,0.0015922227],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99499303,0.0009878281,0.001498149,0.0011746073,0.0009485932,0.0003977694],"domain_scores_gemma":[0.9904857,0.006163121,0.0008784879,0.0017763675,0.0005579722,0.00013833474],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0022154415,0.00030925876,0.00053539523,0.0002888997,0.0006150469,0.0007019343,0.0022036412,0.00014594245,0.001708077],"category_scores_gemma":[0.0153640825,0.00017616368,0.0003570786,0.00091396086,0.00046897714,0.00057326036,0.00028516492,0.0004024979,0.0052340943],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048602538,0.00038646703,0.5685122,9.865299e-7,0.00017607161,0.00023838408,0.0053615584,0.0008074333,0.015894042,0.00026913386,0.030874023,0.37699366],"study_design_scores_gemma":[0.0012216414,0.00039070396,0.905977,0.00008194371,0.00010301853,0.000027576389,0.0016153416,0.0022699644,0.0012489569,0.08453783,0.0020133571,0.0005126559],"about_ca_topic_score_codex":0.00015420465,"about_ca_topic_score_gemma":0.000049507187,"teacher_disagreement_score":0.37648103,"about_ca_system_score_codex":0.00005388392,"about_ca_system_score_gemma":0.000036782316,"threshold_uncertainty_score":0.9992045},"labels":[],"label_agreement":null},{"id":"W2790092298","doi":"10.1037/pag0000223","title":"Aging and altruism in intertemporal choice.","year":2018,"lang":"en","type":"article","venue":"Psychology and Aging","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Ontario Ministry of Research and Innovation; Natural Sciences and Engineering Research Council of Canada","keywords":"Altruism (biology); Psychology; PsycINFO; Affect (linguistics); Context (archaeology); Intertemporal choice; Social psychology; Demand characteristics; Economics; Microeconomics; MEDLINE","score_opus":0.15750733033056638,"score_gpt":0.4801107901499552,"score_spread":0.32260345981938887,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2790092298","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9912946,0.0003496033,0.00037715826,0.0033753132,0.0007815976,0.00004332413,0.0000012566195,0.000018813233,0.0037582892],"genre_scores_gemma":[0.9965772,0.00003424861,0.0005654983,0.0024279545,0.00014891803,0.0000021846606,4.4184506e-7,0.000006114972,0.00023741911],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99872893,0.00008224707,0.0003684162,0.00049847434,0.00010795037,0.00021400762],"domain_scores_gemma":[0.99913013,0.00039553214,0.00009916162,0.00026438225,0.00003728474,0.000073537136],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014293347,0.00009938605,0.00020601456,0.00030813916,0.00012555656,0.00014314658,0.0002366554,0.00007545432,0.00014472521],"category_scores_gemma":[0.00025784312,0.00007862475,0.000024324432,0.0002091431,0.00026834966,0.00022914569,0.00013042158,0.00016694862,0.00010793487],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009594246,0.000017936502,0.30702677,6.324343e-7,0.0000017994433,0.000011869921,0.0005525304,2.3537858e-7,0.00025519243,0.00010481058,0.0011724689,0.69084615],"study_design_scores_gemma":[0.0010101902,0.0001283318,0.72756344,0.000075142,0.00000669247,0.00014064288,0.0004548422,0.0007367725,0.000079184865,0.16655284,0.102984555,0.00026735154],"about_ca_topic_score_codex":0.000042076805,"about_ca_topic_score_gemma":0.0001658629,"teacher_disagreement_score":0.6905788,"about_ca_system_score_codex":0.0000069300386,"about_ca_system_score_gemma":0.000007742386,"threshold_uncertainty_score":0.3206224},"labels":[],"label_agreement":null},{"id":"W2791058789","doi":"10.1162/jocn_a_01253","title":"Modulating Episodic Memory Alters Risk Preference during Decision-making","year":2018,"lang":"en","type":"article","venue":"Journal of Cognitive Neuroscience","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Episodic memory; Psychology; Task (project management); Cognitive psychology; Preference; Cognition; Social psychology; Neuroscience","score_opus":0.1298668383265355,"score_gpt":0.4015516695397181,"score_spread":0.2716848312131826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2791058789","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96106637,0.00004687317,0.034233253,0.00005950774,0.0029874346,0.00013196995,0.000020063508,0.00002152826,0.00143298],"genre_scores_gemma":[0.9962347,0.00003643866,0.0027780123,0.00040419534,0.0004300627,0.0000016597899,7.57512e-8,0.000020120293,0.00009472729],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99419135,0.00039727174,0.0017815768,0.00077835185,0.002325658,0.00052578334],"domain_scores_gemma":[0.98782164,0.0064405734,0.0027534103,0.00051540055,0.0021455842,0.0003233951],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.005053932,0.0002704995,0.0005545083,0.0009308305,0.00088485505,0.00083167996,0.001877061,0.000088167435,0.00021654513],"category_scores_gemma":[0.053677086,0.00019825426,0.00030223015,0.0014584281,0.0008379187,0.0018853954,0.00046632407,0.00061197823,0.00019419687],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035683025,0.000120040735,0.027079633,0.0000017015443,0.000004843284,0.00016189943,0.00085720536,0.00090428744,0.008365827,0.000011250267,0.00021636877,0.96192014],"study_design_scores_gemma":[0.0024905284,0.002534296,0.83320147,0.0022096988,0.00014136366,0.0020102407,0.0032644158,0.023535997,0.015101275,0.11371243,0.00075685116,0.0010414667],"about_ca_topic_score_codex":0.0000045246943,"about_ca_topic_score_gemma":0.0000110444835,"teacher_disagreement_score":0.9608787,"about_ca_system_score_codex":0.00008794097,"about_ca_system_score_gemma":0.00024092245,"threshold_uncertainty_score":0.9542942},"labels":[],"label_agreement":null},{"id":"W2793054157","doi":"10.1177/1747021818763573","title":"Predicting our own and others’ future preferences: The role of social distance","year":2018,"lang":"en","type":"article","venue":"Quarterly Journal of Experimental Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Presentism; Psychology; Perspective (graphical); Social psychology; Phenomenon; Social distance; Preference; Cognitive psychology; Computer science; Statistics","score_opus":0.06693906006831755,"score_gpt":0.42642249283258454,"score_spread":0.359483432764267,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2793054157","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99381155,0.0008649048,0.00019875448,0.0007697942,0.0014792447,0.000062670944,0.000009886221,0.000004669931,0.002798539],"genre_scores_gemma":[0.99845856,0.0000050997683,0.00039565103,0.00017753264,0.00091418653,0.0000015531855,1.9830986e-7,0.000008538642,0.00003865127],"study_design_codex":"design_other","study_design_gemma":"qualitative","domain_scores_codex":[0.99808407,0.00019451843,0.00087968865,0.00024420157,0.0004192471,0.00017826434],"domain_scores_gemma":[0.9983374,0.00013635201,0.0009895741,0.000261692,0.00020290901,0.00007207406],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011918533,0.00012525216,0.00033267308,0.00012297987,0.00018882603,0.00011176779,0.00072191877,0.00010527673,0.00019467981],"category_scores_gemma":[0.000040171944,0.00007175837,0.00013055054,0.00016053484,0.00030733613,0.00027624314,0.000030096508,0.00020208737,0.000023786919],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00077684707,0.00040211744,0.024004396,9.542485e-7,0.000055520384,0.000009090067,0.052162584,4.066414e-7,0.040793505,0.0010610698,0.005347728,0.87538576],"study_design_scores_gemma":[0.0032739474,0.014519616,0.061654046,0.00007041711,0.000060694576,0.0008608075,0.6613393,0.00015947517,0.009414951,0.17595853,0.07220008,0.00048813722],"about_ca_topic_score_codex":0.0000062125832,"about_ca_topic_score_gemma":0.00001664634,"teacher_disagreement_score":0.87489766,"about_ca_system_score_codex":0.000020113506,"about_ca_system_score_gemma":0.000028242093,"threshold_uncertainty_score":0.29262215},"labels":[],"label_agreement":null},{"id":"W2793286537","doi":"10.1002/jcpy.1031","title":"If You Are Going to Pay Within the Next 24 Hours, Press 1: Automatic Planning Prompt Reduces Credit Card Delinquency","year":2018,"lang":"en","type":"article","venue":"Journal of Consumer Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Rotman School of Management, University of Toronto; University of Toronto","keywords":"Concreteness; Juvenile delinquency; Psychology; Action (physics); Credit card; Test (biology); Plan (archaeology); Debt; Business; Cognitive psychology; Finance; Payment; Criminology","score_opus":0.24459474517595206,"score_gpt":0.46298260745756364,"score_spread":0.21838786228161158,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2793286537","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98181945,0.0010088537,0.0016798219,0.0044597206,0.009771317,0.00020361156,0.000013522752,0.000028201277,0.0010155084],"genre_scores_gemma":[0.9912148,0.000029788234,0.0057703974,0.0013901015,0.0010851842,0.0000068821487,4.2718312e-7,0.000025580122,0.00047684004],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99585116,0.00046777664,0.0019244284,0.000482338,0.0008750705,0.00039923156],"domain_scores_gemma":[0.994693,0.0011497625,0.0020793083,0.0008231456,0.0009807259,0.00027405698],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0050109257,0.00024525647,0.0006788345,0.0004370244,0.00029529477,0.0006940056,0.0018672335,0.00018708149,0.00019638833],"category_scores_gemma":[0.0031825954,0.00012807004,0.00022193574,0.0004429397,0.00041232014,0.00066546345,0.00014799503,0.0006407338,0.0005078666],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034030533,0.00017497838,0.034839887,0.000003925653,0.000104754814,0.00020349723,0.004939629,0.00038858477,0.0012624537,0.00003081895,0.38766438,0.5700468],"study_design_scores_gemma":[0.004341764,0.0044432166,0.19060723,0.0020200477,0.0006716127,0.0079767825,0.012737288,0.0030713382,0.0022741272,0.06796817,0.7020519,0.0018365639],"about_ca_topic_score_codex":0.000011790101,"about_ca_topic_score_gemma":0.000017735305,"teacher_disagreement_score":0.56821024,"about_ca_system_score_codex":0.00005160563,"about_ca_system_score_gemma":0.00020757967,"threshold_uncertainty_score":0.6692312},"labels":[],"label_agreement":null},{"id":"W2793940238","doi":"10.1111/caje.12314","title":"Welfare economics, risk and uncertainty","year":2018,"lang":"en","type":"article","venue":"Canadian Journal of Economics/Revue canadienne d économique","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":63,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Egalitarianism; Ambiguity; Utilitarianism; Ex-ante; Economics; Welfare; Expected utility hypothesis; Social Welfare; Social preferences; Microeconomics; Actuarial science; Public economics; Positive economics; Financial economics; Political science; Law; Computer science","score_opus":0.23786702647772331,"score_gpt":0.26439869263867266,"score_spread":0.026531666160949346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2793940238","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98972553,0.0001696391,0.00009303305,0.0032951161,0.0037058932,0.00018587925,0.0005169798,0.000007653709,0.002300297],"genre_scores_gemma":[0.99628425,0.00017723891,0.0010807604,0.0006340904,0.0012336273,0.0000045528086,0.0000056924346,0.000052521034,0.0005272968],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99594957,0.00016926324,0.0021187623,0.0008196952,0.000008059393,0.00093467475],"domain_scores_gemma":[0.99275136,0.00068754976,0.0018726741,0.0009894407,0.00072564394,0.0029733344],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0039935564,0.00041220148,0.0010669647,0.0015413426,0.00067387306,0.0009072114,0.0015679449,0.0003153138,0.001675704],"category_scores_gemma":[0.0022378052,0.0004168993,0.00036677206,0.00023630064,0.00077395927,0.00097526924,0.000092934104,0.00051021815,0.00028568297],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022800043,0.000025997226,0.0582112,0.000006903729,0.00016723496,0.00014938238,0.0023298627,0.00580892,0.0000039210013,0.22183123,0.0053234966,0.70591384],"study_design_scores_gemma":[0.0007043643,0.00057729613,0.0046872282,0.000033976157,0.000053411288,0.0006828783,0.0014237689,0.0034590226,0.000028500308,0.6970994,0.2907253,0.00052490016],"about_ca_topic_score_codex":0.097778864,"about_ca_topic_score_gemma":0.9763483,"teacher_disagreement_score":0.8785694,"about_ca_system_score_codex":0.0015613476,"about_ca_system_score_gemma":0.0017435465,"threshold_uncertainty_score":0.9998283},"labels":[],"label_agreement":null},{"id":"W2794622550","doi":"10.3389/fpsyg.2018.00403","title":"The Role of Type and Source of Uncertainty on the Processing of Climate Models Projections","year":2018,"lang":"en","type":"article","venue":"Frontiers in Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"National Science Foundation","keywords":"Ambiguity; Credibility; Timeline; Set (abstract data type); Range (aeronautics); Disjoint sets; Perception; Heuristics; Climate change; Climate model; Feature (linguistics); Econometrics; Computer science; Psychology; Statistics; Mathematics","score_opus":0.08966104859247541,"score_gpt":0.40631081347291836,"score_spread":0.31664976488044294,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2794622550","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98519135,0.0003846154,0.0041102353,0.00032926767,0.0006921088,0.00012616851,0.000006409321,0.0000043389196,0.00915553],"genre_scores_gemma":[0.9980014,0.000119457014,0.0017456977,0.000066190965,0.000018523124,0.0000037121997,2.0512066e-7,0.0000048882002,0.000039954946],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9988844,0.00012402561,0.00047461226,0.00021298684,0.00017192359,0.00013204265],"domain_scores_gemma":[0.9986532,0.00034095507,0.00034084375,0.00041014532,0.00023875447,0.000016113685],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016211851,0.000062256,0.00020728288,0.00015781194,0.000108815235,0.000018893164,0.00042991413,0.00006921003,0.000009409004],"category_scores_gemma":[0.00042407354,0.00003217783,0.000033083677,0.00049195817,0.0007107347,0.00005846377,0.00006080106,0.00009715779,0.0000029301702],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025937523,0.00006171567,0.014195278,0.0000012814312,0.0000050651615,9.8638004e-8,0.0010010041,0.000368567,0.00015472119,0.00070063013,0.002401691,0.9808506],"study_design_scores_gemma":[0.00038228356,0.00063470745,0.004195694,0.00005965822,0.0000147246365,0.0000066363086,0.009197502,0.07033968,0.0003876661,0.893357,0.021322062,0.00010239857],"about_ca_topic_score_codex":0.000026924885,"about_ca_topic_score_gemma":0.00003139785,"teacher_disagreement_score":0.9807482,"about_ca_system_score_codex":0.0000087851895,"about_ca_system_score_gemma":0.00003673342,"threshold_uncertainty_score":0.26187316},"labels":[],"label_agreement":null},{"id":"W2794648354","doi":"10.2139/ssrn.2425396","title":"Do Risk Preferences Change? Evidence from Panel Data Before and after the Great East Japan Earthquake","year":2014,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Panel data; East Asia; Economics; History; Econometrics; China","score_opus":0.18490606764449902,"score_gpt":0.3591590631056432,"score_spread":0.1742529954611442,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2794648354","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99303794,0.003596695,0.0011647388,0.0014631,0.00043396986,0.00013625942,0.000080147576,0.000017687606,0.000069475645],"genre_scores_gemma":[0.9956925,0.002946058,0.00015173161,0.00013842875,0.00076557783,0.000009027881,0.0000045774846,0.000016794558,0.00027529773],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99593395,0.00051687163,0.000641889,0.0007579989,0.0009029835,0.0012463039],"domain_scores_gemma":[0.9964717,0.0012011717,0.00052186754,0.0014788947,0.00015866582,0.00016770686],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.010723811,0.00023796297,0.0003480383,0.00014479097,0.0005171301,0.0012379235,0.0025369362,0.00011419373,0.00027845736],"category_scores_gemma":[0.0020512033,0.00012646744,0.00010436128,0.0002563858,0.00020491432,0.0013289615,0.0006049513,0.0014984115,0.00029511572],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007254193,0.000012349088,0.19095881,3.0367949e-7,0.00001978493,0.0000011038039,0.0005908839,0.00000283004,0.0000024226808,0.00012325992,0.000094281044,0.80812144],"study_design_scores_gemma":[0.0002512745,0.0003357784,0.3091212,0.00008460842,0.000083399485,0.00019615177,0.0024398463,0.0011769587,0.0000014574373,0.68108743,0.005028384,0.00019350571],"about_ca_topic_score_codex":0.00059414416,"about_ca_topic_score_gemma":0.031824466,"teacher_disagreement_score":0.8079279,"about_ca_system_score_codex":0.000084920175,"about_ca_system_score_gemma":0.0003842179,"threshold_uncertainty_score":0.9997989},"labels":[],"label_agreement":null},{"id":"W2795238567","doi":"10.1007/s10899-018-9770-2","title":"Unclaimed Prize Information Biases Perceptions of Winning in Scratch Card Gambling","year":2018,"lang":"en","type":"article","venue":"Journal of Gambling Studies","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Gambling Research Exchange Ontario","keywords":"Psychology; Scratch; Context (archaeology); Equating; Perception; Social psychology; Advertising; Computer science; Developmental psychology; Business","score_opus":0.31440656950015033,"score_gpt":0.4967319749600865,"score_spread":0.18232540545993614,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2795238567","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99566936,0.00043841245,0.0017434504,0.00052903476,0.0011395069,0.00007329923,0.0000051115812,0.000009731978,0.0003920764],"genre_scores_gemma":[0.99266404,0.00022992221,0.006653971,0.00012857774,0.00027582698,0.0000013795178,4.4586315e-7,0.0000071166364,0.000038703518],"study_design_codex":"design_other","study_design_gemma":"qualitative","domain_scores_codex":[0.996358,0.000120078505,0.0021559321,0.00015645036,0.0009852564,0.00022433187],"domain_scores_gemma":[0.99375945,0.0017179039,0.0015569811,0.0002700842,0.0026249224,0.00007065039],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0052523855,0.0001499989,0.0006928851,0.0013861061,0.00021336513,0.00023431474,0.00048239113,0.00007594141,0.000044051932],"category_scores_gemma":[0.010731708,0.00010608366,0.00022070683,0.001039478,0.00026119314,0.0018287663,0.00017013308,0.00025584636,0.000057986366],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045646593,0.0002475023,0.19269,0.00003008702,0.00019659929,0.000030275061,0.043705158,0.011149269,0.004035023,0.00011911658,0.0129342,0.7344063],"study_design_scores_gemma":[0.0067899344,0.003941228,0.3095845,0.006082794,0.00046000775,0.00030121912,0.5206135,0.009106859,0.005652062,0.1143318,0.021650428,0.001485664],"about_ca_topic_score_codex":0.000024901397,"about_ca_topic_score_gemma":0.00008020386,"teacher_disagreement_score":0.73292065,"about_ca_system_score_codex":0.00012736977,"about_ca_system_score_gemma":0.00018547941,"threshold_uncertainty_score":0.99760133},"labels":[],"label_agreement":null},{"id":"W2795752317","doi":"10.1027/1614-0001/a000254","title":"Cognitive Reflection Effects on Time Discounting","year":2018,"lang":"en","type":"article","venue":"Journal of Individual Differences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":44,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Psychology; Cognition; Reflection (computer programming); Preference; Temporal discounting; Cognitive psychology; Stochastic game; Numeracy; Discounting; Social psychology; Developmental psychology; Statistics; Impulsivity; Mathematics; Economics; Computer science; Microeconomics","score_opus":0.16221025554991786,"score_gpt":0.43120157013457644,"score_spread":0.2689913145846586,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2795752317","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9934784,0.000035565135,0.00033568504,0.0002489387,0.0016049249,0.00007278778,0.00001368991,0.000011961628,0.00419803],"genre_scores_gemma":[0.9979247,0.000005731875,0.00035725706,0.00029795853,0.0010398404,0.0000011802849,9.4340413e-7,0.000009089719,0.0003633166],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9966577,0.00026136014,0.0009157279,0.00028109032,0.001647518,0.00023657124],"domain_scores_gemma":[0.994182,0.0036223668,0.0011731044,0.0001760952,0.00071547757,0.00013097454],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0031764514,0.00017236834,0.00045679297,0.00057295815,0.00027928269,0.00077696925,0.0008264054,0.00010345326,0.0005154796],"category_scores_gemma":[0.0045883153,0.000101873695,0.00019243888,0.00045096382,0.00018436777,0.0005612673,0.00010751352,0.00031186256,0.0010317038],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018874797,0.00013485226,0.02557864,0.0000016795083,0.000046912104,0.000024486097,0.0010911501,0.0000013929105,0.0006685762,0.0000541087,0.0047585145,0.9674509],"study_design_scores_gemma":[0.0017751023,0.008863931,0.8000208,0.0011323707,0.00023906215,0.00023221942,0.0026835848,0.00024334343,0.0130392155,0.16873403,0.0024434614,0.00059283595],"about_ca_topic_score_codex":0.0000033282736,"about_ca_topic_score_gemma":0.000008063252,"teacher_disagreement_score":0.9668581,"about_ca_system_score_codex":0.00004043981,"about_ca_system_score_gemma":0.00009101422,"threshold_uncertainty_score":0.9997461},"labels":[],"label_agreement":null},{"id":"W2795986334","doi":"10.1287/mnsc.2017.2931","title":"The (Neural) Dynamics of Stochastic Choice","year":2018,"lang":"en","type":"article","venue":"Management Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":114,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Observable; Preference; Bounded function; Econometrics; Discrete choice; Class (philosophy); Stochastic modelling; Dynamics (music); Stochastic process; Contrast (vision); Computer science; Mathematics; Mathematical economics; Economics; Statistics; Artificial intelligence; Psychology","score_opus":0.08718519604467406,"score_gpt":0.4031275039371026,"score_spread":0.31594230789242855,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2795986334","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9434477,0.000017058637,0.024987845,0.0012206791,0.0017658003,0.00021221141,0.000004766664,0.000029241455,0.028314669],"genre_scores_gemma":[0.99635315,0.0000021255028,0.00080042117,0.00012882047,0.000045454715,0.000004584645,2.053648e-7,0.000004464678,0.002660789],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9971832,0.000034955247,0.0005018006,0.0005127386,0.0014345815,0.0003327372],"domain_scores_gemma":[0.99747556,0.00073488377,0.00027506554,0.0011260659,0.00030508818,0.000083323095],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0047803465,0.000096758165,0.00013693456,0.00029330797,0.00080139743,0.0005757514,0.0031516147,0.000018886418,0.000091197304],"category_scores_gemma":[0.0013981923,0.000056099096,0.000060266033,0.0018181789,0.0019715738,0.00040195137,0.0008354802,0.000063029474,0.00046056378],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009680884,0.000028838098,0.0011923689,8.380103e-7,0.0000025779436,0.0000013754938,0.00008035933,0.00049072306,0.000040863517,0.021461828,0.001547116,0.97514343],"study_design_scores_gemma":[0.00043739122,0.0003512837,0.06915668,0.000040798845,0.000035685855,0.000007821839,0.0027765837,0.51937056,0.00021046028,0.37521812,0.03197732,0.00041728507],"about_ca_topic_score_codex":0.000021481257,"about_ca_topic_score_gemma":0.00017065054,"teacher_disagreement_score":0.97472614,"about_ca_system_score_codex":0.00008017941,"about_ca_system_score_gemma":0.000029547009,"threshold_uncertainty_score":0.7264346},"labels":[],"label_agreement":null},{"id":"W2799322610","doi":"10.1177/0301006618773081","title":"Learning in the Target Prevalence Effect","year":2018,"lang":"en","type":"article","venue":"Perception","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Task (project management); Psychology; Cognitive psychology; Point (geometry); Relation (database); Sampling (signal processing); Value (mathematics); Statistics; Computer science; Artificial intelligence; Mathematics; Computer vision; Data mining","score_opus":0.0853493115442623,"score_gpt":0.41684276196796705,"score_spread":0.33149345042370476,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2799322610","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99390024,0.000010344332,0.0006682165,0.00028868383,0.00032459712,0.00011515526,0.0000010705864,0.00002658214,0.004665115],"genre_scores_gemma":[0.9983067,0.000007523804,0.00050247915,0.00016971788,0.00020238328,0.000009581445,0.000001247362,0.000004841884,0.0007955203],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99834555,0.0004397634,0.00028718045,0.0003044038,0.0004697549,0.00015333827],"domain_scores_gemma":[0.99874324,0.00073405367,0.000088523695,0.00033534152,0.00007318908,0.000025658166],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0052170483,0.00007769342,0.00011888549,0.00013061594,0.00017471358,0.000239279,0.0005359064,0.000055563083,0.0019114076],"category_scores_gemma":[0.0015225442,0.000043720822,0.00006259761,0.00033840147,0.000099864745,0.00026014008,0.000056090925,0.00017173267,0.0050781136],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002541055,0.000023785258,0.13580649,0.0000014794294,4.433699e-7,0.0000019336626,0.003113222,0.00010689925,0.0011124525,0.000012055776,0.0021304141,0.8576654],"study_design_scores_gemma":[0.00023566163,0.00068421697,0.9472739,0.000031253563,0.0000069238263,0.000017979153,0.0017920603,0.00852873,0.00006934011,0.015194875,0.02601514,0.00014989058],"about_ca_topic_score_codex":0.000022620194,"about_ca_topic_score_gemma":0.000025158772,"teacher_disagreement_score":0.8575155,"about_ca_system_score_codex":0.000038496164,"about_ca_system_score_gemma":0.000013117344,"threshold_uncertainty_score":0.99900097},"labels":[],"label_agreement":null},{"id":"W2801536555","doi":"10.5539/ijps.v10n2p71","title":"Behavioral Perspectives on Risk Prone Behavior: Why Do People Take Risks?","year":2018,"lang":"en","type":"article","venue":"International Journal of Psychological Studies","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Foraging; Psychology; Context (archaeology); Behavioral economics; Empirical research; Social psychology; Addictive behavior; Addiction; Cognitive psychology; Epistemology; Ecology; Economics; Neuroscience; Microeconomics","score_opus":0.41586580244852955,"score_gpt":0.5722124755930074,"score_spread":0.1563466731444778,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2801536555","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9901662,0.00069159723,0.0005162413,0.0014772392,0.00521346,0.00013262937,0.000057763184,0.000024361192,0.001720518],"genre_scores_gemma":[0.99549115,0.0006820852,0.0019544535,0.00032817543,0.0013776066,0.000011264163,6.9718715e-7,0.000013142826,0.00014145172],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9955253,0.00027416513,0.0013426369,0.0005989519,0.0019834475,0.00027552326],"domain_scores_gemma":[0.9936889,0.0009591498,0.001418289,0.00039827393,0.0033791417,0.0001562782],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0027078767,0.00025842266,0.00060238456,0.00048761562,0.00026979856,0.00043622887,0.0017903786,0.0001347715,0.0013597336],"category_scores_gemma":[0.0036571913,0.00015487373,0.00044451296,0.00034441735,0.00059381395,0.0004037132,0.0002759491,0.00054002955,0.0005723359],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00096429,0.0028799314,0.18735556,3.7649008e-7,0.00018447747,0.00023490192,0.005075095,0.000032734773,0.00011867237,0.0005416856,0.037149463,0.7654628],"study_design_scores_gemma":[0.0027044674,0.0086742705,0.80681354,0.00014029423,0.00021958591,0.0006705937,0.03385203,0.000026953961,0.0001579262,0.100096375,0.04601437,0.0006295797],"about_ca_topic_score_codex":0.000024938141,"about_ca_topic_score_gemma":0.00007151489,"teacher_disagreement_score":0.7648332,"about_ca_system_score_codex":0.00021269452,"about_ca_system_score_gemma":0.000023671773,"threshold_uncertainty_score":0.99955314},"labels":[],"label_agreement":null},{"id":"W2802883214","doi":"10.1007/s40070-018-0081-8","title":"On proper scoring rules and cumulative prospect theory","year":2018,"lang":"en","type":"article","venue":"EURO Journal on Decision Processes","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Cumulative prospect theory; Scoring rule; Weighting; Prospect theory; Rank (graph theory); Property (philosophy); Computer science; Outcome (game theory); Function (biology); Expected utility hypothesis; Belief structure; Artificial intelligence; Mathematics; Mathematical economics; Machine learning; Economics; Epistemology; Medicine; Microeconomics","score_opus":0.12894715752955593,"score_gpt":0.4127037657872057,"score_spread":0.28375660825764976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2802883214","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98367393,0.00030673933,0.0043475796,0.00032401126,0.0012205844,0.00019988773,0.000010828204,0.000050781466,0.0098656425],"genre_scores_gemma":[0.99369454,0.00013056677,0.0028674616,0.0008666299,0.00052200176,0.000004885459,4.0127992e-7,0.000042228472,0.0018712942],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9954122,0.00026349383,0.0011676622,0.00087223394,0.0018843218,0.00040011844],"domain_scores_gemma":[0.9900545,0.006743993,0.0007144998,0.0006219797,0.001530831,0.0003341896],"candidate_categories":["metaresearch","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.005355593,0.00034360055,0.00049615063,0.0007731833,0.00089963,0.0018552082,0.0010574703,0.00010714566,0.001064552],"category_scores_gemma":[0.028460892,0.00019716375,0.000125907,0.0008092499,0.00032136563,0.00093163596,0.00025318688,0.00054980215,0.002631667],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001482267,0.00022172015,0.0015140921,0.0000041298,0.000013689309,0.00012348816,0.0006249897,0.00013206,0.00007679207,0.0034855295,0.006994801,0.98532647],"study_design_scores_gemma":[0.0008774381,0.0020868112,0.0062897513,0.0005850459,0.0000186156,0.0004226379,0.00033565046,0.00019302218,0.0018450706,0.95135725,0.035612773,0.0003759409],"about_ca_topic_score_codex":6.6917664e-7,"about_ca_topic_score_gemma":0.0000038996036,"teacher_disagreement_score":0.9849505,"about_ca_system_score_codex":0.0000709233,"about_ca_system_score_gemma":0.00022473428,"threshold_uncertainty_score":0.9998486},"labels":[],"label_agreement":null},{"id":"W2802997583","doi":"10.3390/jintelligence6020025","title":"How to Think Rationally about World Problems","year":2018,"lang":"en","type":"article","venue":"Journal of Intelligence","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Rationality; Variety (cybernetics); Positive economics; Context (archaeology); Sacrifice; Psychology; Social issues; Sociology; Social psychology; Epistemology; Economics; Political science; Law; Economic growth; Computer science; Philosophy; History","score_opus":0.18657246087327478,"score_gpt":0.4209051342128343,"score_spread":0.23433267333955954,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2802997583","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7286375,0.00022393432,0.25029945,0.010232703,0.0034880012,0.00017590408,0.0000071392556,0.000017160595,0.0069181826],"genre_scores_gemma":[0.9684471,0.000019853944,0.022516618,0.0009787842,0.00060578116,0.0000010996665,1.5532915e-7,0.000009794611,0.0074208453],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99711776,0.00007477294,0.0011330623,0.00026655616,0.0011948424,0.00021301078],"domain_scores_gemma":[0.9955384,0.0008156393,0.0008169335,0.00041366922,0.0021738256,0.00024151577],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003587461,0.00013072725,0.00031788502,0.0006508729,0.00014194017,0.0010278532,0.0014764813,0.00005258469,0.0008096327],"category_scores_gemma":[0.004179784,0.00008475812,0.00018798017,0.00091909093,0.00012770835,0.00075431226,0.00012905977,0.00023489514,0.001176185],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000075441065,0.00007825639,0.0016150591,0.0000011105966,0.000011545202,0.000022219818,0.0011583439,0.001008093,0.00095797976,0.0025345306,0.043363154,0.9491743],"study_design_scores_gemma":[0.00012042887,0.0010782301,0.0042263023,0.00025574808,0.000019254267,0.0002382709,0.0012075994,0.0012759463,0.012265561,0.49639156,0.482586,0.0003350837],"about_ca_topic_score_codex":0.0000044421045,"about_ca_topic_score_gemma":0.00017090618,"teacher_disagreement_score":0.9488392,"about_ca_system_score_codex":0.000082614315,"about_ca_system_score_gemma":0.00019376654,"threshold_uncertainty_score":0.99960154},"labels":[],"label_agreement":null},{"id":"W2804977554","doi":"10.1007/s40505-018-0147-6","title":"Recursive maxmin preferences and rectangular priors: a simple proof","year":2018,"lang":"en","type":"article","venue":"Economic Theory Bulletin","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Simple (philosophy); Prior probability; Mathematical economics; Key (lock); Element (criminal law); Characterization (materials science); Computer science; Mathematics; Mathematical optimization; Artificial intelligence; Bayesian probability","score_opus":0.057114991708866615,"score_gpt":0.3511157200397288,"score_spread":0.29400072833086216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2804977554","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97711027,0.00019360016,0.0003827217,0.0009791292,0.0007040417,0.00028903535,0.000053109365,0.00005084525,0.020237254],"genre_scores_gemma":[0.99429923,0.000018199631,0.0015621876,0.000373002,0.00038461178,0.000021743133,0.000003951938,0.000025473393,0.0033115954],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99733716,0.00037023044,0.00080532714,0.00092357915,0.00019578204,0.0003678895],"domain_scores_gemma":[0.99682045,0.0016610658,0.00042130938,0.0008028326,0.00011368424,0.0001806658],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.004715469,0.00024293482,0.00045273761,0.00023207616,0.00026690282,0.00046692308,0.00084566214,0.00014959455,0.016581062],"category_scores_gemma":[0.0015428596,0.00019316042,0.00011467483,0.000104710474,0.0005495377,0.00017228292,0.00032099793,0.00016356395,0.007825707],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036102888,0.000058817594,0.0021770212,0.000002535359,0.00002648357,0.00000961281,0.0018285189,0.000012594863,0.000079018406,0.013473739,0.0546878,0.9272828],"study_design_scores_gemma":[0.00028018546,0.00024995033,0.0011182076,0.000019104824,0.000013509315,0.000026422531,0.001438747,0.00006113879,0.00086754357,0.60495734,0.3907175,0.00025032714],"about_ca_topic_score_codex":0.000040435123,"about_ca_topic_score_gemma":0.00009319169,"teacher_disagreement_score":0.92703253,"about_ca_system_score_codex":0.00009723093,"about_ca_system_score_gemma":0.00009688117,"threshold_uncertainty_score":0.9929468},"labels":[],"label_agreement":null},{"id":"W2809113179","doi":"10.7554/elife.39656","title":"Time preferences are reliable across time-horizons and verbal versus experiential tasks","year":2019,"lang":"en","type":"article","venue":"eLife","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Science and Technology Commission of Shanghai Municipality; National Natural Science Foundation of China; New York University Shanghai","keywords":"Experiential learning; Context (archaeology); Psychology; Cognitive psychology; Delay discounting; Discounting; Time preference; Preference; Time horizon; Task (project management); Temporal discounting; Social psychology; Developmental psychology; Impulsivity; Biology","score_opus":0.0802426073853749,"score_gpt":0.38186642720143954,"score_spread":0.3016238198160646,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2809113179","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9913171,0.00012429718,0.0000135053,0.00009448024,0.0020131909,0.00014629358,0.00009036115,0.00006638722,0.0061344183],"genre_scores_gemma":[0.9892127,0.000013624707,0.00030081774,0.000085231455,0.00017096639,0.000008215699,0.000008688145,0.000016145757,0.01018364],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99749315,0.000059575792,0.00050673785,0.00070819515,0.0008506335,0.00038173716],"domain_scores_gemma":[0.99809885,0.00057913933,0.00024955347,0.0007083696,0.00017792716,0.00018614967],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0010402921,0.00018919606,0.0003923252,0.00008687363,0.00023191905,0.0006141157,0.00066599314,0.00015417693,0.003864471],"category_scores_gemma":[0.0005319428,0.00014665787,0.00010416955,0.0002675825,0.00016530669,0.00048637998,0.00039766956,0.00016329977,0.020225625],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002495145,0.00053741777,0.05321824,0.000010827221,0.000097081254,0.00006621373,0.011810674,0.0007317893,0.0052339854,0.0001874605,0.42682743,0.49878374],"study_design_scores_gemma":[0.005808811,0.0017765482,0.020027936,0.00015236139,0.000060158265,0.000030983865,0.016328413,0.009249954,0.0037753822,0.004724045,0.93644047,0.0016249344],"about_ca_topic_score_codex":0.00003475024,"about_ca_topic_score_gemma":0.000021660302,"teacher_disagreement_score":0.50961304,"about_ca_system_score_codex":0.000038684568,"about_ca_system_score_gemma":0.00006638732,"threshold_uncertainty_score":0.9970461},"labels":[],"label_agreement":null},{"id":"W2851780690","doi":"","title":"Bunk House Rules","year":2016,"lang":"en","type":"article","venue":"Osgoode Hall law journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Mathematics","score_opus":0.13851498451405977,"score_gpt":0.3808930838355891,"score_spread":0.24237809932152934,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2851780690","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7750127,0.00019757476,0.0060109366,0.0037268184,0.0023392502,0.000078025856,0.000037612223,0.00012253507,0.21247457],"genre_scores_gemma":[0.99388975,0.000072245355,0.0035781278,0.00038706997,0.00044986437,0.0000017092458,2.0614206e-7,0.000033696684,0.001587305],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9970694,0.000166326,0.0009094509,0.0004114151,0.0010245574,0.0004188555],"domain_scores_gemma":[0.99718803,0.0009910323,0.00046147394,0.0006676324,0.00032549337,0.00036635803],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002852268,0.00018722683,0.00034695797,0.00019001892,0.0005319778,0.0009415847,0.0012734457,0.00012303052,0.0025510122],"category_scores_gemma":[0.0009533697,0.000096915355,0.00028411296,0.00014860017,0.00018186649,0.000866244,0.00017190253,0.00024609338,0.008383604],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000043225034,0.000082464205,0.0015804752,3.1773519e-7,0.000010903016,0.00011457664,0.000052745487,0.000016799251,0.0007337327,0.06647746,0.014069921,0.91681737],"study_design_scores_gemma":[0.0005789264,0.000092652124,0.0010509269,0.000052984215,0.000012683729,0.0006210347,0.00008568916,0.0000273368,0.00045659806,0.88181704,0.115000054,0.00020408514],"about_ca_topic_score_codex":0.00038776925,"about_ca_topic_score_gemma":0.0034379852,"teacher_disagreement_score":0.9166133,"about_ca_system_score_codex":0.0000954528,"about_ca_system_score_gemma":0.0000711386,"threshold_uncertainty_score":0.9983608},"labels":[],"label_agreement":null},{"id":"W2856705998","doi":"10.1037/xge0000457","title":"Do smart people have better intuitions?","year":2018,"lang":"en","type":"article","venue":"Journal of Experimental Psychology General","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":110,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Psychology; Cognitive psychology; Task (project management); Dimension (graph theory); Deductive reasoning; PsycINFO; Social psychology; Artificial intelligence; Computer science; Mathematics; MEDLINE","score_opus":0.16470856980880794,"score_gpt":0.4943128742715425,"score_spread":0.3296043044627346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2856705998","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98393315,0.0002714533,0.00091997307,0.0015489154,0.0047925604,0.00005884116,0.000007162261,0.000008915537,0.008459003],"genre_scores_gemma":[0.98697823,0.000007694726,0.007337462,0.0036887007,0.0014953221,0.0000028701004,0.0000011434272,0.000016204098,0.00047239495],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99732184,0.00023174548,0.001190417,0.00038173888,0.0005889617,0.0002852674],"domain_scores_gemma":[0.99804586,0.00018453778,0.00066364213,0.0005415559,0.00036925092,0.00019516028],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0018341686,0.00017415696,0.00043233935,0.00045100987,0.00021886893,0.00023149986,0.0008899013,0.00014719644,0.004742425],"category_scores_gemma":[0.00021221774,0.00012703166,0.0003025142,0.00024526144,0.0002984014,0.00042834276,0.00013624555,0.0003182316,0.0010234119],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006696025,0.0011798166,0.069776386,4.292855e-7,0.000074360614,0.00012552078,0.0031948544,0.000013244856,0.14858267,0.0003651902,0.58126056,0.1947574],"study_design_scores_gemma":[0.0092613995,0.010952343,0.18385018,0.00008742679,0.00009844465,0.0076938774,0.008650755,0.0004963408,0.122223884,0.24132475,0.41382036,0.0015402214],"about_ca_topic_score_codex":0.000007918366,"about_ca_topic_score_gemma":0.000016147555,"teacher_disagreement_score":0.24095955,"about_ca_system_score_codex":0.00007312526,"about_ca_system_score_gemma":0.00004443012,"threshold_uncertainty_score":0.9997544},"labels":[],"label_agreement":null},{"id":"W2886966691","doi":"10.1016/j.drugalcdep.2018.06.034","title":"Delay discounting and e-cigarette use: An investigation in current, former, and never cigarette smokers","year":2018,"lang":"en","type":"article","venue":"Drug and Alcohol Dependence","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Institute on Drug Abuse; National Cancer Institute; National Heart, Lung, and Blood Institute","keywords":"Delay discounting; Discounting; Cigarette smoking; Psychology; Environmental health; Medicine; Demography; Clinical psychology; Economics; Impulsivity; Internal medicine; Sociology","score_opus":0.13357285850081904,"score_gpt":0.38983672591527363,"score_spread":0.2562638674144546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2886966691","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9983869,0.0003614882,0.00017727792,0.00039435684,0.00039109218,0.0001509334,0.000021009128,0.00002548538,0.00009145949],"genre_scores_gemma":[0.9988072,0.000134357,0.00036088712,0.0004528527,0.00009286998,0.0000068610766,0.000005650778,0.000013460244,0.00012584054],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99764365,0.000113367554,0.00056162797,0.0008246807,0.000533877,0.0003227901],"domain_scores_gemma":[0.99854064,0.00049431215,0.00023046994,0.0003702091,0.000133203,0.00023117225],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020975387,0.00020934372,0.00027842095,0.00027733415,0.0003087999,0.0009984723,0.00029988456,0.000094814466,0.000031024814],"category_scores_gemma":[0.00047997528,0.00016750759,0.000030237965,0.0003180145,0.00047769645,0.0034399382,0.00024038312,0.0002656332,0.00001256863],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002113308,0.000016315395,0.5508522,0.0000033957583,0.0000032013304,0.000010181884,0.0013859866,0.0000052609485,0.00016405345,0.000221345,0.00053139386,0.44678554],"study_design_scores_gemma":[0.0011610412,0.00013053135,0.91657853,0.00027883356,0.00004523625,0.00011827804,0.0020827805,0.016490132,0.0006393687,0.055622786,0.006100302,0.0007521844],"about_ca_topic_score_codex":0.00032877637,"about_ca_topic_score_gemma":0.00095909205,"teacher_disagreement_score":0.44603336,"about_ca_system_score_codex":0.000025355657,"about_ca_system_score_gemma":0.00004619067,"threshold_uncertainty_score":0.9628292},"labels":[],"label_agreement":null},{"id":"W2887819748","doi":"10.3389/fpsyg.2018.01461","title":"Cognitive Style and Frame Susceptibility in Decision-Making","year":2018,"lang":"en","type":"article","venue":"Frontiers in Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada; York University","funders":"Natural Sciences and Engineering Research Council of Canada; Ministère de la Défense Nationale","keywords":"Psychology; Framing effect; Cognition; Framing (construction); Cognitive style; Social psychology; Cognitive psychology; Developmental psychology; Persuasion","score_opus":0.07506158193669349,"score_gpt":0.4459175960190833,"score_spread":0.37085601408238983,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2887819748","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9312339,0.00028312797,0.059772525,0.00024104938,0.003560309,0.00020561677,0.000016680578,0.000021092854,0.004665709],"genre_scores_gemma":[0.9665244,0.00003850597,0.032246914,0.0010291117,0.00010040935,0.000010270774,0.0000011225363,0.000014656843,0.000034585402],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99673116,0.00030548815,0.0009758571,0.0011703024,0.0003696318,0.0004475391],"domain_scores_gemma":[0.9970802,0.0017150178,0.00022560703,0.0006984262,0.00017953211,0.000101221965],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035914974,0.00019576722,0.0005528576,0.0010012882,0.00009563688,0.00013703796,0.0006713522,0.0003119342,0.0005676595],"category_scores_gemma":[0.004746925,0.00016945734,0.00007157034,0.0009861673,0.00076397543,0.00030025383,0.00021933003,0.0003833215,0.00028120494],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026620406,0.000086016975,0.3711193,3.7582947e-7,0.0000022995382,0.000021671796,0.00047680904,9.1264235e-7,0.000008168047,0.000017623604,0.008506225,0.61949444],"study_design_scores_gemma":[0.0010743558,0.00024505233,0.3774776,0.00008280658,0.0000046836217,0.000022175891,0.0021554101,0.0009809139,0.000005959822,0.61209095,0.005644144,0.0002159978],"about_ca_topic_score_codex":0.000022573402,"about_ca_topic_score_gemma":0.00068571104,"teacher_disagreement_score":0.61927843,"about_ca_system_score_codex":0.00007555326,"about_ca_system_score_gemma":0.000042970787,"threshold_uncertainty_score":0.69102705},"labels":[],"label_agreement":null},{"id":"W2888193398","doi":"10.1371/journal.pone.0202732","title":"In the real world, people prefer their last whisky when tasting options in a long sequence","year":2018,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brock University","funders":"","keywords":"Wine tasting; Sequence (biology); Psychology; Order (exchange); Social psychology; Biology; Economics; Food science; Genetics","score_opus":0.3237415144347216,"score_gpt":0.3862391858001297,"score_spread":0.062497671365408125,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2888193398","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99087125,0.000018659033,0.000070611626,0.001206301,0.00010774137,0.00023206006,0.000020695239,0.000024583964,0.007448089],"genre_scores_gemma":[0.9958654,0.000014799882,0.0025542446,0.00028385097,0.00016551782,0.00003782343,0.0000029124365,0.000011720664,0.0010637498],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977345,0.00022763778,0.0006217088,0.00047435175,0.0006246818,0.00031714587],"domain_scores_gemma":[0.99749136,0.0013725206,0.00017602635,0.00072825135,0.00017281988,0.000058995007],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0028907403,0.00013526628,0.00029793428,0.00041431744,0.00016083765,0.00034865536,0.0010332696,0.000060150167,0.0006095626],"category_scores_gemma":[0.0011815588,0.00008635665,0.00005371587,0.0011348722,0.00012623562,0.0005315815,0.00020007681,0.0002728259,0.00085137243],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012456962,0.0030327241,0.8318375,0.000012025514,0.000027665308,0.000062675674,0.03262626,0.00022210274,0.0039016132,0.0015462674,0.0034438518,0.12316275],"study_design_scores_gemma":[0.0011346817,0.00035681512,0.748592,0.0008195929,0.000052135616,0.000018879733,0.006306541,0.013451469,0.0012911552,0.22454095,0.002691381,0.0007443907],"about_ca_topic_score_codex":0.00050593284,"about_ca_topic_score_gemma":0.058214683,"teacher_disagreement_score":0.22299469,"about_ca_system_score_codex":0.00009627745,"about_ca_system_score_gemma":0.00007656301,"threshold_uncertainty_score":0.99992657},"labels":[],"label_agreement":null},{"id":"W2888616395","doi":"10.1111/ecoj.12639","title":"Expectations-Based Reference-Dependence and Choice Under Risk","year":2018,"lang":"en","type":"article","venue":"The Economic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Axiom independence; Axiom; Independence (probability theory); Preference; Revealed preference; Mathematical economics; Risk neutral; Prospect theory; Economics; Econometrics; Expected utility hypothesis; Microeconomics; Mathematics; Statistics","score_opus":0.16569955052686625,"score_gpt":0.4168504478558013,"score_spread":0.25115089732893503,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2888616395","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9915415,0.00011564455,0.0030241872,0.0011271407,0.0009458619,0.000059121357,0.000014670289,0.00001649636,0.0031553553],"genre_scores_gemma":[0.9978154,0.000028240682,0.00093845517,0.00027544468,0.0005336358,0.0000023116518,3.2616154e-7,0.000010706671,0.00039551582],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9983625,0.00020057702,0.00065044855,0.00031976012,0.00023789643,0.0002288591],"domain_scores_gemma":[0.9965114,0.0020776005,0.000591649,0.000513256,0.0001593927,0.0001467298],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002643618,0.00012817977,0.00020977038,0.00017840185,0.0007806787,0.0009406092,0.00089855737,0.00006512608,0.0019161041],"category_scores_gemma":[0.0008107861,0.000077244695,0.000082614504,0.00009390596,0.00031336964,0.00047307613,0.000101973514,0.00034760535,0.0027355868],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013354316,0.000049838472,0.026216203,5.334256e-7,0.000039615203,0.0000076106094,0.0011360964,0.004291344,0.00013360358,0.0015297673,0.020923423,0.9455384],"study_design_scores_gemma":[0.0013893764,0.00035794932,0.07218147,0.000031912095,0.00006512992,0.00047139285,0.004352375,0.043167584,0.00033659997,0.8391238,0.03806268,0.00045971098],"about_ca_topic_score_codex":0.00009263222,"about_ca_topic_score_gemma":0.00042449046,"teacher_disagreement_score":0.94507873,"about_ca_system_score_codex":0.00014893917,"about_ca_system_score_gemma":0.00026801418,"threshold_uncertainty_score":0.99899626},"labels":[],"label_agreement":null},{"id":"W2889788226","doi":"10.1007/s11408-020-00353-5","title":"Behavioral portfolio insurance strategies","year":2020,"lang":"en","type":"article","venue":"Financial markets and portfolio management","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Portfolio insurance; Portfolio; Downside risk; Actuarial science; Economics; Expected utility hypothesis; Pension; Investment strategy; Replicating portfolio; Payment; Financial economics; Business; Portfolio optimization; Microeconomics; Finance; Profit (economics)","score_opus":0.08425534236865562,"score_gpt":0.352121121894842,"score_spread":0.2678657795261864,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889788226","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9318827,0.00022702808,0.0008136874,0.0007015091,0.0006814102,0.0003221815,0.000061027313,0.00008549931,0.06522498],"genre_scores_gemma":[0.99591976,0.00028388502,0.0008807889,0.0012753996,0.00020641918,0.000024580126,0.000009106443,0.000021361531,0.0013787049],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.996949,0.00007058594,0.00091499026,0.0008661043,0.00078245834,0.0004168448],"domain_scores_gemma":[0.9986297,0.00009577446,0.00033837833,0.0005143322,0.00011960445,0.00030221493],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0010531564,0.00029693215,0.0004820204,0.00024257773,0.0002358109,0.0007657373,0.0006964288,0.00011335914,0.0013117504],"category_scores_gemma":[0.0001623644,0.0002475611,0.00016344525,0.0006827849,0.00012260166,0.00064186164,0.00046680056,0.00019081723,0.00027358817],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016597591,0.00009872905,0.019809764,0.000010898323,0.000009047224,0.0003843123,0.00016321643,0.000025428735,0.0000086166765,0.006722581,0.08024826,0.8923532],"study_design_scores_gemma":[0.00048321983,0.00016587073,0.39860642,0.000022864195,0.000032636795,0.000011902038,0.0005740255,0.0001294328,0.000008592365,0.03342926,0.56617564,0.0003601372],"about_ca_topic_score_codex":0.000037834772,"about_ca_topic_score_gemma":0.000021000771,"teacher_disagreement_score":0.89199305,"about_ca_system_score_codex":0.000024071667,"about_ca_system_score_gemma":0.0000734115,"threshold_uncertainty_score":0.9999977},"labels":[],"label_agreement":null},{"id":"W2890724975","doi":"10.3386/w22671","title":"Applying Behavioral Economics to Public Policy in Canada","year":2016,"lang":"en","type":"preprint","venue":"National Bureau of Economic Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto; Employment and Social Development Canada","funders":"","keywords":"Behavioral economics; Public economics; Economics; Political science; Microeconomics","score_opus":0.623303342608137,"score_gpt":0.5932346105687699,"score_spread":0.030068732039367108,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890724975","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9404526,0.00005706123,0.00002613244,0.008509859,0.0012307646,0.0012391531,0.00075324654,0.000011824808,0.047719393],"genre_scores_gemma":[0.99735254,0.00005074798,0.00044299033,0.00017850894,0.0005742232,0.00050291966,0.0000578362,0.00004485224,0.0007953857],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9928963,0.00039620415,0.0024174512,0.0015497662,0.0018062816,0.0009340007],"domain_scores_gemma":[0.9922164,0.003932832,0.00069031277,0.001303355,0.0013485348,0.00050856086],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0112403445,0.00035738506,0.0010006184,0.004686873,0.00015792697,0.00062315474,0.0037922093,0.00039188116,0.0008041314],"category_scores_gemma":[0.0042136875,0.00032205426,0.00024940656,0.00062017626,0.00020507014,0.00041918954,0.0029253569,0.0010055606,0.0007352465],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":true,"study_design_scores_codex":[0.00015522694,0.00021990498,0.05489453,0.000018124114,0.00004541689,0.000016925344,0.00015101697,0.019922554,0.00007109977,0.21594045,0.036976103,0.67158866],"study_design_scores_gemma":[0.00038694998,0.00004534282,0.00349338,0.00007216123,0.0000024170217,0.000005145672,0.00023854389,0.001370053,0.000087172375,0.97437656,0.019559644,0.00036260101],"about_ca_topic_score_codex":0.7345626,"about_ca_topic_score_gemma":0.8850339,"teacher_disagreement_score":0.75843614,"about_ca_system_score_codex":0.015298572,"about_ca_system_score_gemma":0.036446087,"threshold_uncertainty_score":0.99992317},"labels":[],"label_agreement":null},{"id":"W2893737531","doi":"10.1007/s11238-018-9673-9","title":"Sunk ‘Decision Points’: a theory of the endowment effect and present bias","year":2018,"lang":"en","type":"article","venue":"Theory and Decision","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Endowment effect; Situational ethics; Sunk costs; Consumption (sociology); Economics; Endowment; Mechanism (biology); Simple (philosophy); Microeconomics; Inference; Prospect theory; Positive economics; Psychology; Cognitive psychology; Social psychology; Computer science; Epistemology; Sociology; Artificial intelligence","score_opus":0.0818551225695389,"score_gpt":0.381343428437957,"score_spread":0.29948830586841807,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2893737531","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9823967,0.0006515002,0.012159648,0.000114804534,0.0010539228,0.00043614366,0.000022057742,0.000025945186,0.0031392279],"genre_scores_gemma":[0.99785626,0.00007324505,0.0012534347,0.00021863647,0.00014681862,0.000008786332,6.462287e-7,0.000019529312,0.00042266847],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9952494,0.0013900693,0.0010483033,0.00080430385,0.0011897539,0.0003181779],"domain_scores_gemma":[0.9704697,0.027188957,0.00044818345,0.0014367139,0.00026527068,0.00019113679],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.021777641,0.00029373035,0.00058801513,0.0003121666,0.0004741706,0.00030520337,0.0009802629,0.00017002072,0.0005925437],"category_scores_gemma":[0.009304719,0.00014673355,0.0002260809,0.0005205479,0.00096515095,0.00032540437,0.0011117208,0.00020825371,0.00022503162],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002550372,0.000070091286,0.0028430682,0.0000025790634,0.000011287185,0.0000039606275,0.0004953779,0.000006609078,0.00048337717,0.032477837,0.0013251738,0.95973027],"study_design_scores_gemma":[0.0009976301,0.00064475636,0.018253729,0.00016764246,0.00004293025,0.000055621887,0.00037143927,0.00022279994,0.0052789696,0.96745723,0.0063247113,0.00018255462],"about_ca_topic_score_codex":0.000010019863,"about_ca_topic_score_gemma":0.000013999022,"teacher_disagreement_score":0.9595477,"about_ca_system_score_codex":0.000030213421,"about_ca_system_score_gemma":0.000043237622,"threshold_uncertainty_score":0.9990403},"labels":[],"label_agreement":null},{"id":"W2893743957","doi":"10.1017/s1930297500006240","title":"How generalizable is good judgment? A multi-task, multi-benchmark study","year":2017,"lang":"en","type":"article","venue":"Judgment and Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":51,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Consistency (knowledge bases); Coherence (philosophical gambling strategy); Psychology; Task (project management); Cognitive psychology; Quality (philosophy); Axiom; Social psychology; Computer science; Artificial intelligence; Mathematics; Statistics; Epistemology","score_opus":0.23110184384625995,"score_gpt":0.43551786390771624,"score_spread":0.2044160200614563,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2893743957","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9557912,0.00039736397,0.039140105,0.0006589344,0.002006057,0.00085328805,0.000048111513,0.00007412244,0.0010308222],"genre_scores_gemma":[0.92668104,0.000061069906,0.06813366,0.00059231377,0.00017910646,0.00004869392,0.0000022264758,0.000047430975,0.00425443],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9938061,0.00015853214,0.0013565812,0.0018676253,0.00206399,0.0007471461],"domain_scores_gemma":[0.99382806,0.0011415288,0.0012579993,0.0030355914,0.00038365336,0.00035315336],"candidate_categories":["metaepi_narrow","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.004093754,0.0005773568,0.0009551508,0.00061416434,0.0023849383,0.00911426,0.002403296,0.00024748454,0.00050751364],"category_scores_gemma":[0.0023058108,0.00043086518,0.00034707598,0.00031656655,0.00018745643,0.001696834,0.0019033259,0.0003613411,0.00045155658],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011987676,0.0008098748,0.1484112,0.0000030142583,0.00003832201,0.00010224693,0.00082079123,0.000097573706,0.00018507976,0.00006410572,0.009974505,0.8393734],"study_design_scores_gemma":[0.021217661,0.0017342446,0.48330373,0.0008398346,0.00043563606,0.00012741514,0.015649924,0.14325494,0.00053669984,0.14280474,0.1860072,0.00408797],"about_ca_topic_score_codex":0.00008612473,"about_ca_topic_score_gemma":0.0003349857,"teacher_disagreement_score":0.8352854,"about_ca_system_score_codex":0.00012471249,"about_ca_system_score_gemma":0.00006833987,"threshold_uncertainty_score":0.99981433},"labels":[],"label_agreement":null},{"id":"W2899743006","doi":"10.1007/s11166-018-9291-5","title":"Reporting probabilistic expectations with dynamic uncertainty about possible distributions","year":2018,"lang":"en","type":"article","venue":"Journal of Risk and Uncertainty","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Ambiguity; Econometrics; Probability distribution; Counterfactual thinking; Bayes' theorem; Prior probability; Set (abstract data type); Probabilistic logic; Bayesian probability; Statistics; Distribution (mathematics); Mathematics; Joint probability distribution; Computer science; Psychology","score_opus":0.05329607838990369,"score_gpt":0.3793879351215523,"score_spread":0.3260918567316486,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2899743006","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98435223,0.0001963454,0.01410643,0.00028460345,0.00043586234,0.000105900624,0.000081194936,0.000016782284,0.00042063495],"genre_scores_gemma":[0.9954505,0.00004874511,0.0041432893,0.00002601239,0.00018566028,0.0000030852757,0.000004742933,0.000010433231,0.00012756124],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.996282,0.00015690822,0.0022122439,0.00035734466,0.0007088565,0.00028267258],"domain_scores_gemma":[0.9919462,0.0013414158,0.0042904187,0.00043141446,0.0017471495,0.00024339653],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.003533109,0.00018048222,0.0005261193,0.00028879335,0.000639315,0.0004610181,0.00040549916,0.00008337782,0.00012104185],"category_scores_gemma":[0.011390787,0.00010604169,0.00018129632,0.0006437721,0.00045085198,0.0003987307,0.000073268224,0.00033694532,0.000025383752],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005749705,0.00029344662,0.080726184,0.000005910558,0.00007047782,0.00012242311,0.0034218372,0.011992891,0.00011505296,0.0011108017,0.002522575,0.89904344],"study_design_scores_gemma":[0.0031253004,0.003067012,0.28419957,0.00056905823,0.0005382505,0.0025764434,0.030136058,0.06185028,0.0001014341,0.5953142,0.017508667,0.0010137229],"about_ca_topic_score_codex":0.00012568434,"about_ca_topic_score_gemma":0.0010902184,"teacher_disagreement_score":0.8980297,"about_ca_system_score_codex":0.0001577949,"about_ca_system_score_gemma":0.00035741163,"threshold_uncertainty_score":0.9969367},"labels":[],"label_agreement":null},{"id":"W2900034484","doi":"","title":"On Embedded Choice Theory: Re-framing and Emotions","year":2018,"lang":"en","type":"article","venue":"Review of Economics and Finance","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Framing (construction); Embeddedness; Framing effect; Social psychology; Valence (chemistry); Psychology; Strategic Choice; Positive economics; Cognitive psychology; Epistemology; Sociology; Economics; Persuasion; Philosophy","score_opus":0.0956444263412624,"score_gpt":0.386857831729927,"score_spread":0.2912134053886646,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2900034484","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9806468,0.012742286,0.00016915765,0.00048368046,0.00025191178,0.00013848783,0.000029952684,0.000005221009,0.0055325194],"genre_scores_gemma":[0.83682144,0.16014731,0.0014585566,0.0011110036,0.00007960259,0.0000048309175,0.0000013151966,0.000009810697,0.00036610677],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9987145,0.000052445605,0.00063007354,0.0004145733,0.000059574497,0.00012884109],"domain_scores_gemma":[0.9979672,0.0009434054,0.00041757847,0.0005279404,0.000101573205,0.000042307023],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002049798,0.00011554488,0.0004528374,0.00008176864,0.00012948518,0.00008668755,0.00027152215,0.000051326493,0.000105553816],"category_scores_gemma":[0.0014026834,0.00009023446,0.00007690812,0.00012727856,0.00021101476,0.0001744781,0.0001072301,0.00007311664,0.00009374839],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008020823,0.00002207889,0.00020246842,0.000041433952,0.0000036240742,3.3744305e-7,0.00006568133,0.000007594339,0.0000023516366,0.08459387,0.0014482688,0.91360426],"study_design_scores_gemma":[0.00032423736,0.00030766494,0.0061696954,0.0024538625,0.00003107598,0.0000129937125,0.00009520831,0.0025755598,0.000041891166,0.5399197,0.44777352,0.00029464928],"about_ca_topic_score_codex":0.0000051047923,"about_ca_topic_score_gemma":0.000017229324,"teacher_disagreement_score":0.91330963,"about_ca_system_score_codex":0.000014292348,"about_ca_system_score_gemma":0.00003100649,"threshold_uncertainty_score":0.36796546},"labels":[],"label_agreement":null},{"id":"W2900705341","doi":"10.1111/1911-3846.12590","title":"Revising Audit Plans to Address Fraud Risk: A Case of “Do as I Advise, Not as I Do”?*","year":2020,"lang":"en","type":"article","venue":"Contemporary Accounting Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Audit; Plan (archaeology); Business; Accounting; Public relations; Psychology; Political science","score_opus":0.31517912215259025,"score_gpt":0.4900631619620229,"score_spread":0.17488403980943262,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2900705341","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97169465,0.00049600465,0.0001806676,0.0040156334,0.00035590047,0.0007817327,0.00029446595,0.00008246542,0.022098454],"genre_scores_gemma":[0.99725467,0.00002738809,0.00046368522,0.00083217246,0.00042297476,0.000026495001,0.000008254168,0.000057305566,0.00090703624],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99208456,0.0009307011,0.0018192529,0.0015502018,0.0028294008,0.0007859028],"domain_scores_gemma":[0.98788327,0.0070037097,0.0007972348,0.001636335,0.0019557977,0.0007236638],"candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.016540157,0.00033215893,0.00089671457,0.0010464401,0.0008034542,0.0017853208,0.002460398,0.0002503967,0.0013817145],"category_scores_gemma":[0.04502258,0.0002813578,0.00029669036,0.002893678,0.00030203356,0.0011857125,0.0015746499,0.0012486324,0.0048725167],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020104905,0.00027777575,0.08292483,0.00009171167,0.000069205315,0.0059131533,0.00867661,0.0003834629,0.0026381167,0.00066790695,0.26143754,0.6349092],"study_design_scores_gemma":[0.0043665185,0.0033723617,0.009560532,0.0026140427,0.000072854615,0.0011999343,0.051000856,0.0057244776,0.008004489,0.039844427,0.8717045,0.0025349653],"about_ca_topic_score_codex":0.0011627112,"about_ca_topic_score_gemma":0.000047843972,"teacher_disagreement_score":0.6323742,"about_ca_system_score_codex":0.00009296619,"about_ca_system_score_gemma":0.0009085611,"threshold_uncertainty_score":0.9999639},"labels":[],"label_agreement":null},{"id":"W2901728273","doi":"10.5334/pb.448","title":"Conflict Detection and Logical Complexity","year":2018,"lang":"en","type":"article","venue":"Psychologica Belgica","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"Agence Nationale de la Recherche","keywords":"GRASP; Psychology; Intuition; Inference; Denial; Modus ponens; Normative; Logical analysis; Non-classical logic; Logical reasoning; Empirical evidence; Logical consequence; Epistemology; Cognitive science; Cognitive psychology; Artificial intelligence; Computer science; Mathematics; Philosophy","score_opus":0.4550523134063947,"score_gpt":0.48360980336610876,"score_spread":0.028557489959714077,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2901728273","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9501837,0.000065936685,0.0033237697,0.00098433,0.000798165,0.0001454549,0.00001260048,0.00011826324,0.044367783],"genre_scores_gemma":[0.9955909,0.000023170931,0.002415554,0.0012387616,0.00024732365,0.000009031519,0.0000011145753,0.000007987331,0.0004661231],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99753153,0.00019004029,0.00059824466,0.00088833284,0.00047277063,0.00031905982],"domain_scores_gemma":[0.9980559,0.00058902387,0.00022862531,0.00068807113,0.00023726784,0.00020112636],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0018393187,0.00018477452,0.000349815,0.00016222741,0.0004445423,0.00034534946,0.0006422138,0.00019815101,0.0030918738],"category_scores_gemma":[0.0010729864,0.000118010445,0.000105894476,0.000485555,0.0009774464,0.00016727897,0.00021385627,0.00021134772,0.002559882],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017456443,0.0001741615,0.005497001,4.6128218e-7,0.000006169325,0.000013372049,0.00018726956,5.708867e-7,0.0027373286,0.0015646019,0.0065102004,0.98313427],"study_design_scores_gemma":[0.0005473475,0.0011067294,0.3026209,0.000006144245,0.00001116122,0.00014886042,0.00019918782,0.0004066107,0.00035641846,0.34260985,0.35167658,0.00031021857],"about_ca_topic_score_codex":0.000012818013,"about_ca_topic_score_gemma":0.000037881953,"teacher_disagreement_score":0.9828241,"about_ca_system_score_codex":0.00002278131,"about_ca_system_score_gemma":0.000008246002,"threshold_uncertainty_score":0.99821675},"labels":[],"label_agreement":null},{"id":"W2902702966","doi":"10.1017/cjn.2018.371","title":"Applying Behavioral Economics and Neuroeconomics to Medical Education and Clinical Care","year":2018,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"St. Michael's Hospital; Institute for Clinical Evaluative Sciences; University of Toronto","funders":"","keywords":"Neuroeconomics; Content (measure theory); Action (physics); Psychology; Medical economics; Medical education; Neuroscience; Medicine; MEDLINE; Chemistry; Mathematics","score_opus":0.1287138907167547,"score_gpt":0.4207099877046733,"score_spread":0.2919960969879186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2902702966","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9897531,0.0005564553,0.000022260287,0.0052283043,0.0029424168,0.00021320324,0.000011382778,0.000010434263,0.0012624293],"genre_scores_gemma":[0.98523873,0.0005131772,0.0039378307,0.009579703,0.0006967908,0.000004051713,1.6743613e-7,0.0000124343,0.000017115504],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99445,0.000919634,0.001901691,0.0009861456,0.00077017496,0.0009723934],"domain_scores_gemma":[0.9913652,0.0014181897,0.0010226762,0.0002683211,0.0009013877,0.0050242357],"candidate_categories":["metaresearch","sts","scholarly_communication"],"consensus_categories":["sts"],"category_scores_codex":[0.010823389,0.00032429487,0.0006988541,0.0013800993,0.0027003854,0.0024554168,0.0028592977,0.00029517073,0.0002408794],"category_scores_gemma":[0.011413191,0.00022589053,0.00020842098,0.0008705279,0.008629786,0.0012879785,0.00029691454,0.0009973071,0.000016969962],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004062036,0.000029165578,0.55568796,7.860197e-7,0.0000031077209,0.00028227147,0.00036976763,0.00008946094,8.1349003e-7,0.0005349771,0.0006919554,0.4422691],"study_design_scores_gemma":[0.0010433088,0.16129497,0.41398346,0.0001169126,0.00013112955,0.057769507,0.0060972753,0.0060349964,0.000030065657,0.19123499,0.16088441,0.0013789654],"about_ca_topic_score_codex":0.0008761135,"about_ca_topic_score_gemma":0.10782287,"teacher_disagreement_score":0.44089013,"about_ca_system_score_codex":0.00017897098,"about_ca_system_score_gemma":0.00795253,"threshold_uncertainty_score":0.998598},"labels":[],"label_agreement":null},{"id":"W2903080575","doi":"10.1016/j.econlet.2018.11.030","title":"Prior knowledge and monotone decision problems","year":2018,"lang":"en","type":"article","venue":"Economics Letters","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Monotone polygon; Mathematical economics; Mathematics; Econometrics; Economics","score_opus":0.07826004492651611,"score_gpt":0.3583961312109026,"score_spread":0.28013608628438647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2903080575","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.990129,0.00010417737,0.0032733032,0.0017698945,0.001507447,0.00022451366,0.000014630735,0.00004942179,0.0029276018],"genre_scores_gemma":[0.992182,0.000053638738,0.005273724,0.0016523439,0.00042141738,0.000012573353,0.0000019577594,0.000030373498,0.00037195694],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99763495,0.000057621335,0.00090522674,0.0008848827,0.00015531704,0.0003620266],"domain_scores_gemma":[0.9975269,0.0009889649,0.0003081894,0.0008440002,0.000119506396,0.0002124672],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0019491715,0.00023042063,0.00041388985,0.00039014357,0.0003017037,0.0006547119,0.00078297214,0.00011497496,0.00032439313],"category_scores_gemma":[0.00043747213,0.00019569165,0.00012274884,0.00022161282,0.00034815836,0.0005658043,0.00038154595,0.00015085471,0.003054102],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000044803783,0.000048101152,0.0061878455,0.0000012366586,0.000009682523,0.0000025728527,0.0006165817,0.000115573996,0.0008862811,0.00039287016,0.020888578,0.9708059],"study_design_scores_gemma":[0.0019720327,0.00035908277,0.0386949,0.000076810786,0.000036343947,0.00009377917,0.00041508357,0.017703513,0.0016482433,0.17645232,0.76142,0.0011278592],"about_ca_topic_score_codex":0.00001945704,"about_ca_topic_score_gemma":0.00016582136,"teacher_disagreement_score":0.969678,"about_ca_system_score_codex":0.00011113206,"about_ca_system_score_gemma":0.000052893593,"threshold_uncertainty_score":0.99772215},"labels":[],"label_agreement":null},{"id":"W2903695383","doi":"10.2196/12265","title":"The Effects of Positive Affect and Episodic Future Thinking on Temporal Discounting and Healthy Food Demand and Choice Among Overweight and Obese Individuals: Protocol for a Pilot 2×2 Factorial Randomized Controlled Study","year":2018,"lang":"en","type":"article","venue":"JMIR Research Protocols","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Complementary and Integrative Health; National Institute on Alcohol Abuse and Alcoholism; Cancer Research UK","keywords":"Affect (linguistics); Overweight; Randomized controlled trial; Delay discounting; Psychology; Food choice; Temporal discounting; Gerontology; Obesity; Social psychology; Medicine; Clinical psychology; Impulsivity","score_opus":0.20585762707426264,"score_gpt":0.562214107340927,"score_spread":0.3563564802666644,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2903695383","genre_codex":"protocol","genre_gemma":"protocol","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"protocol","genre_consensus":"protocol","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.47617593,0.000012046468,0.00003366935,0.00012017277,0.000033421227,0.5235675,0.000012904393,0.000011569718,0.000032758155],"genre_scores_gemma":[0.41317955,0.0000010924213,0.00008341633,0.000017481196,0.00033172805,0.5863453,4.8045086e-7,0.000017808976,0.000023143728],"study_design_codex":"randomized_trial","study_design_gemma":"randomized_trial","domain_scores_codex":[0.9915447,0.0039599426,0.0011895006,0.0009750208,0.0017000351,0.0006307744],"domain_scores_gemma":[0.9551483,0.04265481,0.0008153244,0.000501938,0.0006180481,0.0002615849],"candidate_categories":["metaresearch","sts","scholarly_communication"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.029018998,0.0003607888,0.0015426711,0.00043524345,0.0017545237,0.0021399565,0.00052636914,0.00016514047,0.000005610529],"category_scores_gemma":[0.013455279,0.00018210086,0.00012703703,0.00037196552,0.0014664658,0.0005626362,0.0006297372,0.0005602929,0.0000012069952],"study_design_candidate":"randomized_trial","study_design_consensus":"randomized_trial","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.6004261,0.0024164724,0.28841686,0.0008462093,0.0003539947,0.000012442484,0.010404264,3.5127138e-7,0.00032476347,0.0014676818,0.0014656052,0.09386529],"study_design_scores_gemma":[0.7334533,0.07719168,0.10972947,0.0036678077,0.000056387536,0.000009596732,0.002183193,0.00059854216,0.0004249233,0.067253806,0.0048440737,0.00058721734],"about_ca_topic_score_codex":0.00006350823,"about_ca_topic_score_gemma":0.00033237986,"teacher_disagreement_score":0.1786874,"about_ca_system_score_codex":0.00004878292,"about_ca_system_score_gemma":0.00016119827,"threshold_uncertainty_score":0.9998293},"labels":[],"label_agreement":null},{"id":"W2908341264","doi":"10.3758/s13421-018-0888-3","title":"Probability matching does not decrease under cognitive load: A preregistered failure to replicate","year":2019,"lang":"en","type":"article","venue":"Memory & Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Waterloo","funders":"Australian Research Council; Natural Sciences and Engineering Research Council of Canada; Max-Planck-Gesellschaft","keywords":"Psychology; Replicate; Cognitive load; Cognition; Task (project management); Matching (statistics); Cognitive psychology; Contrast (vision); Sample (material); Selection (genetic algorithm); Cognitive resource theory; Bayesian probability; Social psychology; Statistics; Artificial intelligence; Computer science","score_opus":0.13954008636621287,"score_gpt":0.3720364253891622,"score_spread":0.23249633902294933,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2908341264","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9864748,0.000006012659,0.0021686645,0.0017156809,0.00046719942,0.0013007384,0.00017513469,0.00013757458,0.0075541646],"genre_scores_gemma":[0.9931261,8.960885e-7,0.0015592196,0.002460308,0.00008942656,0.00009767465,0.00003305925,0.000029882916,0.002603468],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9958563,0.0002901403,0.0009172032,0.0014028735,0.0011336646,0.00039980648],"domain_scores_gemma":[0.9957187,0.0014297629,0.00041262535,0.001089083,0.0009694486,0.00038036055],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00311865,0.0002920615,0.00048155434,0.0002455009,0.0002083482,0.0006203201,0.00057299744,0.00016340717,0.0022651828],"category_scores_gemma":[0.003434263,0.00020883737,0.00022376113,0.0004727598,0.000101598336,0.0006946369,0.00029818085,0.00026031464,0.00721654],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002470023,0.0009328805,0.0028866644,0.000056557205,0.00007250019,0.00005137023,0.0030795583,0.0003839545,0.04762207,0.00022767138,0.004335025,0.9378817],"study_design_scores_gemma":[0.0058858576,0.00096887094,0.052671615,0.0011608641,0.0004021674,0.00016765903,0.017809484,0.0008633833,0.0603316,0.84495866,0.012265726,0.0025141123],"about_ca_topic_score_codex":0.00009876556,"about_ca_topic_score_gemma":0.0004814996,"teacher_disagreement_score":0.93536764,"about_ca_system_score_codex":0.00018541199,"about_ca_system_score_gemma":0.00023364254,"threshold_uncertainty_score":0.99864686},"labels":[],"label_agreement":null},{"id":"W2908473914","doi":"10.1016/j.beproc.2018.12.009","title":"Comparative inspiration: From puzzles with pigeons to novel discoveries with humans in risky choice","year":2019,"lang":"en","type":"review","venue":"Behavioural Processes","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Alberta Gambling Research Institute, University of Calgary; Natural Sciences and Engineering Research Council of Canada","keywords":"Odds; Psychology; Judgement; Outcome (game theory); Perspective (graphical); Social psychology; Cognitive psychology; Computer science; Logistic regression; Artificial intelligence; Epistemology","score_opus":0.48593856625511117,"score_gpt":0.47889419232334324,"score_spread":0.007044373931767933,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2908473914","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2764074,0.7156299,0.00084145437,0.00017575371,0.0005151675,0.002965558,0.002377144,0.00013434011,0.0009533261],"genre_scores_gemma":[0.32424554,0.6540742,0.009309109,0.00046947313,0.0007381744,0.0020466775,0.0016864829,0.0004997606,0.0069306204],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99466646,0.00013230347,0.0016633634,0.0016983454,0.0013141126,0.00052544574],"domain_scores_gemma":[0.9946363,0.0020307605,0.0012809153,0.001184105,0.00064541784,0.00022251095],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00051961903,0.00089944433,0.0032888176,0.00073376426,0.000261154,0.0015639492,0.001874712,0.00031090682,0.00029304074],"category_scores_gemma":[0.00053252454,0.0005137899,0.00021483225,0.0023075063,0.00026115298,0.0014162057,0.00031479402,0.00064384146,0.0008645928],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002724917,0.0013972246,0.049404133,0.0012355892,0.00012408031,0.000081097656,0.003241428,0.0005292358,0.0000017507899,0.00009304423,0.0015681357,0.94205177],"study_design_scores_gemma":[0.001118581,0.0008172283,0.009414786,0.014539143,0.0009523555,0.000038685295,0.0018828575,0.0000056697786,0.000013597099,0.00047739965,0.96883327,0.0019064281],"about_ca_topic_score_codex":0.001605117,"about_ca_topic_score_gemma":0.03887138,"teacher_disagreement_score":0.9672651,"about_ca_system_score_codex":0.00017764965,"about_ca_system_score_gemma":0.0014384366,"threshold_uncertainty_score":0.99991333},"labels":[],"label_agreement":null},{"id":"W2910780493","doi":"10.5539/ijef.v11n2p50","title":"Confirmation Bias in Investments","year":2018,"lang":"en","type":"article","venue":"International Journal of Economics and Finance","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Eurostars","keywords":"Confirmation bias; Investment (military); Disposition effect; Investment decisions; Negative information; Economics; Inside information; Business; Positive economics; Microeconomics; Monetary economics; Financial economics; Actuarial science; Psychology; Social psychology; Behavioral economics; Law; Political science","score_opus":0.1984289546880739,"score_gpt":0.40379717193395537,"score_spread":0.20536821724588147,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2910780493","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99521065,0.000071605384,0.00014351877,0.0011126912,0.0016617732,0.000024667594,0.000009884474,8.630045e-7,0.0017643704],"genre_scores_gemma":[0.99688864,0.00061061996,0.0017269045,0.00044573515,0.0002209627,4.788181e-7,5.532021e-7,0.000003498189,0.000102586266],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9988131,0.000023882869,0.00081897987,0.00013508453,0.00013374542,0.00007522703],"domain_scores_gemma":[0.9985796,0.00020894104,0.0007009427,0.000104713625,0.00037610295,0.000029651195],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013028209,0.00006238141,0.0001752174,0.00033222337,0.000026291691,0.00022907503,0.0004763989,0.00004010822,0.000053715034],"category_scores_gemma":[0.00045238849,0.000051537692,0.000052684107,0.00006723311,0.000088253444,0.00053521426,0.00006869638,0.00007757014,0.00006883406],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001119342,0.00006484385,0.016895568,2.1406466e-7,0.000013477301,0.000018398217,0.0003775868,0.0011039774,0.000016946922,0.01999314,0.0012830684,0.96012086],"study_design_scores_gemma":[0.001170243,0.0001851953,0.06433715,0.00005146721,0.0000037921718,0.00017179387,0.00017280958,0.029369853,0.0003860237,0.64053535,0.26347068,0.00014564984],"about_ca_topic_score_codex":0.0000155302,"about_ca_topic_score_gemma":0.000064249725,"teacher_disagreement_score":0.9599752,"about_ca_system_score_codex":0.000064079075,"about_ca_system_score_gemma":0.00006587961,"threshold_uncertainty_score":0.22089759},"labels":[],"label_agreement":null},{"id":"W2911532086","doi":"10.3758/s13423-018-1555-1","title":"A statistical test for the optimality of deliberative time allocation","year":2019,"lang":"en","type":"article","venue":"Psychonomic Bulletin & Review","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":21,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Deliberation; Variety (cybernetics); Incentive; Rationality; Test (biology); Psychology; Task (project management); Consistency (knowledge bases); Dynamic inconsistency; Microeconomics; Economics; Cognitive psychology; Computer science; Artificial intelligence","score_opus":0.09454468385242114,"score_gpt":0.4226450988256062,"score_spread":0.32810041497318504,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2911532086","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.45347694,0.12975414,0.15784696,0.17697841,0.0075613535,0.024081614,0.0029146343,0.00025716017,0.047128774],"genre_scores_gemma":[0.80994684,0.026348319,0.124059804,0.017300697,0.00055205956,0.00093387184,0.0001306142,0.00015298376,0.020574812],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99768203,0.00014959252,0.0011801563,0.0005128947,0.00029089046,0.0001844362],"domain_scores_gemma":[0.989681,0.008418458,0.00056957867,0.0009544833,0.00030975146,0.00006673931],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00461196,0.00015637644,0.00059083937,0.000044836153,0.000076721815,0.0000975212,0.0008209661,0.000053999654,0.008630723],"category_scores_gemma":[0.0028021706,0.0000937776,0.00021859478,0.00016289073,0.00010848192,0.000057126013,0.000075784366,0.00011022871,0.009546194],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000043381064,0.00011340991,0.00037667566,0.00007494925,0.000014799982,1.5769773e-7,0.000033052333,0.000056104243,0.00006604211,0.0008093934,0.30201873,0.6963933],"study_design_scores_gemma":[0.0003590293,0.00016159151,0.0019397634,0.00045296602,0.000070145696,0.0000061578394,0.00003506623,0.0018240608,0.00001819449,0.007434502,0.98752797,0.00017056678],"about_ca_topic_score_codex":0.000013856503,"about_ca_topic_score_gemma":0.0000018672554,"teacher_disagreement_score":0.6962227,"about_ca_system_score_codex":0.000040565476,"about_ca_system_score_gemma":0.000069138485,"threshold_uncertainty_score":0.99227554},"labels":[],"label_agreement":null},{"id":"W2914258438","doi":"10.1002/jcpy.1098","title":"Compared to Dematerialized Money, Cash Increases Impatience in Intertemporal Choice","year":2019,"lang":"en","type":"article","venue":"Journal of Consumer Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Cash; Economics; Intertemporal choice; Patience; Dynamic inconsistency; Monetary economics; Microeconomics; Psychology; Finance; Social psychology","score_opus":0.14118398296251916,"score_gpt":0.4745694727849915,"score_spread":0.33338548982247235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2914258438","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9949451,0.00014820998,0.00021752907,0.00069559686,0.0030970478,0.00017305037,0.000011417432,0.000007672916,0.00070436846],"genre_scores_gemma":[0.9970469,0.000014895397,0.0013956819,0.001363041,0.00006467829,0.0000027838414,6.598015e-7,0.000011804862,0.00009957416],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99652857,0.00039583078,0.0018852968,0.00037654093,0.0005165181,0.0002972629],"domain_scores_gemma":[0.99658346,0.0012110312,0.0009899682,0.0005745879,0.00040084065,0.00024011389],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0026938934,0.00017277003,0.00085540407,0.0008954316,0.00003183261,0.00017689282,0.0012138641,0.00012099541,0.0013370115],"category_scores_gemma":[0.0017484541,0.00012612285,0.00016589079,0.0005174702,0.00009424635,0.00041196978,0.00014720364,0.00025159257,0.001203026],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011639547,0.00036423662,0.88543004,0.000002258137,0.000021416148,0.00011484914,0.00042069686,0.00009369912,0.0051134,0.000018665298,0.020133805,0.08712298],"study_design_scores_gemma":[0.006129119,0.0011331098,0.86468226,0.00021354016,0.00003412316,0.0012019244,0.00063826627,0.00021480293,0.00032791524,0.016312644,0.10861906,0.00049323705],"about_ca_topic_score_codex":0.00023092495,"about_ca_topic_score_gemma":0.00024581002,"teacher_disagreement_score":0.08848525,"about_ca_system_score_codex":0.000062078296,"about_ca_system_score_gemma":0.00011532801,"threshold_uncertainty_score":0.9995759},"labels":[],"label_agreement":null},{"id":"W2916607818","doi":"10.3982/te3647","title":"Gradual pairwise comparison and stochastic choice","year":2020,"lang":"en","type":"article","venue":"Theoretical Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Pairwise comparison; Transitive relation; Preference; Preference relation; Similarity (geometry); Mathematical economics; Computer science; Order (exchange); Econometrics; Mathematics; Artificial intelligence; Economics; Statistics; Combinatorics","score_opus":0.17045502142091484,"score_gpt":0.3911482955049835,"score_spread":0.22069327408406864,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2916607818","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9778252,0.00005501642,0.013759192,0.0051072952,0.000288507,0.0001371121,0.00003366363,0.0000669723,0.0027270336],"genre_scores_gemma":[0.9968945,0.000008828246,0.0010529152,0.0017855573,0.00020853002,0.0000042419683,0.0000035985322,0.000022449103,0.000019391946],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.997828,0.00008688086,0.0008798938,0.0006949466,0.00019709277,0.00031316248],"domain_scores_gemma":[0.99606913,0.0026948033,0.00020792022,0.000440663,0.0000675611,0.0005198972],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0010769505,0.0002091796,0.00056872715,0.00008435335,0.00013043538,0.0004486136,0.0006819526,0.000121628815,0.0009141754],"category_scores_gemma":[0.0031272455,0.00017201196,0.00012060388,0.00015572702,0.0007792617,0.0002272156,0.00035311162,0.00026091057,0.0012464342],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014692124,0.000073087416,0.0022623637,0.0000024093947,0.000012423008,0.0000034767036,0.00061169366,0.0021351194,0.000021579935,0.66276395,0.0020958479,0.32987112],"study_design_scores_gemma":[0.0005381508,0.00022957294,0.0012642642,0.0000063155226,0.000028654278,0.000009803852,0.0004330352,0.16457611,0.000039771578,0.82649374,0.006071714,0.0003088465],"about_ca_topic_score_codex":0.000004914705,"about_ca_topic_score_gemma":0.000007084587,"teacher_disagreement_score":0.32956228,"about_ca_system_score_codex":0.000036780173,"about_ca_system_score_gemma":0.00004991532,"threshold_uncertainty_score":0.9999991},"labels":[],"label_agreement":null},{"id":"W2917640324","doi":"10.5167/uzh-95109","title":"How Time Preferences Differ: Evidence from 45 Countries","year":2009,"lang":"en","type":"article","venue":"Zurich Open Repository and Archive (University of Zurich)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Universität Innsbruck; Alpen-Adria-Universität Klagenfurt; Fudan University; Peking University; LOEWE Zentrum AdRIA; University of Windsor","keywords":"Hofstede's cultural dimensions theory; Hyperbolic discounting; Time preference; Inflation (cosmology); Individualism; Discounting; Scale (ratio); Economics; World Values Survey; Econometrics; Psychology; Social psychology; Microeconomics; Geography","score_opus":0.07483483675299946,"score_gpt":0.2987708226638049,"score_spread":0.22393598591080544,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2917640324","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98944396,0.0003353359,0.0028535519,0.0014600599,0.00016361054,0.00023854502,0.0000983114,0.000031172844,0.00537545],"genre_scores_gemma":[0.98479044,0.00017919757,0.0077007757,0.00008034973,0.000053119507,2.7738437e-7,0.000008449721,0.0000058357296,0.007181531],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9975476,0.0005789413,0.0003028482,0.0007476833,0.00059469155,0.00022818876],"domain_scores_gemma":[0.9952776,0.0032002912,0.00047130577,0.00065935304,0.00018750601,0.00020394882],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001264314,0.00020002399,0.00053953717,0.000196405,0.0006943373,0.0009621438,0.0021058202,0.00009526159,0.00020024252],"category_scores_gemma":[0.00034798362,0.00017575036,0.00012314398,0.0002625582,0.0003636283,0.0018561141,0.00074667967,0.0001785746,0.00010241028],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0025162708,0.00086039846,0.15879746,0.000023771627,0.00020782741,0.00070073537,0.017950298,0.000093423696,0.046979316,0.0017616625,0.15187828,0.6182306],"study_design_scores_gemma":[0.0012872065,0.0013237847,0.687162,0.0005117709,0.00022044289,0.000060032737,0.0066481032,0.0018439625,0.0020600008,0.2376049,0.06032143,0.0009563677],"about_ca_topic_score_codex":0.00040993528,"about_ca_topic_score_gemma":0.000080835176,"teacher_disagreement_score":0.61727417,"about_ca_system_score_codex":0.000028164688,"about_ca_system_score_gemma":0.00009930065,"threshold_uncertainty_score":0.9277975},"labels":[],"label_agreement":null},{"id":"W2919328485","doi":"10.1609/aaai.v33i01.33017949","title":"Rethinking the Discount Factor in Reinforcement Learning: A Decision Theoretic Approach","year":2019,"lang":"en","type":"preprint","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Discounting; Reinforcement learning; Axiom; Markov decision process; Bellman equation; Generalization; Mathematical economics; Expected utility hypothesis; Preference; Computer science; Revealed preference; Decision theory; Markov process; Mathematics; Econometrics; Economics; Artificial intelligence; Microeconomics; Statistics","score_opus":0.24995316240911114,"score_gpt":0.3937038071337248,"score_spread":0.14375064472461369,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2919328485","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9666739,0.000048139955,0.0096385125,0.0015505471,0.0017593898,0.0014752155,0.000014654574,0.00004449437,0.018795116],"genre_scores_gemma":[0.9981618,0.00011870909,0.00066755066,0.00014772206,0.00010438167,0.00006996493,0.0000024871476,0.000037811802,0.00068957655],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9926531,0.0001355228,0.0024998768,0.0014950067,0.002634376,0.00058211753],"domain_scores_gemma":[0.9931783,0.0019114647,0.0023186097,0.0012940064,0.0011910219,0.000106595326],"candidate_categories":["metaepi_narrow","scholarly_communication","open_science","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.006432599,0.0005972717,0.000975492,0.00052357704,0.0003518675,0.0017145923,0.00672311,0.0004889012,0.00042953965],"category_scores_gemma":[0.007977975,0.00031541672,0.00045819633,0.0009147881,0.0007209711,0.00031111555,0.0033709155,0.0025917199,0.0003759669],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00067745615,0.0003692552,0.0038507695,0.00008876982,0.000034551085,0.00000147039,0.01800542,0.11312904,0.0011756105,0.34261313,0.00034783554,0.5197067],"study_design_scores_gemma":[0.000038147766,0.00015662974,0.0004345086,0.0008904648,0.000024224617,0.0000030491456,0.0035576832,0.17285325,0.0048193266,0.8166537,0.00019811797,0.00037089185],"about_ca_topic_score_codex":0.00012097959,"about_ca_topic_score_gemma":0.000033307315,"teacher_disagreement_score":0.5193358,"about_ca_system_score_codex":0.00026961116,"about_ca_system_score_gemma":0.00037408265,"threshold_uncertainty_score":0.9999298},"labels":[],"label_agreement":null},{"id":"W2925235104","doi":"10.1017/s0140525x18001875","title":"How uncertainty begets hope: A model of adaptive and maladaptive seeking behavior","year":2019,"lang":"en","type":"letter","venue":"Behavioral and Brain Sciences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health","funders":"","keywords":"Hoarding (animal behavior); Psychology; Incentive; Social psychology; Cognitive psychology; Feeding behavior; Economics; Microeconomics; Medicine","score_opus":0.2372149180738014,"score_gpt":0.3829963734115134,"score_spread":0.14578145533771197,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2925235104","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8847989,0.00042596072,0.0003956815,0.11155463,0.00071258453,0.0008104551,0.0008666494,0.00004684206,0.00038829583],"genre_scores_gemma":[0.9475278,0.00006234052,0.0046818024,0.038682576,0.00043314908,0.00008082401,0.00003675735,0.000059651324,0.008435078],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99317175,0.0003064713,0.0011314295,0.0021835421,0.0023808563,0.0008259703],"domain_scores_gemma":[0.99531627,0.0018716544,0.0012777031,0.0008263264,0.0005271495,0.00018087077],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.003090309,0.00072771433,0.0014496731,0.00093346596,0.00053768966,0.0016294129,0.0017480248,0.0008881401,0.000058189235],"category_scores_gemma":[0.0004710353,0.0005101012,0.00033889562,0.0007994263,0.0025800613,0.0012335588,0.00095257186,0.0011518898,0.000020880427],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011263272,0.00030278933,0.014900492,0.000041463507,0.000029568757,0.00026857582,0.0020347408,0.0004848313,0.0020026485,0.00036445542,0.37835744,0.6011004],"study_design_scores_gemma":[0.0077376436,0.016096883,0.025340807,0.003179857,0.0029145903,0.0013984635,0.0335728,0.21939069,0.0010242441,0.19378921,0.48065126,0.014903561],"about_ca_topic_score_codex":0.00038097354,"about_ca_topic_score_gemma":0.00015032837,"teacher_disagreement_score":0.5861968,"about_ca_system_score_codex":0.00008302287,"about_ca_system_score_gemma":0.00042085262,"threshold_uncertainty_score":0.99973506},"labels":[],"label_agreement":null},{"id":"W2927601509","doi":"10.1017/s1930297500006604","title":"Why choose wisely if you have already paid? Sunk costs elicit stochastic dominance violations","year":2018,"lang":"en","type":"article","venue":"Judgment and Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Trinity College","funders":"","keywords":"Sunk costs; Stochastic dominance; Economics; Irrational number; Dominance (genetics); Status quo; Microeconomics; Econometrics; Prospect theory; Expected utility hypothesis; Mathematical economics; Mathematics","score_opus":0.08666690225901935,"score_gpt":0.38749835216467315,"score_spread":0.3008314499056538,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2927601509","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.84544694,0.000252221,0.14919856,0.00047313192,0.0014408749,0.00042082855,0.00004476521,0.00008546041,0.002637214],"genre_scores_gemma":[0.9841221,0.00002922286,0.013190931,0.001714414,0.00042961145,0.000028166029,0.000004716259,0.000040212977,0.0004406467],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9949014,0.00011830254,0.0014963155,0.0013019198,0.0015580023,0.0006240374],"domain_scores_gemma":[0.9934661,0.0036381509,0.00067212456,0.0012188088,0.0007052664,0.00029954183],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0028557493,0.00042654815,0.0006733501,0.00072531647,0.0009005068,0.0013117952,0.0009567104,0.00023227892,0.00094321265],"category_scores_gemma":[0.0031546417,0.00033281313,0.00022307706,0.0007572384,0.00030069327,0.00083529623,0.0005806081,0.0002878497,0.0012207667],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028241353,0.00011199314,0.0044884034,0.0000011737201,0.0000104565715,0.00001710538,0.00038071413,0.00029885094,0.00012879499,0.0005034273,0.030208021,0.9635686],"study_design_scores_gemma":[0.0038611647,0.00089380896,0.070788816,0.0012017912,0.00016892131,0.00015495492,0.0025544204,0.11835269,0.00021756077,0.64391005,0.15599252,0.0019033289],"about_ca_topic_score_codex":0.00004967921,"about_ca_topic_score_gemma":0.00020770016,"teacher_disagreement_score":0.96166533,"about_ca_system_score_codex":0.00019636529,"about_ca_system_score_gemma":0.000077194534,"threshold_uncertainty_score":0.9999701},"labels":[],"label_agreement":null},{"id":"W2932161991","doi":"10.1101/598466","title":"Behavioural and neural interactions between objective and subjective performance in a Matching Pennies game","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University; University of Alberta","funders":"","keywords":"Outcome (game theory); Optimism; Contingency; Psychology; Matching (statistics); Negativity effect; Social psychology; Contrast (vision); Competition (biology); Trustworthiness; Contingency table; Ultimatum game; Statistics; Cognitive psychology; Econometrics; Economics; Mathematics; Microeconomics; Computer science; Artificial intelligence","score_opus":0.06622057945594605,"score_gpt":0.31716383471988235,"score_spread":0.2509432552639363,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2932161991","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99713236,0.00030302274,0.00020526003,0.00013083946,0.0012634455,0.0006228165,0.00022532928,0.00009994684,0.000016953147],"genre_scores_gemma":[0.9987305,0.00008930538,0.00082303263,0.000054275217,0.00015525107,0.00006833214,2.7201276e-7,0.0000673283,0.0000117296695],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9960046,0.000257848,0.0010615011,0.0015670003,0.00058564276,0.0005234506],"domain_scores_gemma":[0.99653006,0.0010048639,0.0007336068,0.0010507888,0.00044366578,0.0002370326],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0018050001,0.00057034544,0.0010092685,0.0009901286,0.0002058716,0.0011864447,0.00073552906,0.0003828466,0.000030679716],"category_scores_gemma":[0.0005925199,0.0005325765,0.00013965773,0.0005602333,0.00023969043,0.0009898099,0.0013619998,0.0014356393,0.00006327777],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000054160784,0.00005770794,0.9965994,0.000031980293,0.00002988619,0.000023606735,0.0002876587,0.00024858568,0.0023072201,0.000028281112,0.000014070327,0.0003174533],"study_design_scores_gemma":[0.0004266696,0.00008332396,0.99427474,0.0003121797,0.00006523091,2.0522148e-7,0.0001409098,0.0021702931,0.0016821614,0.00012304302,0.000105642896,0.00061559654],"about_ca_topic_score_codex":0.00038759699,"about_ca_topic_score_gemma":0.00008564871,"teacher_disagreement_score":0.002324645,"about_ca_system_score_codex":0.00033321895,"about_ca_system_score_gemma":0.0002727994,"threshold_uncertainty_score":0.9998504},"labels":[],"label_agreement":null},{"id":"W2936326179","doi":"10.3819/ccbr.2019.140006","title":"The Case for a Heuristic Approach to Account for Suboptimal Choice","year":2019,"lang":"en","type":"article","venue":"Comparative Cognition & Behavior Reviews","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Margin (machine learning); Space (punctuation); Heuristic; Line (geometry); Psychology; White (mutation); Selection (genetic algorithm); Font; Arithmetic; Statistics; Mathematics; Artificial intelligence; Computer science; Machine learning; Biology; Geometry","score_opus":0.4844919538919981,"score_gpt":0.509163919179003,"score_spread":0.024671965287004938,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2936326179","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9365296,0.0016759468,0.045550372,0.0001883676,0.0012803975,0.01197549,0.0005194213,0.000049281767,0.0022311606],"genre_scores_gemma":[0.97804326,0.000069873495,0.012575332,0.0004923261,0.00020406905,0.00673521,0.00009406251,0.000032349322,0.0017534965],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9965598,0.00026339423,0.0014408672,0.0009227902,0.0003796457,0.000433504],"domain_scores_gemma":[0.99287224,0.004176421,0.0006643352,0.000884285,0.0011931149,0.0002095864],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0038523832,0.00033281595,0.00092438544,0.00017197922,0.00067135226,0.00083185645,0.0008373649,0.00009005115,0.0001463621],"category_scores_gemma":[0.0022114017,0.00020535602,0.00051975506,0.00050245196,0.00010665038,0.00035653292,0.00013448452,0.00017251435,0.0021168266],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034032008,0.00073397724,0.0009016048,0.00004239836,0.000018321865,0.000010951109,0.0006328849,0.000092126946,0.0005343889,0.0011639001,0.102454096,0.89307505],"study_design_scores_gemma":[0.0011406216,0.00048273543,0.0013508368,0.00008637618,0.00026444445,0.00018784964,0.0011322998,0.003067983,0.00012637122,0.003862663,0.9877899,0.00050789147],"about_ca_topic_score_codex":0.000008843438,"about_ca_topic_score_gemma":0.00006760387,"teacher_disagreement_score":0.89256716,"about_ca_system_score_codex":0.00009147082,"about_ca_system_score_gemma":0.0000727245,"threshold_uncertainty_score":0.99866015},"labels":[],"label_agreement":null},{"id":"W2936701616","doi":"10.5539/ijsp.v8n3p46","title":"An Essential Analogy Between Coherent Previsions of Random Gains and Well-Behaved Preferences","year":2019,"lang":"en","type":"article","venue":"International Journal of Statistics and Probability","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Coherence (philosophical gambling strategy); Mathematics; Analogy; Mathematical economics; Decision maker; Regular polygon; Expected utility hypothesis; Set (abstract data type); Mathematical optimization; Computer science; Statistics","score_opus":0.08372914305427011,"score_gpt":0.4154550330500134,"score_spread":0.3317258899957433,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2936701616","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9793019,0.000060763392,0.019337075,0.0001381066,0.0005083227,0.00014275016,0.00034676955,0.0000023186988,0.00016194803],"genre_scores_gemma":[0.99030983,0.000084755586,0.009470907,0.00001603198,0.000080023296,7.954937e-7,0.000010116771,0.0000042328275,0.000023280385],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99751264,0.00021213696,0.0011714677,0.00025189662,0.00075303804,0.000098843164],"domain_scores_gemma":[0.9957625,0.0018513158,0.0008724629,0.00020480661,0.0011729152,0.0001359979],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00231805,0.00010691761,0.0004443818,0.0001819113,0.00004034381,0.00020249169,0.00052019407,0.00006212472,0.0005144736],"category_scores_gemma":[0.0008702045,0.000073600284,0.00006933154,0.000071736664,0.00020979768,0.00027418215,0.00011135982,0.00015379129,0.0000066978987],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036626673,0.00020829469,0.62227905,0.000010240361,0.000066934364,0.000006556172,0.00045787814,0.0001984126,0.0002782242,0.0023590387,0.00021698975,0.3735521],"study_design_scores_gemma":[0.0015705324,0.00068511633,0.47463813,0.00006558121,0.00006375217,0.00003077535,0.00022947187,0.0018993671,0.00015051266,0.5195353,0.0010027578,0.00012868918],"about_ca_topic_score_codex":0.000041716314,"about_ca_topic_score_gemma":0.000045867477,"teacher_disagreement_score":0.5171763,"about_ca_system_score_codex":0.000025316815,"about_ca_system_score_gemma":0.000111589616,"threshold_uncertainty_score":0.5633125},"labels":[],"label_agreement":null},{"id":"W2937891012","doi":"10.3819/ccbr.2019.140001","title":"What Suboptimal Choice Tells Us About the Control of Behavior","year":2019,"lang":"en","type":"article","venue":"Comparative Cognition & Behavior Reviews","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Margin (machine learning); White (mutation); Psychology; Line (geometry); Animal behavior; Space (punctuation); Mathematics; Arithmetic; Social psychology; Computer science; Biology; Zoology; Geometry; Machine learning","score_opus":0.3171822628679781,"score_gpt":0.47071811886844933,"score_spread":0.1535358560004712,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2937891012","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9847334,0.0073160282,0.00046770275,0.00010440041,0.0020243928,0.0036029378,0.00014426632,0.00003665381,0.0015701916],"genre_scores_gemma":[0.9960228,0.001147139,0.0002933013,0.00053216534,0.00011219971,0.0006327206,0.00004169037,0.000025750602,0.0011922006],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.994153,0.00094588345,0.0024465343,0.0009242193,0.0010954285,0.00043491725],"domain_scores_gemma":[0.9932712,0.0021231878,0.0017829359,0.0014399297,0.0011873859,0.00019539591],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.003432134,0.00046611097,0.0016472543,0.00027684157,0.0002505219,0.000774547,0.0014424684,0.00016390446,0.0051620016],"category_scores_gemma":[0.00059904874,0.0002865863,0.000757946,0.000818496,0.00042438044,0.0014593351,0.00018213781,0.00046275562,0.009124371],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015445198,0.00134657,0.15816647,0.000021384769,0.000029973271,0.000014838177,0.0009189657,0.00005704197,0.010748604,0.00018114163,0.007416726,0.82094383],"study_design_scores_gemma":[0.003143789,0.000778535,0.5123574,0.0008486712,0.0013101128,0.00007621199,0.0018864016,0.00044062446,0.0038630208,0.0011271499,0.4730416,0.0011264861],"about_ca_topic_score_codex":0.00002139876,"about_ca_topic_score_gemma":0.00005647453,"teacher_disagreement_score":0.81981736,"about_ca_system_score_codex":0.00007594915,"about_ca_system_score_gemma":0.000103702,"threshold_uncertainty_score":0.99995863},"labels":[],"label_agreement":null},{"id":"W2939024220","doi":"","title":"Street-level bureaucracy: best to be grey (or silver) on Friday, in Halifax","year":2019,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Favourite; Bureaucracy; Certificate; Demographic economics; Variation (astronomy); Advertising; Test (biology); Psychology; Demography; Economics; Business; Political science; Sociology; Politics; Computer science; Law","score_opus":0.3015787825574317,"score_gpt":0.46488405563472557,"score_spread":0.16330527307729387,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2939024220","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9300727,0.000035658057,0.000009428275,0.0019990706,0.002071804,0.0015862779,0.00094849954,0.000039987368,0.06323653],"genre_scores_gemma":[0.98395777,0.0011633663,0.0017335778,0.00084055547,0.00032823972,0.00025057804,0.00006599962,0.00013894413,0.011520969],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9896031,0.00080286706,0.0027939759,0.0034321684,0.0017318118,0.0016360484],"domain_scores_gemma":[0.9863668,0.007271243,0.00065158773,0.004537894,0.00049523177,0.0006772591],"candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.011950845,0.0007875351,0.001812867,0.0035934132,0.00021825964,0.0014095762,0.004917718,0.0011359248,0.000865705],"category_scores_gemma":[0.011696474,0.0006834937,0.0004890645,0.00085598376,0.00032292245,0.0003803767,0.0044647497,0.003438436,0.0017937991],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000731303,0.00065230974,0.026504757,0.00002599477,0.000031988508,0.0002400863,0.000540758,0.06967195,0.000025842472,0.0003499018,0.0028760103,0.8983491],"study_design_scores_gemma":[0.007373167,0.0040910146,0.11408457,0.0040229904,0.000063874,0.00007332272,0.018927215,0.04246007,0.00066420785,0.1525326,0.6486657,0.007041223],"about_ca_topic_score_codex":0.0016395552,"about_ca_topic_score_gemma":0.025412936,"teacher_disagreement_score":0.8913079,"about_ca_system_score_codex":0.002310391,"about_ca_system_score_gemma":0.0018067213,"threshold_uncertainty_score":0.99962705},"labels":[],"label_agreement":null},{"id":"W2939624893","doi":"10.3758/s13421-019-00927-3","title":"The development of fast and slow inferential responding: Evidence for a parallel development of rule-based and belief-based intuitions","year":2019,"lang":"en","type":"article","venue":"Memory & Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Psychology; Cognitive psychology; Cognition; Dual process theory (moral psychology); False belief; Dual (grammatical number); Affect (linguistics); Developmental psychology; Theory of mind; Communication; Neuroscience","score_opus":0.2050320571790161,"score_gpt":0.40853867670353927,"score_spread":0.20350661952452317,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2939624893","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95883423,0.00006374763,0.0401019,0.00014974494,0.00016164083,0.00049226626,0.000026421489,0.000011791104,0.00015827388],"genre_scores_gemma":[0.9652322,0.0000039551455,0.034484573,0.00004594328,0.000011464235,0.000071406794,0.00002107521,0.0000087766,0.00012064203],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99795806,0.000094464944,0.0009145682,0.00036431957,0.0004965224,0.00017206649],"domain_scores_gemma":[0.99585545,0.0029057262,0.00044869364,0.00025925264,0.00046210692,0.00006875313],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026195582,0.00014022403,0.00027581767,0.0003393823,0.00033342818,0.00013626575,0.00024001168,0.00007210494,0.00007080776],"category_scores_gemma":[0.0011178465,0.00009832098,0.000065359905,0.00025432793,0.00015173468,0.00020068642,0.00008912693,0.000073668074,0.000024725507],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00092282763,0.00013835626,0.0027635838,0.000048051228,0.000018333987,4.0661172e-7,0.0011445311,0.00013907623,0.013637235,0.00010951523,0.000095981224,0.9809821],"study_design_scores_gemma":[0.017786544,0.0019862014,0.41647038,0.005441807,0.0004415053,0.000015656678,0.012379779,0.030112248,0.4072462,0.08521518,0.020625116,0.0022793934],"about_ca_topic_score_codex":0.0000017400195,"about_ca_topic_score_gemma":0.000061339764,"teacher_disagreement_score":0.9787027,"about_ca_system_score_codex":0.000040607392,"about_ca_system_score_gemma":0.0005067326,"threshold_uncertainty_score":0.40094134},"labels":[],"label_agreement":null},{"id":"W2943275446","doi":"","title":"\"Never tell me the odds\" do people emphasize value or probability when choosing between alternatives?","year":2018,"lang":"en","type":"article","venue":"Journal of Exercise, Movement, and Sport (SCAPPS refereed abstracts repository)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University; University of Toronto","funders":"","keywords":"Preference; Psychology; Odds; Task (project management); Outcome (game theory); Statistics; Value (mathematics); Social psychology; Cognitive psychology; Mathematics; Economics; Mathematical economics","score_opus":0.06454443448268607,"score_gpt":0.33651497540864067,"score_spread":0.27197054092595463,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2943275446","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9923425,0.00025704858,0.0002594693,0.00045436303,0.0014754663,0.00048492829,0.000012528549,0.00002432882,0.0046893843],"genre_scores_gemma":[0.99366486,0.00020927051,0.0016002826,0.00018172881,0.0011115279,0.000006429647,0.0000017334559,0.00003560306,0.0031885388],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9935048,0.00012394555,0.003090329,0.0007761075,0.001978289,0.0005264806],"domain_scores_gemma":[0.9932366,0.00074461167,0.0032374358,0.0010694454,0.0012374532,0.0004744759],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0054070177,0.00044629697,0.001163118,0.00036629857,0.00068787043,0.0013123449,0.0015255299,0.00023258934,0.00026175805],"category_scores_gemma":[0.0005803288,0.00024181286,0.00039155592,0.00041361855,0.0003656666,0.0015955513,0.00029306868,0.0006124714,0.00004195649],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0027519853,0.0013654956,0.6296158,0.00006943626,0.00038081082,0.00043356724,0.0068143746,0.0003120803,0.00368948,0.0004438831,0.01621024,0.33791286],"study_design_scores_gemma":[0.0014837487,0.0007855778,0.9182712,0.00049587357,0.00029980417,0.0001733605,0.0017935139,0.000087721164,0.0055878004,0.04615104,0.024316331,0.00055406144],"about_ca_topic_score_codex":0.00020749075,"about_ca_topic_score_gemma":0.000065476896,"teacher_disagreement_score":0.3373588,"about_ca_system_score_codex":0.0002019205,"about_ca_system_score_gemma":0.00034803772,"threshold_uncertainty_score":0.9997244},"labels":[],"label_agreement":null},{"id":"W2945104486","doi":"10.1257/aeri.20190051","title":"The Relation between Behavior under Risk and over Time","year":2020,"lang":"en","type":"article","venue":"American Economic Review Insights","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"National Science Foundation","keywords":"Economics; Relation (database); Consumption (sociology); Certainty; Mathematical economics; Decision maker; Econometrics; Expected utility hypothesis; Microeconomics; Subjective expected utility; Mathematics; Computer science","score_opus":0.09454115975625091,"score_gpt":0.37655474229856084,"score_spread":0.2820135825423099,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2945104486","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9889442,0.0067010056,0.00013762231,0.002216944,0.00013063192,0.00036560206,0.000030077119,0.000035775825,0.0014381695],"genre_scores_gemma":[0.9831466,0.014288747,0.00021630038,0.0019606967,0.000176438,0.000023507213,0.000006771521,0.000022392273,0.00015852542],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9975868,0.00030221435,0.0010598401,0.00062426465,0.00022565512,0.00020122502],"domain_scores_gemma":[0.9962282,0.0018599586,0.0009990698,0.00064510567,0.000041071475,0.0002265506],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0010679093,0.00019809128,0.0006638311,0.00005756048,0.0003236286,0.00035432802,0.00061646017,0.000043223918,0.0003226804],"category_scores_gemma":[0.00051052845,0.00012061068,0.00017932188,0.00025732376,0.00037557515,0.0003720532,0.0001853765,0.00020979879,0.0037349206],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000061002124,0.000006583387,0.03009466,0.0000027593028,0.000013680716,0.000001851691,0.00007167681,0.00001844473,0.000007457124,0.00033355018,0.0068035796,0.96263963],"study_design_scores_gemma":[0.00021662697,0.00017605998,0.35240555,0.000081625854,0.00019507583,0.00000787,0.000087419765,0.00095664203,0.000008508299,0.012487295,0.6330158,0.0003615023],"about_ca_topic_score_codex":0.000068862864,"about_ca_topic_score_gemma":0.000015936725,"teacher_disagreement_score":0.9622781,"about_ca_system_score_codex":0.00007891954,"about_ca_system_score_gemma":0.000065359585,"threshold_uncertainty_score":0.9970408},"labels":[],"label_agreement":null},{"id":"W2945826097","doi":"10.1093/jeea/jvad062","title":"Hard-to-Interpret Signals","year":2023,"lang":"en","type":"preprint","venue":"Journal of the European Economic Association","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; McGill University","funders":"","keywords":"Interpretation (philosophy); Observable; Epistemology; Computer science; Data science; Physics; Philosophy","score_opus":0.16321926697632816,"score_gpt":0.38430541070633034,"score_spread":0.22108614373000218,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2945826097","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9636034,0.000039597697,0.0009367293,0.0071288343,0.02008918,0.0002189542,0.00017149764,0.000035157984,0.007776697],"genre_scores_gemma":[0.9814615,0.00004460878,0.00053645315,0.00061435066,0.0021864907,0.0000016653455,0.0000025529484,0.00007932423,0.015073025],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.9939325,0.0016464444,0.0027432535,0.0005077167,0.0008746722,0.0002954399],"domain_scores_gemma":[0.9908127,0.002147376,0.0053563244,0.001019081,0.00048387435,0.0001806264],"candidate_categories":["metaresearch","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.025119469,0.0002711934,0.0008265297,0.0005511469,0.00015864434,0.0012790927,0.0037255497,0.00018163885,0.00020291467],"category_scores_gemma":[0.010648164,0.00018580312,0.0011219148,0.00017531353,0.000025339581,0.0002824316,0.0021140685,0.0009872088,0.008334092],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004981364,0.00005374526,0.027896035,0.0000033497813,0.00023984424,0.000023842049,0.0012765999,0.09734218,0.00023044825,0.000019906302,0.71162903,0.16123521],"study_design_scores_gemma":[0.0011947703,0.00026757593,0.5366011,0.0010209227,0.0004839163,0.00006385267,0.0009487394,0.0042471145,0.00044181602,0.29091185,0.16255742,0.001260906],"about_ca_topic_score_codex":0.000015624197,"about_ca_topic_score_gemma":0.000025568334,"teacher_disagreement_score":0.5490716,"about_ca_system_score_codex":0.0018609582,"about_ca_system_score_gemma":0.00032774152,"threshold_uncertainty_score":0.99975765},"labels":[],"label_agreement":null},{"id":"W2946737764","doi":"10.31820/pt.28.1.3","title":"Fluency and Feeling of Rightness","year":2019,"lang":"en","type":"article","venue":"Psihologijske teme","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Fluency; Psychology; Feeling; Processing fluency; Cognitive psychology; Value (mathematics); Social psychology; Mathematics education; Statistics; Mathematics","score_opus":0.12121488560684562,"score_gpt":0.40803474124502936,"score_spread":0.28681985563818374,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2946737764","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99258757,0.00014716476,0.00014885192,0.00016209122,0.0006562515,0.000120769684,0.00001064137,0.00003470023,0.006131958],"genre_scores_gemma":[0.99766487,0.00001290028,0.0012477555,0.000092659124,0.000027461072,0.000002439787,9.567725e-7,0.000008026089,0.0009429617],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.998201,0.000072851806,0.00065003306,0.00047024948,0.00040823146,0.00019762],"domain_scores_gemma":[0.99801546,0.00082261825,0.00028024724,0.0006441502,0.00016759698,0.000069907495],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0018265792,0.00011916699,0.00037608962,0.0002055042,0.000057823352,0.000093460505,0.00058273657,0.00010578575,0.0008798154],"category_scores_gemma":[0.0006629838,0.00008024738,0.00008457451,0.00029272152,0.00011400667,0.0002377202,0.00020971148,0.00011269667,0.0010640111],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000050556875,0.00011665074,0.46300954,0.000009248601,0.000009774219,0.000013253588,0.0005780223,0.00011974076,0.007949778,0.0017465783,0.0015694865,0.52482736],"study_design_scores_gemma":[0.0017552447,0.0006586002,0.4560771,0.000117167525,0.00004567251,0.0000961902,0.0020618897,0.0025743225,0.0057876008,0.49503177,0.034928575,0.00086585426],"about_ca_topic_score_codex":0.000027237125,"about_ca_topic_score_gemma":0.00000743147,"teacher_disagreement_score":0.52396154,"about_ca_system_score_codex":0.000014317013,"about_ca_system_score_gemma":0.000026677135,"threshold_uncertainty_score":0.9997138},"labels":[],"label_agreement":null},{"id":"W2947042294","doi":"10.1007/s10899-019-09860-1","title":"Graphical Depiction of Statistical Information Improves Gambling-Related Judgments","year":2019,"lang":"en","type":"article","venue":"Journal of Gambling Studies","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Depiction; Psychology; Statistical analysis; Graphical display; Social psychology; Cognitive psychology; Statistics; Linguistics; Computer science; Mathematics; Philosophy","score_opus":0.12095167507780985,"score_gpt":0.4391230338796383,"score_spread":0.31817135880182845,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2947042294","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99340254,0.00030154482,0.0033622975,0.00025368165,0.0022960538,0.00009653034,0.000009728861,0.000009927102,0.0002676734],"genre_scores_gemma":[0.996784,0.0002301097,0.0027949999,0.00006447677,0.00005715368,7.9074596e-7,0.0000011701787,0.000006376509,0.000060946015],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9961482,0.000100640595,0.00222479,0.00015626983,0.001184185,0.00018591016],"domain_scores_gemma":[0.9947822,0.0015300486,0.0018312754,0.00023915307,0.0015349691,0.00008236629],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00373147,0.00014119988,0.00065918633,0.00080996385,0.00009411167,0.00014422105,0.0003721528,0.000089934656,0.000052657204],"category_scores_gemma":[0.0046394477,0.00009421327,0.00022196853,0.0005413811,0.00012180307,0.0011445242,0.00011955867,0.00030615853,0.000115699906],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005541418,0.0002932216,0.079158135,0.000046847905,0.00043981045,0.000013597169,0.0028783018,0.0023759569,0.003263459,0.001756938,0.00547724,0.9037424],"study_design_scores_gemma":[0.008011549,0.00567816,0.4653183,0.0012060751,0.00062807306,0.00040094674,0.022083001,0.01264478,0.0028643792,0.4648803,0.015197977,0.0010864841],"about_ca_topic_score_codex":0.0000047269255,"about_ca_topic_score_gemma":0.0000030993026,"teacher_disagreement_score":0.90265584,"about_ca_system_score_codex":0.00006661604,"about_ca_system_score_gemma":0.00007808835,"threshold_uncertainty_score":0.5554187},"labels":[],"label_agreement":null},{"id":"W2947323737","doi":"10.48550/arxiv.1906.00296","title":"The Theory of Weak Revealed Preference","year":2019,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Axiom; Rationalization (economics); Minimax; Revealed preference; Pairwise comparison; Mathematical economics; Preference; Rationalizability; Economics; Expected utility hypothesis; Consumer choice; Mathematics; Microeconomics; Econometrics; Statistics; Nash equilibrium","score_opus":0.35167729410807846,"score_gpt":0.2817032317417254,"score_spread":0.06997406236635306,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2947323737","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.963084,0.000113385075,0.011169073,0.00006561909,0.0014426559,0.00032216692,0.000065748,0.000039465624,0.02369793],"genre_scores_gemma":[0.97439975,0.00023748954,0.00008594955,0.00002811396,0.000041526902,5.6689305e-7,0.0000039048764,0.000015945123,0.02518675],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9971144,0.00052999344,0.0006614243,0.001095028,0.00030041666,0.00029874372],"domain_scores_gemma":[0.9917318,0.0038240848,0.0010427643,0.0027748554,0.00051202445,0.00011444307],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0037246128,0.0002741401,0.00057162,0.0002702386,0.00020931526,0.00022356234,0.0038184791,0.0003336925,0.00030316407],"category_scores_gemma":[0.0013442879,0.00019167768,0.00042641268,0.0005196998,0.00037807372,0.00019323212,0.0021775393,0.0005997318,0.0009358641],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012342472,0.0003558708,0.06650797,0.000053856682,0.00023222563,0.0001261498,0.00063378277,0.19484968,0.00009239548,0.42499915,0.014243138,0.2966715],"study_design_scores_gemma":[0.00029315348,0.000061037594,0.009479271,0.00010519715,0.0000795503,0.0000020992704,0.000993407,0.010543594,0.000041475912,0.9694186,0.008673265,0.0003093369],"about_ca_topic_score_codex":0.000039767172,"about_ca_topic_score_gemma":0.00005517429,"teacher_disagreement_score":0.54441947,"about_ca_system_score_codex":0.00011122137,"about_ca_system_score_gemma":0.00032220932,"threshold_uncertainty_score":0.99984205},"labels":[],"label_agreement":null},{"id":"W2947373391","doi":"10.1007/978-3-030-17925-0_6","title":"What We Can Learn","year":2019,"lang":"en","type":"book-chapter","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Psychology; Computer science","score_opus":0.21529474010764693,"score_gpt":0.39066499576838437,"score_spread":0.17537025566073744,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2947373391","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010493129,0.000627855,0.00007635641,0.0036742564,0.0063731624,0.00021878227,0.000038450737,0.000076960314,0.98786485],"genre_scores_gemma":[0.0040184427,0.00096720346,0.00025326622,0.0008690814,0.00022465907,0.0000012963268,0.000010892189,0.000058669757,0.9935965],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9963968,0.000026129694,0.0009844021,0.0010552919,0.0012509382,0.000286471],"domain_scores_gemma":[0.99623173,0.0010725833,0.0005108194,0.0017190436,0.00028461896,0.00018122855],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0013254035,0.00038886289,0.0008253506,0.0005012278,0.00009534033,0.0018109931,0.0014798813,0.0005365974,0.030011347],"category_scores_gemma":[0.00020830122,0.00027012624,0.00047954798,0.000058842194,0.00011428403,0.00052415987,0.0004327177,0.00047649437,0.059850007],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007827808,0.000007289306,0.00001573164,0.0000012962252,0.000009241866,0.00001864484,0.00006025864,0.000016163856,0.0000016357524,0.030313512,0.1131941,0.8563543],"study_design_scores_gemma":[0.000076259115,0.000042803156,0.000006424552,0.00008972307,0.000013833239,0.000010905865,0.00015969368,0.00003548581,0.0000043344053,0.3299445,0.66934955,0.00026653646],"about_ca_topic_score_codex":0.000024543882,"about_ca_topic_score_gemma":0.0004063787,"teacher_disagreement_score":0.85608774,"about_ca_system_score_codex":0.000106231426,"about_ca_system_score_gemma":0.00027883443,"threshold_uncertainty_score":0.9999751},"labels":[],"label_agreement":null},{"id":"W2948011249","doi":"10.1002/icd.2133","title":"The effect of psychological distance on young children's future predictions","year":2019,"lang":"en","type":"article","venue":"Infant and Child Development","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brock University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Psychology; Distancing; Preference; Task (project management); Futures studies; Social psychology; Developmental psychology; Psychological research; Cognitive psychology; Coronavirus disease 2019 (COVID-19)","score_opus":0.0174920268372856,"score_gpt":0.3246487558126567,"score_spread":0.30715672897537105,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2948011249","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9916802,0.00017781793,0.00006487866,0.0002985778,0.0010605442,0.00025814242,0.000012820344,0.000019717218,0.00642728],"genre_scores_gemma":[0.99934703,0.00006142414,0.00013344496,0.00006916355,0.00007774363,0.000011655882,0.0000040606747,0.0000054015836,0.0002900887],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99836606,0.00006847007,0.000494858,0.00038329567,0.00051485334,0.00017247013],"domain_scores_gemma":[0.9987459,0.00051746913,0.00018407674,0.0004422586,0.00004490837,0.00006535674],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011782269,0.00014070023,0.00024091273,0.00007465802,0.0003202789,0.00014544798,0.000428573,0.00007823346,0.00007608168],"category_scores_gemma":[0.00013422506,0.000066924105,0.00007419251,0.00019263937,0.00008208839,0.00007422196,0.000099028235,0.0001758116,0.00016944976],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016679209,0.000039871033,0.6138239,0.0000015297518,0.000016056349,0.0000012369861,0.00024231529,0.000032284934,0.0000049082323,0.00063678314,0.0017664116,0.38326788],"study_design_scores_gemma":[0.00042950502,0.00028873453,0.95174307,0.000048059766,0.0000047669832,0.000027144344,0.00006561924,0.000028559125,0.00019839908,0.00085107837,0.04619794,0.00011710182],"about_ca_topic_score_codex":0.0000019085742,"about_ca_topic_score_gemma":0.000014036771,"teacher_disagreement_score":0.3831508,"about_ca_system_score_codex":0.000019874362,"about_ca_system_score_gemma":0.000014696982,"threshold_uncertainty_score":0.27290857},"labels":[],"label_agreement":null},{"id":"W2948022226","doi":"10.1142/s1084946719500055","title":"GENDER DIFFERENCES IN ATTITUDES TOWARD RISK: EVIDENCE FROM ENTREPRENUERS IN GHANA AND UGANDA","year":2019,"lang":"en","type":"article","venue":"Journal of Developmental Entrepreneurship","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Assertion; Risk aversion (psychology); Perception; Gender gap; Demographic economics; Psychology; Risk perception; Social psychology; Economics; Financial economics","score_opus":0.1759959697721275,"score_gpt":0.3570825888944674,"score_spread":0.18108661912233992,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2948022226","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9979774,0.000809497,0.000026996378,0.00019009753,0.000707688,0.00012402302,0.0000102148215,0.000005854531,0.00014826062],"genre_scores_gemma":[0.9974353,0.00029699487,0.0020870336,0.000051502695,0.00004137105,0.0000017151805,7.8515035e-7,0.00001014739,0.0000751646],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9964036,0.0003209571,0.0014297756,0.00056181586,0.0009814948,0.00030238248],"domain_scores_gemma":[0.99599224,0.002643933,0.000819617,0.00026065865,0.000106971,0.00017655436],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023855818,0.00022085964,0.0006409749,0.0006399346,0.000039399016,0.00032048312,0.0008122246,0.000112321795,0.0007661693],"category_scores_gemma":[0.0021996272,0.00016462864,0.000120488694,0.00045148123,0.0000785647,0.00083653344,0.00025639092,0.0004295313,0.00016512345],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001569556,0.00008642173,0.91103643,0.0000031299317,0.00001444934,0.00007955898,0.0033679404,0.00005592189,0.00030913707,0.0000025461839,0.00006267216,0.08482485],"study_design_scores_gemma":[0.000841032,0.00006696022,0.98861295,0.00032459656,0.00001169676,0.000049622053,0.0029851787,0.000055177847,0.0007026247,0.0061100265,0.00004381668,0.00019634397],"about_ca_topic_score_codex":0.0001713593,"about_ca_topic_score_gemma":0.00032787689,"teacher_disagreement_score":0.084628515,"about_ca_system_score_codex":0.00020701339,"about_ca_system_score_gemma":0.00023692561,"threshold_uncertainty_score":0.83890164},"labels":[],"label_agreement":null},{"id":"W2950557080","doi":"10.3389/fpsyg.2019.01506","title":"Editorial: Judgment and Decision Making Under Uncertainty: Descriptive, Normative, and Prescriptive Perspectives","year":2019,"lang":"en","type":"editorial","venue":"Frontiers in Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University; Defence Research and Development Canada","funders":"Comisión Nacional de Investigación Científica y Tecnológica; Ministère de la Défense Nationale","keywords":"Normative; Psychology; Social psychology; Cognitive psychology; Epistemology","score_opus":0.04472268416277513,"score_gpt":0.3877273280745118,"score_spread":0.3430046439117367,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2950557080","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015656924,0.0042777862,0.017893968,0.00017451475,0.9595872,0.0006412682,0.0002570993,0.000043681765,0.0014675162],"genre_scores_gemma":[0.008429326,0.0038488673,0.032098386,0.00027280662,0.95461553,0.000087148874,0.00004446203,0.00013757792,0.0004659161],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9928987,0.0005652264,0.0015343901,0.0025081753,0.0017695668,0.00072392914],"domain_scores_gemma":[0.9923258,0.0044960994,0.0009779339,0.0012483478,0.0007560633,0.00019579926],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0036960095,0.00072790356,0.0016859651,0.0017177432,0.00021554736,0.0006954483,0.001357503,0.0019635516,0.00009330709],"category_scores_gemma":[0.004772744,0.0006135609,0.00019120544,0.0006215995,0.0007923828,0.00069212465,0.00070519827,0.0018242265,0.00009027398],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008729998,0.000098400014,0.00079649506,0.00000831068,0.000038274673,0.000010294686,0.0020377787,0.00007655153,0.0000020775346,0.000036997208,0.7727534,0.22326839],"study_design_scores_gemma":[0.0020482563,0.000354317,0.0005905188,0.0002834751,0.00004942722,0.0000066942725,0.011220522,0.00038428436,2.1405138e-7,0.25374562,0.73074645,0.0005702541],"about_ca_topic_score_codex":0.0000628116,"about_ca_topic_score_gemma":0.00010156511,"teacher_disagreement_score":0.2537086,"about_ca_system_score_codex":0.0006349556,"about_ca_system_score_gemma":0.0002942174,"threshold_uncertainty_score":0.9996316},"labels":[],"label_agreement":null},{"id":"W2951077818","doi":"","title":"\"Money, less problems\": Wealth level affects the selection of optimal endpoint in an aiming task with positive and negative outcomes","year":2012,"lang":"en","type":"article","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto; Dalhousie University","funders":"","keywords":"Lottery; Task (project management); Point (geometry); Psychology; Economics; Actuarial science; Microeconomics; Mathematics","score_opus":0.15803512754323856,"score_gpt":0.3912383683658394,"score_spread":0.23320324082260085,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951077818","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99456406,0.000020144193,0.0040975986,0.00034959463,0.00008866624,0.00033452603,0.00001691304,0.000014771921,0.00051369966],"genre_scores_gemma":[0.99391145,0.0000032074065,0.0057983184,0.00010534432,0.000020092457,0.000012963728,0.000001189776,0.00001031129,0.00013711622],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983022,0.00025060898,0.0004127823,0.0003286292,0.00042083338,0.00028494533],"domain_scores_gemma":[0.99771905,0.0014829537,0.00029474503,0.00024068712,0.00015030403,0.00011224272],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020477343,0.00015495121,0.00034668244,0.0002208103,0.00015183011,0.00014816705,0.00025162735,0.00006351918,0.000038964317],"category_scores_gemma":[0.0002699105,0.00007783455,0.00004127176,0.00040170795,0.00013756398,0.0008990556,0.00010215284,0.00017538159,0.0000077269915],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016305193,0.00028311592,0.7555772,0.0000041388503,0.0000150508695,0.000001730816,0.009602394,0.0013578474,0.00072663487,0.00085509394,0.00007382788,0.2313399],"study_design_scores_gemma":[0.00047791708,0.00041613655,0.98307073,0.00003468945,0.000015239174,0.000018441233,0.00905738,0.002979211,0.0022622817,0.0014755061,0.000032117736,0.00016033369],"about_ca_topic_score_codex":0.0007057936,"about_ca_topic_score_gemma":0.003300602,"teacher_disagreement_score":0.23117957,"about_ca_system_score_codex":0.00007106521,"about_ca_system_score_gemma":0.00006668222,"threshold_uncertainty_score":0.3174001},"labels":[],"label_agreement":null},{"id":"W2952571822","doi":"","title":"A Measure of Decision Flexibility","year":2013,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Flexibility (engineering); Measure (data warehouse); Decision maker; Variety (cybernetics); Perspective (graphical); Computer science; Value (mathematics); Decision model; Economics; Artificial intelligence; Management science; Machine learning; Data mining","score_opus":0.3615174583195565,"score_gpt":0.30306867819917177,"score_spread":0.058448780120384736,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2952571822","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96278554,0.00005244815,0.03088695,0.00003903609,0.0012440431,0.0003791883,0.000093181225,0.000073802796,0.004445792],"genre_scores_gemma":[0.9972855,0.000042819687,0.0012976975,0.00003734849,0.000060265604,8.6360853e-7,0.0000073327838,0.000023500574,0.0012447044],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99581337,0.00031513808,0.0010642711,0.0018919316,0.0005564529,0.00035886304],"domain_scores_gemma":[0.99238515,0.0016901848,0.001110822,0.0032653671,0.0012627518,0.00028570375],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002993252,0.00040578115,0.0009812929,0.00067701505,0.00013955496,0.00024236646,0.0031300397,0.00064485,0.0014918528],"category_scores_gemma":[0.0023670837,0.00035817188,0.000739211,0.00092643226,0.00033539836,0.00041731444,0.0024782761,0.0006968745,0.0014726017],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00070499006,0.00087420456,0.057725407,0.00004761405,0.00013430764,0.00028052917,0.0004495621,0.29396364,0.00017545032,0.014182694,0.01164242,0.61981916],"study_design_scores_gemma":[0.0004951086,0.000079658625,0.00988639,0.00016985771,0.00009208366,0.0000049640726,0.00030495983,0.05127057,0.00012961414,0.9352386,0.0018450203,0.0004831499],"about_ca_topic_score_codex":0.000405968,"about_ca_topic_score_gemma":0.00012759036,"teacher_disagreement_score":0.9210559,"about_ca_system_score_codex":0.00024584073,"about_ca_system_score_gemma":0.00035151944,"threshold_uncertainty_score":0.99988705},"labels":[],"label_agreement":null},{"id":"W2952746491","doi":"10.1101/351312","title":"Time preferences are reliable across time-horizons and verbal vs. experiential tasks","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Science and Technology Commission of Shanghai Municipality; National Natural Science Foundation of China; Program of Shanghai Academic Research Leader; New York University Shanghai; National Science Foundation","keywords":"Experiential learning; Context (archaeology); Delay discounting; Discounting; Psychology; Time preference; Preference; Cognitive psychology; Time horizon; Task (project management); Social psychology; Developmental psychology; Impulsivity","score_opus":0.045930191324052884,"score_gpt":0.3127030774616472,"score_spread":0.2667728861375943,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2952746491","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99384755,0.0004234845,0.00017278374,0.00015930558,0.003320222,0.0005307339,0.0011197267,0.00035709914,0.00006907996],"genre_scores_gemma":[0.99593055,0.00008031532,0.002538136,0.00013866584,0.00089817593,0.0001102548,8.4275274e-7,0.000118037904,0.00018504508],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99324495,0.0002455111,0.0014848966,0.0026460637,0.0013857784,0.0009927951],"domain_scores_gemma":[0.9935297,0.000435945,0.0013485544,0.0028623547,0.0012279707,0.000595524],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0030850207,0.0008445287,0.0013498288,0.00038654206,0.00069275114,0.002692525,0.0023323437,0.0010477991,0.0013137923],"category_scores_gemma":[0.0014758506,0.00075643323,0.00030366733,0.00074344553,0.00087695726,0.0006269984,0.0027832915,0.00085960655,0.004303682],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003054896,0.003995554,0.11933321,0.00055882416,0.0013566836,0.0011482135,0.0027468596,0.0008880819,0.35001743,0.00037328032,0.5125357,0.0039912816],"study_design_scores_gemma":[0.00540548,0.0021611068,0.24429786,0.0038359195,0.0008315519,0.0000010330423,0.0005708647,0.014925673,0.1841058,0.0018338455,0.5299281,0.01210276],"about_ca_topic_score_codex":0.00007230629,"about_ca_topic_score_gemma":0.000008519973,"teacher_disagreement_score":0.16591164,"about_ca_system_score_codex":0.00022535841,"about_ca_system_score_gemma":0.0005602931,"threshold_uncertainty_score":0.99959916},"labels":[],"label_agreement":null},{"id":"W2952887472","doi":"10.2139/ssrn.3590216","title":"Are ISS Recommendations Informative? Evidence from Assessments of Compensation Practices","year":2020,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Quest University Canada","funders":"","keywords":"Compensation (psychology); Psychology; Actuarial science; Business; Social psychology","score_opus":0.33843875767732523,"score_gpt":0.49040597641332845,"score_spread":0.15196721873600322,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2952887472","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9612029,0.0003371112,0.02746827,0.0102296015,0.00029834596,0.00009462912,0.000022642249,0.000014887098,0.00033159956],"genre_scores_gemma":[0.9968211,0.0007440089,0.0018492603,0.00037104078,0.00012345369,0.0000018669886,0.000004641923,0.000007604383,0.00007701206],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.997095,0.00029012596,0.0010230924,0.00024612877,0.00077298813,0.0005726625],"domain_scores_gemma":[0.9929209,0.0018581111,0.0043724924,0.0002530414,0.0004787914,0.00011667],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0043097734,0.00012214143,0.00030576746,0.00014984822,0.00020441336,0.0003635238,0.0008670406,0.00006247895,0.00042655444],"category_scores_gemma":[0.0066931485,0.00009509401,0.0001229791,0.00044732096,0.000043096454,0.0024673108,0.0001179535,0.0010216156,0.00026808167],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022203157,0.000113459675,0.06545658,0.0000025039194,0.00009884204,0.000003171459,0.0016523056,0.0007146114,0.00052030117,0.0015974033,0.0035415888,0.9260772],"study_design_scores_gemma":[0.001135786,0.0009647156,0.035291847,0.00026463662,0.00012721414,0.00008427687,0.05692144,0.016517097,0.00054554973,0.8672539,0.020439934,0.00045360829],"about_ca_topic_score_codex":0.00007872149,"about_ca_topic_score_gemma":0.00033179892,"teacher_disagreement_score":0.9256236,"about_ca_system_score_codex":0.000305367,"about_ca_system_score_gemma":0.0010004729,"threshold_uncertainty_score":0.80128074},"labels":[],"label_agreement":null},{"id":"W2953323811","doi":"10.1017/cbo9780511808098.026","title":"Individual Differences in Reasoning: Implications for the Rationality Debate?","year":2002,"lang":"en","type":"book-chapter","venue":"Cambridge University Press eBooks","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":163,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Normative; Irrationality; Psychology; Rationality; Epistemology; Cognition; Cognitive science; Cognitive psychology; Philosophy","score_opus":0.2320080355411214,"score_gpt":0.3271246426150358,"score_spread":0.09511660707391442,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2953323811","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010015986,0.00017047396,0.0026894591,0.0004622823,0.00043866312,0.0009579494,0.002022411,0.000058949885,0.9831838],"genre_scores_gemma":[0.07956409,0.00006128589,0.0002442183,0.00009574198,0.00010604236,0.000007332374,0.00004540965,0.000022199265,0.9198537],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9978809,0.00007190711,0.00054344843,0.00075357204,0.00049254135,0.00025764998],"domain_scores_gemma":[0.99520636,0.0028035184,0.00053086487,0.0009867079,0.00035771294,0.00011485415],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009686205,0.00029108644,0.00047504218,0.0002999924,0.0004832735,0.00035756748,0.0019324028,0.00032112017,0.000030280398],"category_scores_gemma":[0.00035580815,0.00022661749,0.00030847,0.00003292005,0.00032969948,0.00015835308,0.00044136852,0.0003711633,0.000030454945],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000043675635,0.000022731176,0.0005905612,0.0000032135492,0.000043644053,0.000009185486,0.000087302156,0.000012716018,0.0000013784871,0.87901956,0.051786713,0.0683793],"study_design_scores_gemma":[0.0004982889,0.00004224866,0.012118062,0.0000619908,0.00015237408,0.000011339243,0.00010324646,0.00047105952,0.00000592944,0.0060266205,0.98010874,0.00040010532],"about_ca_topic_score_codex":0.00008589093,"about_ca_topic_score_gemma":0.000035022316,"teacher_disagreement_score":0.928322,"about_ca_system_score_codex":0.0001580614,"about_ca_system_score_gemma":0.00013386017,"threshold_uncertainty_score":0.9241193},"labels":[],"label_agreement":null},{"id":"W2954673385","doi":"10.1007/s00780-019-00399-y","title":"Dual utilities on risk aggregation under dependence uncertainty","year":2019,"lang":"en","type":"article","venue":"Finance and Stochastics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Dual (grammatical number); Ambiguity; Mathematical economics; Preference; Expected utility hypothesis; Ambiguity aversion; Economics; Subjective expected utility; Econometrics; Mathematics; Decision maker; Marginal utility; Aggregate (composite); Expected shortfall; Upper and lower bounds; Mathematical optimization; Computer science; Risk management; Microeconomics; Operations research","score_opus":0.07117512660900761,"score_gpt":0.3458142422880111,"score_spread":0.2746391156790035,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2954673385","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9871322,0.00009878056,0.010361102,0.000121054836,0.00075065286,0.0001360397,0.000084297426,0.000022249484,0.001293617],"genre_scores_gemma":[0.9971825,0.00006855611,0.0005152623,0.00017531379,0.00006482197,0.00000474938,0.000003594594,0.000008405312,0.0019768022],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9983285,0.00004821759,0.0003939642,0.00047932766,0.00053152547,0.00021848017],"domain_scores_gemma":[0.9978294,0.0012385872,0.00024501435,0.00048235158,0.00015234457,0.00005230825],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008027779,0.00014721345,0.00025228696,0.00012167273,0.00017261619,0.0002032027,0.00024957818,0.00010459445,0.0001339376],"category_scores_gemma":[0.00078444113,0.00011199046,0.0000619115,0.00019516391,0.00010186918,0.00021400762,0.00008981301,0.00020005566,0.0008961693],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016641052,0.0000698463,0.010096053,0.0000030876774,0.000006295821,0.000008206305,0.0006050548,0.09610276,0.000020582544,0.019597605,0.0016565043,0.87166756],"study_design_scores_gemma":[0.00127014,0.0011297276,0.08887198,0.00019318149,0.000034794164,0.00003548204,0.003319018,0.16877928,0.00014310925,0.71142143,0.0240639,0.00073793327],"about_ca_topic_score_codex":0.00004491915,"about_ca_topic_score_gemma":0.000052815965,"teacher_disagreement_score":0.87092966,"about_ca_system_score_codex":0.00003731028,"about_ca_system_score_gemma":0.00006249635,"threshold_uncertainty_score":0.99988174},"labels":[],"label_agreement":null},{"id":"W2955032915","doi":"10.1016/j.jarmac.2019.05.002","title":"No Peak-End Rule for Simple Positive Experiences Observed in Children and Adults","year":2019,"lang":"en","type":"article","venue":"Journal of Applied Research in Memory and Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kwantlen Polytechnic University","funders":"Social Sciences and Humanities Research Council of Canada; Canada Research Chairs","keywords":"Psychology; Simple (philosophy); Developmental psychology; Cognitive psychology; Epistemology","score_opus":0.1297104871082893,"score_gpt":0.4168629940346397,"score_spread":0.2871525069263504,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2955032915","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9971477,0.000084394684,0.000018914121,0.00008679181,0.000081808146,0.00044093613,0.000017569337,0.0000019470135,0.0021199803],"genre_scores_gemma":[0.9993963,0.00007472246,0.00032339638,0.00005124418,0.0000777651,0.000022651033,0.000005877149,0.000006072706,0.00004192225],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9980321,0.00013954818,0.00060938176,0.00030075415,0.000674397,0.0002438327],"domain_scores_gemma":[0.9976381,0.0014914875,0.00021686211,0.00011699742,0.00042807477,0.000108501335],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006074949,0.00008845352,0.0002859793,0.0005570762,0.00010910988,0.00024051254,0.0002544084,0.00008558358,0.00011883235],"category_scores_gemma":[0.0004894879,0.000065646964,0.000045535475,0.00033555788,0.00014714588,0.0004079746,0.00009698281,0.00034831295,0.000026652586],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0045896363,0.000319792,0.0146621745,0.000017619208,0.0000141800065,0.00002314924,0.004582269,0.00007129154,0.004032007,0.00015713817,0.00033354686,0.9711972],"study_design_scores_gemma":[0.011303221,0.0023701966,0.4717099,0.0005773707,0.000019283814,0.0001602704,0.09312985,0.0021346516,0.008000408,0.409662,0.0004364397,0.00049640477],"about_ca_topic_score_codex":0.000019008763,"about_ca_topic_score_gemma":0.00002432687,"teacher_disagreement_score":0.9707008,"about_ca_system_score_codex":0.00003438189,"about_ca_system_score_gemma":0.00007673015,"threshold_uncertainty_score":0.26770055},"labels":[],"label_agreement":null},{"id":"W2955339725","doi":"10.1016/j.actpsy.2019.102863","title":"Understanding the cognitive miser: Cue-utilization in effort-based decision making","year":2019,"lang":"en","type":"article","venue":"Acta Psychologica","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Cognition; Task (project management); Control (management); Action selection; Psychology; Set (abstract data type); Cognitive psychology; Action (physics); Selection (genetic algorithm); Executive functions; Contrast (vision); Computer science; Artificial intelligence; Perception; Neuroscience; Economics","score_opus":0.44736802295896555,"score_gpt":0.47076053930528006,"score_spread":0.023392516346314507,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2955339725","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9616791,0.000042303338,0.021055011,0.0005659509,0.0009765717,0.00044382073,0.000010879946,0.000047522775,0.015178819],"genre_scores_gemma":[0.99757093,0.000012398369,0.00064220256,0.0016013215,0.000032968277,0.000012755747,0.000004846996,0.000015911644,0.00010663923],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9971175,0.0001936251,0.0007704822,0.000799647,0.0007637769,0.0003549596],"domain_scores_gemma":[0.9938419,0.004827198,0.00037825567,0.00077539985,0.0001170606,0.000060201535],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0031402328,0.00020552604,0.000329665,0.00039215197,0.00021043276,0.00041689383,0.0010043083,0.00019549552,0.0018141619],"category_scores_gemma":[0.0016845901,0.00012022634,0.00015278682,0.0010867476,0.0001183852,0.00031087952,0.00012741017,0.00029823417,0.0010774016],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008652744,0.00032980702,0.42488712,0.0000023465052,0.000009602398,0.00003347654,0.00048066446,0.001185283,0.00020778121,0.00081185554,0.0065756654,0.56461114],"study_design_scores_gemma":[0.0031567665,0.00055967004,0.61298776,0.0005195298,0.000030208443,0.000029451317,0.006929857,0.015299519,0.000077747725,0.34964913,0.010065615,0.00069475564],"about_ca_topic_score_codex":0.0000035841051,"about_ca_topic_score_gemma":0.00005040107,"teacher_disagreement_score":0.5639164,"about_ca_system_score_codex":0.00014510874,"about_ca_system_score_gemma":0.000043759916,"threshold_uncertainty_score":0.99970037},"labels":[],"label_agreement":null},{"id":"W2956977098","doi":"10.1007/s11409-019-09198-4","title":"Does domain matter? Monitoring accuracy across domains","year":2019,"lang":"en","type":"article","venue":"Metacognition and Learning","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":36,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Centre of Excellence for Child and Youth Mental Health; York University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Overconfidence effect; Task (project management); Calibration; Psychology; Generality; Resolution (logic); Cognitive psychology; Cognition; Domain (mathematical analysis); Artificial intelligence; Metacognition; Domain knowledge; Computer science; Machine learning; Developmental psychology; Statistics; Social psychology; Mathematics","score_opus":0.0662592283616116,"score_gpt":0.39904623244513565,"score_spread":0.332787004083524,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2956977098","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9938811,0.00005507518,0.0009808771,0.00035185722,0.0011241178,0.00013469959,0.000008817286,0.000065235705,0.0033982329],"genre_scores_gemma":[0.99343514,0.000023292978,0.0018960027,0.00020368116,0.00015980339,0.000008790822,0.000005039418,0.00001859508,0.0042496305],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99773026,0.00031663672,0.0005298614,0.00057104626,0.00052813214,0.0003240422],"domain_scores_gemma":[0.9975494,0.0015830249,0.00029346393,0.00030387143,0.00014400893,0.00012622878],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0029959884,0.00017207561,0.00032887983,0.00016516019,0.00047701807,0.0009927665,0.00028126035,0.00009657888,0.0022729726],"category_scores_gemma":[0.0009947084,0.000102316575,0.00012660882,0.00028780737,0.000063908665,0.0006951874,0.00018345812,0.00041397894,0.0054218993],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033250195,0.000031944288,0.33633867,0.0000051986985,0.000012667034,0.000009770895,0.0017884509,0.00010731234,0.0035087364,0.00003670126,0.00011473597,0.65801257],"study_design_scores_gemma":[0.0028259233,0.00021682515,0.51464957,0.00024302611,0.00006637416,0.00007883376,0.05393656,0.0008474316,0.0033884,0.10047861,0.3220964,0.0011720448],"about_ca_topic_score_codex":0.00001548213,"about_ca_topic_score_gemma":0.0000041384237,"teacher_disagreement_score":0.6568405,"about_ca_system_score_codex":0.000024865061,"about_ca_system_score_gemma":0.000013814008,"threshold_uncertainty_score":0.9986391},"labels":[],"label_agreement":null},{"id":"W2960780327","doi":"10.3758/s13428-019-01270-w","title":"The role of number of items per trial in best–worst scaling experiments","year":2019,"lang":"en","type":"article","venue":"Behavior Research Methods","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Scaling; Latent semantic analysis; Set (abstract data type); Computer science; Dimension (graph theory); Value (mathematics); Statistics; Cognitive psychology; Natural language processing; Artificial intelligence; Psychology; Machine learning; Mathematics","score_opus":0.5703808539984128,"score_gpt":0.6897069463044384,"score_spread":0.11932609230602564,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2960780327","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9922188,0.00032544165,0.00009036763,0.000033737313,0.00070735347,0.00088931224,0.000011273288,0.0000068127033,0.005716931],"genre_scores_gemma":[0.9785376,0.000024621702,0.019793171,0.0000030892265,0.000053191292,0.00011967657,0.0000010175719,0.000023042263,0.001444542],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9919124,0.0031674656,0.0015179958,0.0005957253,0.0022517096,0.0005546602],"domain_scores_gemma":[0.98901427,0.008456059,0.00035314725,0.0013625058,0.0006749153,0.00013907981],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.03751411,0.00015406874,0.00058677886,0.00049091125,0.00015970423,0.00022644667,0.0017416159,0.00017521753,0.0010447365],"category_scores_gemma":[0.0039971652,0.000098520504,0.00025697623,0.0010955716,0.00038354035,0.00025644386,0.00061150733,0.0005306545,0.00043795025],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019678383,0.00051742163,0.07867879,0.0000016787853,0.0000043709883,0.0000027743135,0.0007973807,0.000010987422,0.03218628,0.00039771316,0.000057289584,0.88537747],"study_design_scores_gemma":[0.0484401,0.003244326,0.07776773,0.00056231586,0.00010769662,0.000049764,0.106229365,0.0033589508,0.3913872,0.2590115,0.108180255,0.001660791],"about_ca_topic_score_codex":0.00045200664,"about_ca_topic_score_gemma":0.0000225137,"teacher_disagreement_score":0.8837167,"about_ca_system_score_codex":0.000099300145,"about_ca_system_score_gemma":0.00018240178,"threshold_uncertainty_score":0.99986845},"labels":[],"label_agreement":null},{"id":"W2963142712","doi":"10.1007/s11238-017-9612-1","title":"Confidence biases and learning among intuitive Bayesians","year":2017,"lang":"en","type":"preprint","venue":"Theory and Decision","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Center for Interuniversity Research and Analysis on Organizations","funders":"","keywords":"Contrarian; Overconfidence effect; Bayesian probability; Task (project management); Perception; Conservatism; Computer science; Phenomenon; Cognitive psychology; Artificial intelligence; Probabilistic logic; Psychology; Machine learning; Social psychology; Economics; Epistemology","score_opus":0.13014408484338472,"score_gpt":0.42261229900778424,"score_spread":0.2924682141643995,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2963142712","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9369624,0.0011812425,0.05693768,0.00006471758,0.0009853309,0.0002674832,0.000048407113,0.000068940804,0.0034837818],"genre_scores_gemma":[0.9960969,0.0007552928,0.0016831746,0.00009642928,0.00014725217,0.000014230688,0.000008549256,0.00003140164,0.0011667849],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99534273,0.0008835235,0.001008675,0.0015395646,0.00088077335,0.00034474002],"domain_scores_gemma":[0.97536486,0.021447742,0.0010354243,0.0014963577,0.0003494321,0.00030619002],"candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.014311063,0.00045438777,0.0009507346,0.0005170982,0.0011194985,0.0026674843,0.0013261206,0.0005366246,0.00038580815],"category_scores_gemma":[0.030709729,0.00033767632,0.00020089041,0.00011056843,0.001025872,0.0005764138,0.0030333665,0.0012705937,0.00018098869],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004055441,0.000029386883,0.0035393233,0.0000051983266,0.000013982624,0.00006923367,0.0010435696,0.0004017049,0.000019526238,0.010351078,0.00042158502,0.98369986],"study_design_scores_gemma":[0.000307399,0.000126997,0.017119521,0.00080324244,0.000050995375,0.000044031556,0.0014240888,0.0022213697,0.00006365145,0.9758726,0.001536419,0.00042970528],"about_ca_topic_score_codex":0.000083255065,"about_ca_topic_score_gemma":0.000057985108,"teacher_disagreement_score":0.98327017,"about_ca_system_score_codex":0.000038349226,"about_ca_system_score_gemma":0.00011292054,"threshold_uncertainty_score":0.99990755},"labels":[],"label_agreement":null},{"id":"W2964206029","doi":"10.1111/sode.12395","title":"The socializing role of logical consequences, mild punishments, and reasoning in rule‐breaking contexts involving multifaceted issues","year":2019,"lang":"en","type":"article","venue":"Social Development","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Psychology; Logical reasoning; Developmental psychology; Social psychology","score_opus":0.07846018603710746,"score_gpt":0.3804586030005637,"score_spread":0.30199841696345625,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2964206029","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99643743,0.0012476981,0.000010798059,0.0004848278,0.00031623433,0.00024552,0.0000040561504,0.000020751668,0.0012326572],"genre_scores_gemma":[0.99701834,0.00007308938,0.002462103,0.00009099978,0.00003330872,0.000012496972,0.0000026385924,0.000010530719,0.00029648296],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9973188,0.00023225007,0.0009486533,0.00043936164,0.0007033143,0.0003576368],"domain_scores_gemma":[0.99821454,0.0009173243,0.00044611958,0.00017739295,0.00018234702,0.00006228374],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033987064,0.00017146431,0.00044224167,0.00013259632,0.0005895666,0.00035469266,0.0005069317,0.00015027325,0.00007196207],"category_scores_gemma":[0.0009315743,0.00012153523,0.000071185816,0.00033017347,0.0002959705,0.00021508473,0.00033082374,0.00020371146,0.000063136846],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005371395,0.00005040182,0.19662763,0.000004857735,0.00002243484,0.000005185861,0.018168798,0.000009303604,0.0029336025,0.0048612566,0.00019015899,0.77707267],"study_design_scores_gemma":[0.0019181706,0.00007218221,0.68194824,0.0004891664,0.000018719102,0.000008245509,0.09110009,0.0006823553,0.005244695,0.1634098,0.054235328,0.00087302655],"about_ca_topic_score_codex":0.0002963959,"about_ca_topic_score_gemma":0.00039733114,"teacher_disagreement_score":0.77619964,"about_ca_system_score_codex":0.00018046655,"about_ca_system_score_gemma":0.00025692108,"threshold_uncertainty_score":0.4956063},"labels":[],"label_agreement":null},{"id":"W2964612905","doi":"10.1177/0956797619861429","title":"Debiasing Training Improves Decision Making in the Field","year":2019,"lang":"en","type":"article","venue":"Psychological Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":117,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Quest University Canada","funders":"Fondation HEC","keywords":"Debiasing; Psychology; Training (meteorology); Field (mathematics); Field training; Cognitive psychology; Applied psychology; Social psychology; Medical education","score_opus":0.22885715513107951,"score_gpt":0.5186872590913891,"score_spread":0.2898301039603096,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2964612905","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97115266,0.000024775527,0.0025034836,0.0014784049,0.001158591,0.00018765058,7.253398e-7,0.000025030635,0.023468656],"genre_scores_gemma":[0.9888019,0.0000032349578,0.0064950483,0.0046007787,0.00004751838,0.0000055839923,7.939755e-8,0.0000037694078,0.00004206514],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9963156,0.00012837347,0.00064282963,0.000991585,0.0014022905,0.00051932206],"domain_scores_gemma":[0.9916672,0.0070504164,0.00018596099,0.00092640036,0.00008921077,0.00008079221],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.011052369,0.00013744524,0.00024900568,0.00031369794,0.00028199982,0.0009949291,0.0032846588,0.00010121436,0.0006012897],"category_scores_gemma":[0.00914838,0.00006897946,0.0001057104,0.0022517033,0.00029983398,0.00061462773,0.00025827438,0.0003431535,0.0008449269],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030032776,0.00005389959,0.010296435,1.7256757e-7,1.9725663e-7,0.000010726764,0.000660747,0.000058563564,0.001489534,0.00057972525,0.0004547173,0.98636526],"study_design_scores_gemma":[0.00039764994,0.00049419457,0.52211744,0.0000852202,0.0000026716784,0.00008422659,0.003645079,0.0042828624,0.000074850235,0.4597093,0.008778515,0.00032800378],"about_ca_topic_score_codex":0.000007649576,"about_ca_topic_score_gemma":0.00001740765,"teacher_disagreement_score":0.98603725,"about_ca_system_score_codex":0.00004519956,"about_ca_system_score_gemma":0.000039376177,"threshold_uncertainty_score":0.999933},"labels":[],"label_agreement":null},{"id":"W2965931042","doi":"10.1177/0963721419855658","title":"Logic, Fast and Slow: Advances in Dual-Process Theorizing","year":2019,"lang":"en","type":"article","venue":"Current Directions in Psychological Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":247,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"Agence Nationale de la Recherche","keywords":"Sketch; Dual (grammatical number); Process (computing); Inference; Dual process theory (moral psychology); Cognitive science; Deliberation; Logical reasoning; Psychology; Task (project management); Key (lock); Thinking processes; Epistemology; Computer science; Cognitive psychology; Artificial intelligence; Social psychology; Moral reasoning; Algorithm","score_opus":0.12607698837945877,"score_gpt":0.5129724884774227,"score_spread":0.3868955000979639,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2965931042","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9732892,0.0012869892,0.00030892686,0.00020136655,0.0033905674,0.00019348804,0.000004550876,0.000041470023,0.021283431],"genre_scores_gemma":[0.9988112,0.00062096707,0.00035722277,0.00007442643,0.00003493164,0.000021445543,3.730973e-7,0.0000036575686,0.00007581334],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9969069,0.0001126636,0.0006293698,0.0012235448,0.0006885972,0.00043892124],"domain_scores_gemma":[0.9983649,0.0007337355,0.00016486117,0.0004782418,0.00012408393,0.00013413746],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003966857,0.00015849654,0.0003004613,0.0007015237,0.00020989352,0.00035259005,0.00073077425,0.00007612712,0.00032304466],"category_scores_gemma":[0.0020081399,0.00010482838,0.00005295665,0.0035030213,0.000719912,0.0011527896,0.00020299522,0.00036150092,0.00033321057],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001543736,0.00021620886,0.12925674,0.0000012250952,1.5432265e-7,0.0000038327944,0.00014786494,0.0002983723,0.0001703742,0.0023510081,0.000035297595,0.86750346],"study_design_scores_gemma":[0.0005809644,0.00019099787,0.39748976,0.00011585889,0.0000021389174,0.000044396482,0.0014269435,0.0022096443,0.00006493076,0.5778935,0.019583903,0.00039697596],"about_ca_topic_score_codex":0.000005102796,"about_ca_topic_score_gemma":0.00003859008,"teacher_disagreement_score":0.8671065,"about_ca_system_score_codex":0.000089563044,"about_ca_system_score_gemma":0.000033466593,"threshold_uncertainty_score":0.4282859},"labels":[],"label_agreement":null},{"id":"W2967056191","doi":"10.7554/elife.49154","title":"Metacontrol of decision-making strategies in human aging","year":2019,"lang":"en","type":"article","venue":"eLife","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":55,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Deutsche Forschungsgemeinschaft","keywords":"Cognitive aging; Situational ethics; Task (project management); Cognition; Dynamic decision-making; Psychology; Adaptation (eye); Cognitive psychology; Successful aging; Iowa gambling task; Stability (learning theory); Contrast (vision); Computer science; Social psychology; Artificial intelligence; Gerontology; Machine learning; Medicine; Neuroscience; Economics","score_opus":0.06585860026297663,"score_gpt":0.42490870457575414,"score_spread":0.3590501043127775,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2967056191","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9887944,0.00016245703,0.0014971242,0.000050297167,0.00055780355,0.00016508445,0.0000069513617,0.00002495487,0.008740932],"genre_scores_gemma":[0.99720806,0.0000044493318,0.0024018136,0.00013074005,0.000050809987,0.0000039497777,7.075211e-7,0.000014497195,0.0001849641],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99683625,0.000108607586,0.0012163676,0.000515312,0.0010405376,0.0002829561],"domain_scores_gemma":[0.99629116,0.002187387,0.00043022254,0.00081437454,0.00021391433,0.00006293136],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003312787,0.00016145449,0.0005951324,0.0006281724,0.000066603294,0.00032515562,0.0009470213,0.00009395391,0.0011435273],"category_scores_gemma":[0.0010895433,0.00012427034,0.0001895054,0.0005937287,0.00005878549,0.00065822614,0.00019673383,0.00018988311,0.00066662737],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009138619,0.00018899942,0.19839515,0.000006421854,0.000019858382,0.000049692502,0.0011045515,0.013535421,0.008861264,0.0075286184,0.0013550685,0.76886356],"study_design_scores_gemma":[0.0040998287,0.00049513235,0.26369813,0.0009772356,0.00005737256,0.000037832608,0.019203683,0.01490012,0.0029224062,0.6703078,0.0219549,0.001345539],"about_ca_topic_score_codex":0.000050504004,"about_ca_topic_score_gemma":0.0001997671,"teacher_disagreement_score":0.76751804,"about_ca_system_score_codex":0.000047345402,"about_ca_system_score_gemma":0.00010508055,"threshold_uncertainty_score":0.99976957},"labels":[],"label_agreement":null},{"id":"W2967278765","doi":"10.2139/ssrn.3233955","title":"Needs Versus Wants: Which Motivates More Effort?","year":2018,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Business; Computer science","score_opus":0.06626153073602628,"score_gpt":0.38170210721636594,"score_spread":0.31544057648033963,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2967278765","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9883041,0.00036441314,0.0028131353,0.0015223639,0.0022837934,0.000078658064,0.000004712,0.00004629492,0.0045825564],"genre_scores_gemma":[0.9960736,0.00023027437,0.00024372253,0.00013201548,0.000962493,0.0000020452812,0.0000016672899,0.000028967412,0.0023252345],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9952906,0.00009358182,0.00084555446,0.00041942435,0.0010564319,0.0022944426],"domain_scores_gemma":[0.9974256,0.0005101183,0.00043859155,0.0006253439,0.000790415,0.0002099326],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.006238441,0.00024533784,0.00037708553,0.0005837083,0.0005777744,0.00060282706,0.0014919591,0.00015469626,0.000577159],"category_scores_gemma":[0.0017948456,0.000173433,0.00021608213,0.0013038376,0.00018252843,0.0006622727,0.00016668858,0.0014359289,0.0017503753],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00051683263,0.000113115704,0.0077981157,4.3127056e-7,0.00009016324,0.000007423927,0.0005594701,0.00006363128,0.00021168165,0.01174129,0.004661298,0.97423655],"study_design_scores_gemma":[0.0019648217,0.0016673034,0.0027243479,0.000027905175,0.000054856282,0.00048452744,0.01051283,0.0006868871,0.0004997973,0.95261425,0.02831861,0.0004438774],"about_ca_topic_score_codex":0.000034485336,"about_ca_topic_score_gemma":0.0007392791,"teacher_disagreement_score":0.9737927,"about_ca_system_score_codex":0.00066824735,"about_ca_system_score_gemma":0.0016977969,"threshold_uncertainty_score":0.9990269},"labels":[],"label_agreement":null},{"id":"W2970094891","doi":"10.1001/jamapsychiatry.2019.2102","title":"Delay Discounting as a Transdiagnostic Process in Psychiatric Disorders","year":2019,"lang":"en","type":"review","venue":"JAMA Psychiatry","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":406,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; St. Joseph’s Healthcare Hamilton","funders":"","keywords":"PsycINFO; Psychology; Meta-analysis; Borderline personality disorder; Clinical psychology; MEDLINE; Discounting; Delay discounting; Psychiatry; Impulsivity; Medicine","score_opus":0.1057808425814239,"score_gpt":0.46516555825593936,"score_spread":0.35938471567451546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2970094891","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010394711,0.97074854,0.00008184353,0.0008745938,0.009314161,0.0015201065,0.000120666,0.00008134137,0.006864053],"genre_scores_gemma":[0.002268482,0.99503076,0.00070330594,0.00039252074,0.00072120555,0.00019820053,0.000049966777,0.00016604153,0.00046953297],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9914284,0.00042342843,0.0035396696,0.002165785,0.0015582042,0.0008845268],"domain_scores_gemma":[0.993189,0.0027642664,0.0017887601,0.0018871807,0.00013188022,0.00023895125],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0031051885,0.0009673409,0.0031666246,0.002153656,0.00020261624,0.0012274332,0.0033693125,0.0010607449,0.0006447027],"category_scores_gemma":[0.0017435963,0.0007048118,0.0015817233,0.0037942443,0.00011248315,0.0008540188,0.00017470315,0.0016529828,0.0066347956],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021760568,0.0003176229,0.003510459,0.001664346,0.000024545247,0.000008557656,0.00014995299,0.00006788048,1.7294411e-9,0.0002698937,0.003822763,0.9901422],"study_design_scores_gemma":[0.0007909415,0.00013179322,0.0002265282,0.0067398897,0.00044715917,0.00008343286,0.00052833144,0.000081769445,4.4722546e-9,0.08794719,0.90200865,0.0010142872],"about_ca_topic_score_codex":0.000079832746,"about_ca_topic_score_gemma":0.0007959937,"teacher_disagreement_score":0.98912793,"about_ca_system_score_codex":0.0001607809,"about_ca_system_score_gemma":0.0019427973,"threshold_uncertainty_score":0.9998094},"labels":[],"label_agreement":null},{"id":"W2970136895","doi":"10.2139/ssrn.3099746","title":"The Quantity Integration Effect: Integrating Purchase and Quantity Decisions Increases Sales by Providing Closure","year":2018,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Revenue; Marketing; Business; Robustness (evolution); Control (management); Computer science; Advertising; Accounting","score_opus":0.04563230780124244,"score_gpt":0.3729167999343486,"score_spread":0.3272844921331062,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2970136895","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9636138,0.0024711017,0.032498967,0.00051397155,0.00052364223,0.00021348316,0.000014537228,0.000039500464,0.00011100637],"genre_scores_gemma":[0.9975255,0.0014096305,0.00042697988,0.00006189031,0.0003227439,0.000007644626,0.000004832077,0.000022421105,0.00021834193],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9954283,0.0006867455,0.0010041064,0.0005444971,0.0009073344,0.0014290033],"domain_scores_gemma":[0.9930911,0.004936921,0.0006787094,0.0005371697,0.00055531267,0.00020075972],"candidate_categories":["metaresearch","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.018869162,0.00028350018,0.00039973325,0.00024622574,0.0024994926,0.0019278375,0.0010429028,0.00014842374,0.000022952447],"category_scores_gemma":[0.018804073,0.00015405225,0.00020587271,0.00055709895,0.00044151704,0.00086928654,0.00022002275,0.0016820617,0.00013924438],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020698774,0.00006649646,0.03142336,5.5876205e-7,0.000028740125,0.0000025812365,0.00014635333,0.0000016865733,0.0014181816,0.01949375,0.001673313,0.945538],"study_design_scores_gemma":[0.0012172142,0.0029832884,0.0038222172,0.00017908232,0.00010289641,0.0009628348,0.00921712,0.003962936,0.001341088,0.9654647,0.010183808,0.00056278036],"about_ca_topic_score_codex":0.0004595287,"about_ca_topic_score_gemma":0.017112363,"teacher_disagreement_score":0.945971,"about_ca_system_score_codex":0.0004418083,"about_ca_system_score_gemma":0.0009316854,"threshold_uncertainty_score":0.99910825},"labels":[],"label_agreement":null},{"id":"W2971069477","doi":"10.32470/ccn.2019.1359-0","title":"FEF Biases the Persistence of Expectation","year":2019,"lang":"en","type":"article","venue":"2019 Conference on Cognitive Computational Neuroscience","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Queen's University","funders":"","keywords":"Persistence (discontinuity); Computer science; Engineering","score_opus":0.3589947543367379,"score_gpt":0.42631655551099806,"score_spread":0.06732180117426018,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2971069477","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9854675,0.000010060637,0.0071626925,0.00061338604,0.0008363168,0.00030484048,0.00009488465,0.000021076288,0.0054892506],"genre_scores_gemma":[0.9980292,0.000007694433,0.00022455117,0.0010040662,0.000021302505,0.000007928181,0.000007777932,0.000007254721,0.00069022697],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99674803,0.00023037974,0.0005624388,0.0007255232,0.0015138674,0.00021975953],"domain_scores_gemma":[0.9919176,0.005845508,0.0004967566,0.00035092153,0.0013085387,0.000080687336],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009959036,0.00016678892,0.00025494047,0.00026633518,0.00022612265,0.00032167407,0.0010452443,0.000042604926,0.00048991153],"category_scores_gemma":[0.004448229,0.00010866657,0.00013022962,0.0008027992,0.0005447163,0.00045328584,0.00015923391,0.00016626016,0.0015268404],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00061651546,0.0010286047,0.06268315,0.000014184015,0.000016102453,0.000026460975,0.00358978,0.10559343,0.015727935,0.046542384,0.003732206,0.76042926],"study_design_scores_gemma":[0.0011095947,0.0014162416,0.508273,0.00036308565,0.000025382666,0.000045223416,0.0059589283,0.35281286,0.002278247,0.12625198,0.00085354404,0.00061192224],"about_ca_topic_score_codex":0.000009446856,"about_ca_topic_score_gemma":0.0000033722108,"teacher_disagreement_score":0.75981736,"about_ca_system_score_codex":0.000021690474,"about_ca_system_score_gemma":0.000275621,"threshold_uncertainty_score":0.9992506},"labels":[],"label_agreement":null},{"id":"W2971443674","doi":"10.1108/vjikms-12-2018-0129","title":"If numbers could “feel”: How well do executives trust their intuition?","year":2019,"lang":"en","type":"article","venue":"VINE Journal of Information and Knowledge Management Systems","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Waterloo; Queen's University","funders":"","keywords":"Intuition; Psychology; Social psychology; Knowledge management; Computer science","score_opus":0.031816078604875925,"score_gpt":0.3134838036022219,"score_spread":0.28166772499734594,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2971443674","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6689113,0.00058324623,0.011649098,0.00049395836,0.005182996,0.00063018664,0.000022532982,0.000034182893,0.31249252],"genre_scores_gemma":[0.99476135,0.00023273735,0.00018970369,0.000075363714,0.00014415462,0.0000040709683,0.0000038026537,0.0000073498622,0.0045814943],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9975648,0.00012065693,0.0013639408,0.00015291784,0.0006119387,0.00018574264],"domain_scores_gemma":[0.99727666,0.00023708536,0.0013887022,0.0003431154,0.00061411655,0.0001403346],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0034215348,0.00018757005,0.00045740372,0.0009404194,0.00012515268,0.0014439037,0.0005638952,0.00008449176,0.00023220031],"category_scores_gemma":[0.00012449712,0.00012130231,0.00016122528,0.00045078635,0.00005036044,0.0025389967,0.00017780744,0.00017841233,0.0012402689],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024924614,0.00023344782,0.014570928,0.00027930684,0.00021539512,0.000012455313,0.0067910952,0.0010220672,0.000040940537,0.032128774,0.21962506,0.7248313],"study_design_scores_gemma":[0.0014679615,0.00023881946,0.002247402,0.0003379194,0.000034292403,0.000092431335,0.053727284,0.006714646,0.00002161525,0.0026649726,0.93220973,0.00024291751],"about_ca_topic_score_codex":0.0000025721733,"about_ca_topic_score_gemma":0.0000016519349,"teacher_disagreement_score":0.7245884,"about_ca_system_score_codex":0.00009383424,"about_ca_system_score_gemma":0.000040239247,"threshold_uncertainty_score":0.9995927},"labels":[],"label_agreement":null},{"id":"W2972845345","doi":"10.1017/beq.2019.19","title":"Big Data and Personalized Pricing","year":2019,"lang":"en","type":"article","venue":"Business Ethics Quarterly","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":50,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Big data; Reservation; Point (geometry); Economics; Microeconomics; Welfare; Public economics; Business; Market economy; Computer science; Political science; Law","score_opus":0.39761866616654307,"score_gpt":0.4326414813813234,"score_spread":0.035022815214780345,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2972845345","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98489726,0.0001806061,0.007078778,0.003932938,0.0020285165,0.00016866,0.0000546735,0.000052795884,0.0016057643],"genre_scores_gemma":[0.99660844,0.00002377528,0.0013684569,0.000667275,0.00019155654,0.0000024244166,0.000021278882,0.00002113174,0.001095651],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9969414,0.00019256087,0.0006300086,0.00092825486,0.0010406788,0.0002670904],"domain_scores_gemma":[0.9942123,0.0029127798,0.00028306898,0.0018461527,0.00063584547,0.000109837034],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0057379436,0.00018690033,0.0004032553,0.00025976353,0.00020043457,0.0008952395,0.0014495123,0.00025728316,0.00023634643],"category_scores_gemma":[0.0019452097,0.0001411343,0.000046491296,0.0006832846,0.00018978647,0.0006841674,0.00027039688,0.0004925057,0.0011431695],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004031314,0.000041534942,0.006718262,0.000014813831,0.0000068617082,0.000011161627,0.0033427943,0.000008277908,0.0005381855,0.0013046913,0.0011533835,0.98681974],"study_design_scores_gemma":[0.0036352582,0.00050984044,0.10993752,0.00044477012,0.00010705875,0.0002428446,0.019086748,0.018290838,0.000035613437,0.35533392,0.4906619,0.0017137101],"about_ca_topic_score_codex":0.00014898898,"about_ca_topic_score_gemma":0.00013469037,"teacher_disagreement_score":0.985106,"about_ca_system_score_codex":0.000022079626,"about_ca_system_score_gemma":0.00025724317,"threshold_uncertainty_score":0.99963456},"labels":[],"label_agreement":null},{"id":"W2973154528","doi":"10.1002/bdm.2154","title":"Examining children's ability to delay reward: Is the delay discounting task a suitable measure?","year":2019,"lang":"en","type":"article","venue":"Journal of Behavioral Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"Economic and Social Research Council; Research Councils UK","keywords":"Delay discounting; Discounting; Delay of gratification; Psychology; Gratification; Task (project management); Temporal discounting; Impulsivity; Sensation seeking; Intertemporal choice; Developmental psychology; Social psychology; Econometrics; Economics","score_opus":0.09533285482985453,"score_gpt":0.3918347828173961,"score_spread":0.29650192798754155,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2973154528","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9871695,0.0002511408,0.008520564,0.0003763179,0.0026942955,0.0005430431,0.00003879352,0.00003078703,0.00037557934],"genre_scores_gemma":[0.98432416,0.000007549591,0.014394056,0.00067513133,0.00031665605,0.000006282915,8.1038553e-7,0.000062536696,0.00021280587],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9894874,0.0004760784,0.0036310786,0.0010778763,0.0044740117,0.0008535289],"domain_scores_gemma":[0.9890381,0.0043285345,0.0024516957,0.0020064863,0.0017729852,0.00040215935],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.018623397,0.0005228278,0.0012459981,0.0010212549,0.00061368797,0.0020593037,0.0034929065,0.0003096487,0.0012967489],"category_scores_gemma":[0.0038364439,0.00031672925,0.0008071544,0.0017644472,0.0001287015,0.001775378,0.00096059596,0.0011993332,0.0010744323],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033313825,0.00020339918,0.35898072,0.0000017620349,0.000018348179,0.0000869523,0.0012545526,0.0025007618,0.0013509538,0.000019499901,0.0061867433,0.6290632],"study_design_scores_gemma":[0.0037451345,0.002884985,0.8948073,0.0025362922,0.0006476755,0.0036560008,0.010878001,0.0016342364,0.0006026054,0.051149983,0.02504198,0.0024158303],"about_ca_topic_score_codex":0.000066019966,"about_ca_topic_score_gemma":0.00006192549,"teacher_disagreement_score":0.62664735,"about_ca_system_score_codex":0.00040374548,"about_ca_system_score_gemma":0.00030940503,"threshold_uncertainty_score":0.9999285},"labels":[],"label_agreement":null},{"id":"W297316193","doi":"","title":"No Two Experiments are Identical","year":2014,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Ambiguity; Knightian uncertainty; Ambiguity aversion; Econometrics; Ball (mathematics); Relation (database); Mathematics; Psychology; Mathematical economics; Social psychology; Computer science; Philosophy; Linguistics; Geometry","score_opus":0.1954498705061671,"score_gpt":0.48871590734404613,"score_spread":0.293266036837879,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W297316193","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8686876,0.000079651276,0.000029016493,0.00019871468,0.0030796307,0.0005795777,0.00006755674,0.000056293673,0.12722194],"genre_scores_gemma":[0.98786,0.0006744932,0.0015632366,0.00023058624,0.0007634447,0.00018234886,0.00002495296,0.00009837557,0.00860253],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9910456,0.00094373984,0.002573103,0.00261028,0.0015537577,0.0012735106],"domain_scores_gemma":[0.9906445,0.0036002528,0.0008647182,0.0036570465,0.00066566415,0.00056780694],"candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication","research_integrity","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.012882485,0.0005586079,0.0014221309,0.0014353329,0.0003002963,0.0018257315,0.004144628,0.0007312323,0.0016105355],"category_scores_gemma":[0.009335283,0.0005174133,0.0005659856,0.0002879628,0.0006339702,0.0002909038,0.00519016,0.002524622,0.0028701974],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020709215,0.0004539659,0.024493314,0.000029583847,0.000051517367,0.00013120731,0.00024566264,0.007857479,0.000107543936,0.00034728606,0.0034334913,0.96264184],"study_design_scores_gemma":[0.004219697,0.0004885881,0.021595558,0.0014014335,0.000043185868,0.00007406127,0.0033608265,0.115874134,0.00060994667,0.3321411,0.5167626,0.0034288315],"about_ca_topic_score_codex":0.000099173034,"about_ca_topic_score_gemma":0.00029765928,"teacher_disagreement_score":0.959213,"about_ca_system_score_codex":0.0011741765,"about_ca_system_score_gemma":0.00057183206,"threshold_uncertainty_score":0.9997766},"labels":[],"label_agreement":null},{"id":"W2978060606","doi":"10.1037/rev0000166","title":"Accumulating advantages: A new conceptualization of rapid multiple choice.","year":2019,"lang":"en","type":"article","venue":"Psychological Review","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":40,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Australian Research Council; Natural Sciences and Engineering Research Council of Canada; University of South Australia","keywords":"Accumulator (cryptography); Hydraulic accumulator; Conceptualization; Binary number; Computer science; Benchmark (surveying); Artificial intelligence; Algorithm; Mathematics; Arithmetic","score_opus":0.3640301810318859,"score_gpt":0.5351487065253254,"score_spread":0.17111852549343953,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2978060606","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95091385,0.030943464,0.003185201,0.0007190449,0.00091500743,0.0009068675,0.000013865684,0.00006771083,0.012334964],"genre_scores_gemma":[0.98640394,0.007705638,0.002944385,0.002196133,0.000068475485,0.000007772456,0.00000814903,0.000011623289,0.00065390475],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9969919,0.00024216974,0.0013178932,0.0006278963,0.0006043642,0.00021578713],"domain_scores_gemma":[0.994595,0.0034860154,0.0007167016,0.0008784261,0.00017947532,0.00014438819],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0020109843,0.000165395,0.0007392193,0.000084450534,0.000046015288,0.00006434077,0.0008274729,0.00010811517,0.010168444],"category_scores_gemma":[0.014972691,0.0001032256,0.00027794932,0.000653075,0.00006412478,0.0002481075,0.00012276284,0.00014986077,0.00237191],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011754684,0.000077452474,0.030149,0.000032496868,0.0000029692267,0.0000010569988,0.00003198449,0.000030148383,0.00018060704,0.00017944355,0.006729739,0.96257335],"study_design_scores_gemma":[0.0014279716,0.0006404684,0.0663968,0.002521192,0.00004824784,0.000018994371,0.00015099069,0.0008282754,0.000057426045,0.01799879,0.90942836,0.0004824681],"about_ca_topic_score_codex":0.000008374266,"about_ca_topic_score_gemma":0.0000029387713,"teacher_disagreement_score":0.96209085,"about_ca_system_score_codex":0.000018465396,"about_ca_system_score_gemma":0.000018494415,"threshold_uncertainty_score":0.99840486},"labels":[],"label_agreement":null},{"id":"W2978435530","doi":"10.1111/sjop.12583","title":"Measuring delay discounting in a crowdsourced sample: An exploratory study","year":2019,"lang":"en","type":"article","venue":"Scandinavian Journal of Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina; University of Guelph","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Discounting; Delay discounting; Psychology; Sample (material); Matching (statistics); Task (project management); Measure (data warehouse); Compensation (psychology); Econometrics; Social psychology; Statistics; Economics; Computer science; Mathematics","score_opus":0.22935838170727837,"score_gpt":0.4488393980587884,"score_spread":0.21948101635151004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2978435530","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9958526,0.00008133689,0.0009484556,0.00016453487,0.0021540998,0.00017868799,0.0000048188886,0.000009018342,0.0006064569],"genre_scores_gemma":[0.99875546,0.0000046262044,0.000823529,0.00017752594,0.00016705181,0.0000026361229,4.549656e-7,0.000021995675,0.000046696463],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9960365,0.00063309894,0.0016491631,0.0005130696,0.00078769994,0.00038046224],"domain_scores_gemma":[0.99706805,0.0006511109,0.0010195941,0.00074258604,0.00030843462,0.00021022551],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008240636,0.00019211527,0.0006746946,0.0011008556,0.00008894412,0.00026385175,0.0013072352,0.00011263042,0.00068452716],"category_scores_gemma":[0.0009874624,0.00014513872,0.00016617398,0.00071003207,0.00007849156,0.00093429396,0.00010001112,0.00052684295,0.00023596425],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028656225,0.00047836752,0.865892,9.446859e-7,0.000014173136,0.00018603414,0.0045191767,0.000338644,0.0006222001,0.000017363349,0.00022495074,0.12741956],"study_design_scores_gemma":[0.006737557,0.004417691,0.8875687,0.00022307629,0.000047032136,0.0008705208,0.044631198,0.00026119535,0.00005631846,0.051457968,0.0030990334,0.0006297225],"about_ca_topic_score_codex":0.000020048366,"about_ca_topic_score_gemma":0.00030999523,"teacher_disagreement_score":0.12678984,"about_ca_system_score_codex":0.00010200773,"about_ca_system_score_gemma":0.00007970969,"threshold_uncertainty_score":0.7495092},"labels":[],"label_agreement":null},{"id":"W2978760545","doi":"10.1111/1911-3846.12568","title":"Intuition versus Analytical Thinking and Impairment Testing","year":2019,"lang":"en","type":"article","venue":"Contemporary Accounting Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Intuition; Audit; Psychology; Skepticism; Cognitive psychology; Epistemology; Accounting; Philosophy; Economics; Cognitive science","score_opus":0.4133382902365313,"score_gpt":0.491748148346807,"score_spread":0.07840985811027573,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2978760545","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96060693,0.00016658289,0.00007321363,0.00078912446,0.0005914776,0.000344711,0.000005910876,0.00006586998,0.037356205],"genre_scores_gemma":[0.9983406,0.0000036617673,0.00070568617,0.00008255741,0.00017633104,0.000008277285,0.0000049920136,0.000020520749,0.0006573815],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9954022,0.00033794402,0.0007766333,0.0008619497,0.0021010889,0.00052016013],"domain_scores_gemma":[0.98908585,0.008803203,0.0002229447,0.00077796,0.0009386815,0.00017132942],"candidate_categories":["metaresearch","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.018938933,0.00016592065,0.00035663732,0.0007486264,0.0005348077,0.0018441676,0.0009224992,0.00013799533,0.00032071237],"category_scores_gemma":[0.009237795,0.0001321387,0.00008353007,0.0012875152,0.00021374263,0.0011954686,0.000960857,0.00065338047,0.0014086488],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045941042,0.00012339551,0.6221358,0.000017383261,0.000019424273,0.00004751846,0.00057629176,0.000047090132,0.00048843585,0.0027153783,0.011771706,0.36159816],"study_design_scores_gemma":[0.007761145,0.002983821,0.2664459,0.0010379528,0.000025867099,0.00008404262,0.016078364,0.13954456,0.0003448367,0.47394964,0.090108715,0.0016351505],"about_ca_topic_score_codex":0.00010911412,"about_ca_topic_score_gemma":0.000008172912,"teacher_disagreement_score":0.47123426,"about_ca_system_score_codex":0.0001287183,"about_ca_system_score_gemma":0.0002986945,"threshold_uncertainty_score":0.99936885},"labels":[],"label_agreement":null},{"id":"W2979898024","doi":"10.1371/journal.pone.0220690","title":"Can knowledge of election results change recall of our predictions? Neural correlates of political hindsight bias","year":2019,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Ottawa Mental Health Centre; University of Ottawa","funders":"Ministry of Science and Technology, Taiwan; National Chengchi University","keywords":"Hindsight bias; Recall; Context (archaeology); Functional magnetic resonance imaging; Neural correlates of consciousness; Cognitive psychology; Phenomenon; Inferior frontal gyrus; Psychology; Demographics; Cognition; Neuropsychology; Medicine; Neuroscience; Demography; Biology","score_opus":0.33000569542831787,"score_gpt":0.3766594115940871,"score_spread":0.04665371616576924,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2979898024","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9963142,0.00006558424,0.000007775042,0.0005874189,0.000474913,0.00024820986,0.00019212843,0.000021255724,0.0020884958],"genre_scores_gemma":[0.99849766,0.000011303139,0.00023840039,0.000017976745,0.00010036141,0.0000065243694,0.000009791835,0.000011527216,0.0011064331],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99762,0.00013956068,0.0011056544,0.00034425725,0.0005609749,0.00022954184],"domain_scores_gemma":[0.9972582,0.0008420916,0.0005619186,0.00055651576,0.0006709157,0.000110381094],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010753551,0.00011765548,0.00053307356,0.0004127494,0.000034222867,0.000023034414,0.00038076457,0.00014251843,0.00007658979],"category_scores_gemma":[0.002065002,0.00009279379,0.0001338096,0.0005560088,0.00006979183,0.00019149558,0.00010556945,0.00017279306,0.00010571839],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0025300707,0.015551443,0.7723858,0.00023021542,0.00036424224,0.0000063201046,0.0073687322,0.00020888976,0.050728496,0.0067852032,0.0049856603,0.13885497],"study_design_scores_gemma":[0.005831213,0.007616951,0.63708043,0.0020248247,0.00069254154,0.00003107181,0.004973638,0.0847816,0.20948438,0.04561636,0.00083515194,0.001031837],"about_ca_topic_score_codex":0.00032097136,"about_ca_topic_score_gemma":0.00016580927,"teacher_disagreement_score":0.15875588,"about_ca_system_score_codex":0.00005579047,"about_ca_system_score_gemma":0.00007562701,"threshold_uncertainty_score":0.37840208},"labels":[],"label_agreement":null},{"id":"W2983309011","doi":"10.1016/j.ijpsycho.2019.11.002","title":"Behavioural and neural interactions between objective and subjective performance in a Matching Pennies game","year":2019,"lang":"en","type":"article","venue":"International Journal of Psychophysiology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta; Toronto Metropolitan University","funders":"","keywords":"Outcome (game theory); Optimism; Psychology; Contingency; Matching (statistics); Negativity effect; Social psychology; Contrast (vision); Ultimatum game; Contingency table; Statistics; Cognitive psychology; Mathematics; Economics; Computer science; Artificial intelligence; Microeconomics","score_opus":0.0723373270005191,"score_gpt":0.40489139665151846,"score_spread":0.3325540696509994,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2983309011","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9971001,0.000047847712,0.00007057204,0.0004892074,0.0019886591,0.00006785704,0.000013295826,0.0000038009823,0.0002186655],"genre_scores_gemma":[0.99933624,0.000043520526,0.00026209804,0.00010768195,0.00017317089,0.0000015776387,0.0000014055295,0.0000071219724,0.00006715759],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984585,0.00011183817,0.00069636054,0.00025983408,0.0003391713,0.00013430488],"domain_scores_gemma":[0.9979939,0.00091106776,0.00053942885,0.000120658355,0.0003717541,0.00006323079],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005885713,0.00011809174,0.00034579693,0.00061153696,0.00003228083,0.00013868067,0.00044273824,0.000058216967,0.00008915738],"category_scores_gemma":[0.00017549563,0.00009007025,0.00008412565,0.00012730662,0.00010060156,0.0008021967,0.00013376407,0.00038207546,0.000028996714],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00042542446,0.00005664105,0.88000786,0.000001033179,0.00003764159,0.000017693781,0.0017284376,0.00028872455,0.0034145096,0.000049047005,0.000027956108,0.11394501],"study_design_scores_gemma":[0.0007609084,0.00029752264,0.96715045,0.000044293276,0.000008399298,0.00025136714,0.0012766466,0.0005364945,0.000080412145,0.02938261,0.00011599144,0.00009487952],"about_ca_topic_score_codex":0.00006625566,"about_ca_topic_score_gemma":0.00004773362,"teacher_disagreement_score":0.11385013,"about_ca_system_score_codex":0.00007203402,"about_ca_system_score_gemma":0.000033515607,"threshold_uncertainty_score":0.36729583},"labels":[],"label_agreement":null},{"id":"W2984820708","doi":"10.1108/ijse-04-2019-0271","title":"Individual time preferences and obesity","year":2019,"lang":"en","type":"article","venue":"International Journal of Social Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Patience; Obesity; Probit model; Discounting; Time preference; Multivariate probit model; Psychological intervention; Psychology; Population; Demography; Medicine; Social psychology; Environmental health; Economics; Econometrics","score_opus":0.07909981303627495,"score_gpt":0.3702086427050974,"score_spread":0.29110882966882246,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2984820708","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9927364,0.000025802003,0.000028567918,0.00093070127,0.0017530641,0.000041098046,0.000048981856,0.000004565585,0.004430848],"genre_scores_gemma":[0.99831647,0.00003358522,0.0004776481,0.00024856665,0.00043262212,2.9555733e-7,0.0000023276918,0.0000065414765,0.00048196246],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.998411,0.000050918712,0.00081442134,0.00018766007,0.0004280136,0.00010798364],"domain_scores_gemma":[0.99800587,0.0004793849,0.00089572597,0.0000957775,0.00044783452,0.00007540776],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0017179244,0.0000955013,0.0003112846,0.0002704646,0.000058702273,0.00057997234,0.001058599,0.00009066726,0.0011392011],"category_scores_gemma":[0.00029212653,0.000079007295,0.00015422665,0.000055308938,0.00007832186,0.00071812177,0.00020967187,0.00016946625,0.0005862298],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019810926,0.00015684517,0.11279176,0.0000011080502,0.00019711217,0.000019265657,0.0018633521,0.00028754142,0.0001196228,0.0051735104,0.0054505854,0.8737412],"study_design_scores_gemma":[0.002087421,0.0003362018,0.282678,0.00003663307,0.00005445471,0.000325159,0.0020995724,0.0012523256,0.00020620834,0.5998941,0.110566825,0.0004630663],"about_ca_topic_score_codex":0.000006149576,"about_ca_topic_score_gemma":0.000008250826,"teacher_disagreement_score":0.87327814,"about_ca_system_score_codex":0.00008987906,"about_ca_system_score_gemma":0.00013786521,"threshold_uncertainty_score":0.9997739},"labels":[],"label_agreement":null},{"id":"W2985836649","doi":"10.1007/s11229-019-02431-2","title":"Naturalism, tractability and the adaptive toolbox","year":2019,"lang":"en","type":"article","venue":"Synthese","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Austrian Science Fund; Deutsche Forschungsgemeinschaft","keywords":"Heuristics; Rationality; Computer science; Bounded rationality; Simple (philosophy); Ecological rationality; Normative; Epistemology; Process (computing); Toolbox; Adaptation (eye); Management science; Artificial intelligence; Philosophy; Psychology; Economics","score_opus":0.0791218413362354,"score_gpt":0.3611739249628632,"score_spread":0.2820520836266278,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2985836649","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98413235,0.00014730963,0.000037367405,0.0017135201,0.0005776918,0.00024007473,0.000015468284,0.000022832655,0.013113385],"genre_scores_gemma":[0.99809074,0.0000057496177,0.00028002908,0.00029013652,0.00004032036,0.000006593212,2.8321426e-7,0.000006782928,0.0012793335],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.998285,0.0002449492,0.00039291938,0.00043414586,0.00047184722,0.00017113653],"domain_scores_gemma":[0.992684,0.006182868,0.00015298183,0.0007962268,0.000118163836,0.00006575488],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.003807904,0.00011476687,0.00030186115,0.000067091,0.000099909244,0.00029767488,0.00059966726,0.00007579747,0.00091755815],"category_scores_gemma":[0.0030957554,0.00005493639,0.00012935928,0.00019060323,0.00029401897,0.00033213533,0.00012729313,0.000191936,0.0013295914],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004330166,0.000049097187,0.00719668,0.0000011726863,0.000010230649,0.000003845476,0.0012778394,0.000027702728,0.00014137458,0.007664991,0.0010708922,0.98212314],"study_design_scores_gemma":[0.002300593,0.00017913693,0.093576334,0.00005532103,0.000051561954,0.00007144374,0.012110041,0.009737939,0.000670992,0.77975184,0.10084289,0.0006519052],"about_ca_topic_score_codex":0.00008884295,"about_ca_topic_score_gemma":0.000040552775,"teacher_disagreement_score":0.98147124,"about_ca_system_score_codex":0.000025092157,"about_ca_system_score_gemma":0.00003182549,"threshold_uncertainty_score":0.99999577},"labels":[],"label_agreement":null},{"id":"W2989005856","doi":"10.5539/ijsp.v8n6p82","title":"Expected Winning Probabilities in Sequential Truels under Uniform Distributions","year":2019,"lang":"en","type":"article","venue":"International Journal of Statistics and Probability","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Mathematics; Conjecture; Sequential estimation; Mathematical economics; Computer science; Statistics; Combinatorics","score_opus":0.08631143428977427,"score_gpt":0.38676363064836405,"score_spread":0.3004521963585898,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2989005856","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9618583,0.000032546002,0.035447873,0.00075473735,0.0010734439,0.00012560587,0.000367384,0.000004750474,0.0003354098],"genre_scores_gemma":[0.9844346,0.000013848308,0.015341288,0.00005039755,0.000058895064,0.0000018556032,0.000012000117,0.0000049532246,0.000082156614],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99750334,0.00011492237,0.0011829275,0.00024138394,0.0008111865,0.00014626856],"domain_scores_gemma":[0.99679786,0.0011794614,0.0005323569,0.00019215373,0.0012120091,0.00008614423],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022443149,0.00011058784,0.00029363018,0.00023761817,0.00004452262,0.00034532807,0.00049953355,0.00006156328,0.00050371146],"category_scores_gemma":[0.0017842102,0.000083496685,0.00007801097,0.00016799624,0.00012604705,0.00042683975,0.0001302578,0.00022815968,0.000020771411],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00066394184,0.00065793504,0.46431506,0.000017502654,0.00009873882,0.00008123661,0.0016571135,0.0060531944,0.0005022705,0.19269003,0.0013694327,0.33189353],"study_design_scores_gemma":[0.000600776,0.00012700011,0.08052031,0.000044272994,0.00000733031,0.00006538594,0.00047817684,0.0014563942,0.000048515256,0.9144777,0.0020703287,0.0001037889],"about_ca_topic_score_codex":0.00004846384,"about_ca_topic_score_gemma":0.00010584647,"teacher_disagreement_score":0.7217877,"about_ca_system_score_codex":0.00023696406,"about_ca_system_score_gemma":0.00021178971,"threshold_uncertainty_score":0.55152875},"labels":[],"label_agreement":null},{"id":"W2989553804","doi":"10.1177/0956797619876982","title":"The Sign Effect in Past and Future Discounting","year":2019,"lang":"en","type":"article","venue":"Psychological Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada; Booth School of Business, University of Chicago; John Templeton Foundation","keywords":"Psychology; Temporal discounting; Sign (mathematics); Discounting; Contemplation; Delay discounting; Phenomenon; Social psychology; Cognitive psychology; Event (particle physics); Developmental psychology; Epistemology; Economics","score_opus":0.06147263609594121,"score_gpt":0.4436096675196458,"score_spread":0.3821370314237046,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2989553804","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98480374,0.00007211065,0.000030258563,0.0023016927,0.0011263313,0.00016198691,8.3403773e-7,0.000014534013,0.011488526],"genre_scores_gemma":[0.99924165,0.000021715174,0.00016769173,0.00029419622,0.000105878986,0.000005306145,6.2900995e-8,0.0000023375753,0.00016114421],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9976739,0.00013183549,0.0003476818,0.0007370162,0.00074450695,0.00036505726],"domain_scores_gemma":[0.99713266,0.0020579335,0.00011761579,0.0005404265,0.000052960226,0.00009843081],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010006629,0.00010226236,0.00017960597,0.000104665945,0.00034143738,0.00092676136,0.0013636546,0.000060585375,0.00014413967],"category_scores_gemma":[0.0011033284,0.000043038035,0.00004589059,0.0011711123,0.0006293734,0.00037702578,0.0002478621,0.00020720834,0.0005914236],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020445303,0.00001943144,0.17771368,1.9012568e-7,2.0692505e-7,0.0000029803803,0.00004970133,0.000007635363,0.0006303007,0.0007654786,0.0002491605,0.8205408],"study_design_scores_gemma":[0.00023114218,0.00023485761,0.9239636,0.000007642171,0.0000011031698,0.0000115544235,0.0003581011,0.0004747416,0.000026148275,0.056243885,0.018324217,0.0001230229],"about_ca_topic_score_codex":0.0000045901847,"about_ca_topic_score_gemma":0.0000092926975,"teacher_disagreement_score":0.82041776,"about_ca_system_score_codex":0.000026886848,"about_ca_system_score_gemma":0.000011427133,"threshold_uncertainty_score":0.8936781},"labels":[],"label_agreement":null},{"id":"W2990137292","doi":"10.3758/s13421-019-00998-2","title":"Who resists belief-biased inferences? The role of individual differences in reasoning strategies, working memory, and attentional focus","year":2019,"lang":"en","type":"article","venue":"Memory & Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Psychology; Working memory; Cognitive psychology; Counterexample; Inference; Cognition; Focus (optics); Task (project management); Causal inference; Fixation (population genetics); Information processing; Artificial intelligence; Computer science; Econometrics","score_opus":0.08557412558674711,"score_gpt":0.32896692151889184,"score_spread":0.24339279593214475,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2990137292","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9867199,0.0003254308,0.00004827168,0.00012871313,0.00021343515,0.0002597203,0.000032790645,0.00001818034,0.012253581],"genre_scores_gemma":[0.9994752,0.000024071405,0.00017580159,0.00005398647,0.00005651229,0.00001645006,0.00001854767,0.000009561132,0.00016986596],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99718165,0.00030036888,0.0007502743,0.0005148315,0.0009848278,0.00026804986],"domain_scores_gemma":[0.99737823,0.0015274523,0.00049074774,0.00034769368,0.00018887293,0.000066981105],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002908971,0.00017869654,0.00038768147,0.00033821128,0.00017090725,0.0005889027,0.0005691865,0.00012418278,0.00042089718],"category_scores_gemma":[0.0005921985,0.00012421179,0.000089435474,0.00047961983,0.00019990494,0.0005143222,0.00019733046,0.00026034506,0.00007741407],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012559288,0.00011755005,0.23552637,0.000006286491,0.00002044161,0.0000060322004,0.0013595121,0.000057937497,0.0013438755,0.0013330918,0.0000815036,0.7600218],"study_design_scores_gemma":[0.0007475352,0.00012296588,0.7934488,0.00039137504,0.00003891214,0.0000110963565,0.013039217,0.0007490467,0.00085413834,0.19020024,0.00016689031,0.00022980126],"about_ca_topic_score_codex":0.00011228518,"about_ca_topic_score_gemma":0.0005844876,"teacher_disagreement_score":0.75979203,"about_ca_system_score_codex":0.000027732774,"about_ca_system_score_gemma":0.00015177226,"threshold_uncertainty_score":0.5678802},"labels":[],"label_agreement":null},{"id":"W2995194683","doi":"10.1387/theoria.20040","title":"The philosopher’s paradox: How to make a coherent decision in the Newcomb Problem","year":2019,"lang":"en","type":"article","venue":"THEORIA An International Journal for Theory History and Foundations of Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Coherence (philosophical gambling strategy); Argument (complex analysis); Constraint (computer-aided design); Swing; Mathematical economics; Computer science; Epistemology; Psychology; Economics; Philosophy; Mathematics; Engineering","score_opus":0.11154307449697283,"score_gpt":0.4157746412767543,"score_spread":0.30423156677978147,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2995194683","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9781007,0.00010980726,0.0096099945,0.0029202981,0.005541789,0.00046018115,0.000015086563,0.000006779356,0.0032353727],"genre_scores_gemma":[0.99599546,0.000031490494,0.00246095,0.00033545028,0.00016008444,0.00002205866,0.000001277137,0.000007023608,0.0009861881],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9971857,0.0002637367,0.000644427,0.00038084944,0.0013038927,0.00022141512],"domain_scores_gemma":[0.99406695,0.0038807567,0.00046212904,0.00056882,0.0009001157,0.00012122343],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.018787047,0.00012431358,0.00018504058,0.0005024924,0.000729977,0.0008945286,0.0035328364,0.00003812745,0.00015428763],"category_scores_gemma":[0.0026673302,0.00006680802,0.00010996167,0.00038685414,0.0010561896,0.0011405926,0.00016487237,0.00019519475,0.000042858148],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046042344,0.00008539324,0.0004947247,5.5420594e-7,0.0000062660224,0.000001347347,0.0025693679,0.0002569816,0.00046674884,0.6608976,0.000487165,0.3342734],"study_design_scores_gemma":[0.0003701387,0.00023322932,0.0019965766,0.000031623254,0.0000065362306,0.00006152477,0.0030594154,0.0005013752,0.000017187756,0.87938035,0.11425006,0.00009196582],"about_ca_topic_score_codex":0.0000064371275,"about_ca_topic_score_gemma":0.000044632125,"teacher_disagreement_score":0.33418143,"about_ca_system_score_codex":0.00031156055,"about_ca_system_score_gemma":0.0003187033,"threshold_uncertainty_score":0.862596},"labels":[],"label_agreement":null},{"id":"W2996621779","doi":"10.1037/npe0000111","title":"Cognitive reflection but not reinforcement sensitivity is consistently associated with delay discounting of gains and losses.","year":2019,"lang":"en","type":"article","venue":"Journal of Neuroscience Psychology and Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Narodowym Centrum Nauki","keywords":"Delay discounting; Reinforcement; Psychology; Discounting; Cognitive psychology; Cognition; Neuroeconomics; Sensitivity (control systems); Reflection (computer programming); Reinforcement learning; Impulsivity; Developmental psychology; Social psychology; Economics; Neuroscience; Computer science; Artificial intelligence","score_opus":0.16383479029538267,"score_gpt":0.41693965954045126,"score_spread":0.2531048692450686,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2996621779","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.997312,0.000017933598,0.00073705835,0.00053440453,0.00070667005,0.00008634924,0.000019535337,0.0000028472195,0.0005831666],"genre_scores_gemma":[0.997618,0.0001788204,0.00010472439,0.0019518933,0.000020224405,3.6793338e-7,3.1774937e-7,0.0000059630056,0.000119671844],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983184,0.00010558584,0.00081009266,0.00037947536,0.00019674053,0.00018971621],"domain_scores_gemma":[0.99708104,0.0008917702,0.0014679093,0.00017628801,0.0002842956,0.00009871884],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027312299,0.00012398965,0.00042990074,0.00027009659,0.00013464582,0.0001519,0.00016698218,0.0000886075,0.000016764754],"category_scores_gemma":[0.00085629744,0.000091822294,0.000071662536,0.00018112728,0.00047586765,0.000679269,0.00007295776,0.0002447929,0.000005803098],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0030207299,0.0006166721,0.74290276,0.000014807932,0.00011198411,0.00018732768,0.0023240268,0.0044334815,0.07191224,0.00049864006,0.000491229,0.17348614],"study_design_scores_gemma":[0.004411331,0.0043500746,0.95124626,0.00023674221,0.00014878309,0.0035112891,0.0026121906,0.020422015,0.003701186,0.0077117407,0.0010690296,0.00057933386],"about_ca_topic_score_codex":0.000006360667,"about_ca_topic_score_gemma":0.000024257884,"teacher_disagreement_score":0.20834355,"about_ca_system_score_codex":0.000027865588,"about_ca_system_score_gemma":0.00008461937,"threshold_uncertainty_score":0.37444046},"labels":[],"label_agreement":null},{"id":"W2998901437","doi":"10.1037/xge0000735","title":"Choice protection for feeling-focused decisions.","year":2020,"lang":"en","type":"article","venue":"Journal of Experimental Psychology General","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Deliberation; Feeling; PsycINFO; Psychology; Relevance (law); Social psychology; Function (biology); Political science; MEDLINE; Politics; Law","score_opus":0.38881830464056044,"score_gpt":0.4996347150892675,"score_spread":0.11081641044870705,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2998901437","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9664107,0.00045686789,0.024761967,0.0048986957,0.0027503616,0.00025659404,0.000009984108,0.000016130041,0.00043872095],"genre_scores_gemma":[0.97319794,0.000010568831,0.021710005,0.003575399,0.0013532633,0.000014043579,0.0000011723452,0.000022982878,0.000114606875],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9971019,0.00018185661,0.0014206948,0.0004532763,0.0005856158,0.0002566323],"domain_scores_gemma":[0.99752575,0.00056524837,0.00091598375,0.00032287659,0.00037460832,0.00029552414],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016466234,0.00018480599,0.00049773516,0.00026782727,0.00020045623,0.00017892226,0.000900924,0.00016684349,0.00036705972],"category_scores_gemma":[0.0026455158,0.00013647058,0.00043421765,0.00034598535,0.00009123553,0.00039118208,0.000084524305,0.00034124282,0.00015137342],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002172576,0.00059558847,0.0018108471,9.989134e-7,0.00005525537,0.000037010945,0.00094727887,0.00070792413,0.3996009,0.00012045434,0.12092012,0.47303107],"study_design_scores_gemma":[0.01749511,0.013956198,0.008354234,0.00007626868,0.00010743596,0.0011798688,0.002220368,0.010502133,0.14616793,0.054118186,0.7446114,0.0012108864],"about_ca_topic_score_codex":0.0000032270527,"about_ca_topic_score_gemma":0.000001666723,"teacher_disagreement_score":0.62369126,"about_ca_system_score_codex":0.00006348792,"about_ca_system_score_gemma":0.000066086366,"threshold_uncertainty_score":0.55651087},"labels":[],"label_agreement":null},{"id":"W2999977105","doi":"10.3758/s13421-019-00992-8","title":"Concreteness and disagreement: Comment on Pollock (2018)","year":2020,"lang":"en","type":"letter","venue":"Memory & Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Concreteness; Psychology; Word (group theory); Cognitive psychology; Memory test; Linguistics; Cognition; Philosophy","score_opus":0.1887207672372673,"score_gpt":0.36590007622552084,"score_spread":0.17717930898825354,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2999977105","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04605827,0.000092364964,0.00021337862,0.93749005,0.0021710724,0.00060612115,0.0006924923,0.00010686924,0.012569403],"genre_scores_gemma":[0.16554503,0.00003474111,0.00010324427,0.83103716,0.0015312553,0.00003874035,0.0004502159,0.00004690214,0.0012127033],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9958524,0.0003169846,0.00091361644,0.00115837,0.0013869775,0.0003716287],"domain_scores_gemma":[0.99688745,0.0014770057,0.00055869174,0.00071696844,0.00020504506,0.00015487027],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0008218712,0.0004325317,0.00071529066,0.00032918432,0.00028958754,0.0006960352,0.000651365,0.00043403314,0.0011735365],"category_scores_gemma":[0.0006507752,0.00034892332,0.00021687962,0.0002604652,0.00019515184,0.0002146185,0.00027392042,0.0010130383,0.003026021],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000045962082,0.00001871153,0.000028715558,0.000010833604,0.000017413275,0.00021832243,0.00007700138,0.0000016340967,0.000022654329,0.0000066617526,0.83204997,0.16750212],"study_design_scores_gemma":[0.00064660946,0.00029967417,0.0001591805,0.00017001259,0.00013086943,0.000025067417,0.0002679619,0.000104944804,0.00020201367,0.025476659,0.9720244,0.00049264607],"about_ca_topic_score_codex":0.000024611603,"about_ca_topic_score_gemma":0.00000492256,"teacher_disagreement_score":0.16700949,"about_ca_system_score_codex":0.00010101001,"about_ca_system_score_gemma":0.00006241227,"threshold_uncertainty_score":0.9998963},"labels":[],"label_agreement":null},{"id":"W3000569177","doi":"10.3917/reco.706.1095","title":"Holt and Laury measures and insurance decisions: A same risk attitude?","year":2019,"lang":"fr","type":"article","venue":"Revue économique","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Center for Interuniversity Research and Analysis on Organizations","funders":"","keywords":"Humanities; Mathematics; Philosophy","score_opus":0.12318179305201335,"score_gpt":0.3339207375444069,"score_spread":0.21073894449239353,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3000569177","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9603396,0.031194918,0.00046512292,0.0027342406,0.0027012522,0.00058918836,0.00030595958,0.000044952503,0.0016247843],"genre_scores_gemma":[0.9588478,0.026082575,0.005188365,0.0006351649,0.0003165284,0.000022907294,0.0000030581048,0.000050934676,0.008852655],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99610794,0.0004264316,0.0012647668,0.0014513736,0.0002014607,0.00054801867],"domain_scores_gemma":[0.99239683,0.005006234,0.0006623412,0.0012397491,0.0002391221,0.00045570167],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0035818026,0.00045980385,0.0010647195,0.00036524478,0.0002777162,0.0009939957,0.0007214738,0.000524149,0.0005363494],"category_scores_gemma":[0.0033800926,0.0004318242,0.00023022592,0.00034762087,0.00045028146,0.0010703837,0.00052060233,0.0006346482,0.0023299393],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000074877426,0.00007525366,0.2778134,0.000020625168,0.000027943237,0.000022836362,0.00029870143,0.00023884272,0.00005613134,0.0023231334,0.0010518011,0.7179964],"study_design_scores_gemma":[0.0015917096,0.00041011826,0.29881668,0.0013405426,0.00009745385,0.00045774598,0.00048015596,0.004265569,0.00006348023,0.236012,0.4554529,0.0010116587],"about_ca_topic_score_codex":0.0007995515,"about_ca_topic_score_gemma":0.00127039,"teacher_disagreement_score":0.7169848,"about_ca_system_score_codex":0.00016459738,"about_ca_system_score_gemma":0.0002409527,"threshold_uncertainty_score":0.9998134},"labels":[],"label_agreement":null},{"id":"W3002706339","doi":"10.1177/0022243719889336","title":"Inaction Traps in Consumer Response to Product Malfunctions","year":2020,"lang":"en","type":"article","venue":"Journal of Marketing Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Product (mathematics); Consumption (sociology); Phenomenon; Vulnerability (computing); Action (physics); Psychological intervention; Trap (plumbing); Business; Downstream (manufacturing); Risk analysis (engineering); Marketing; Economics; Psychology; Social psychology; Microeconomics; Computer science; Computer security; Sociology; Engineering","score_opus":0.46715446509705577,"score_gpt":0.5296060164812807,"score_spread":0.062451551384224924,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3002706339","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9681582,0.000084746775,0.000141946,0.029713491,0.00041454472,0.00015860352,0.0000032833943,0.0000070192627,0.0013181684],"genre_scores_gemma":[0.9978635,0.000026765947,0.001020272,0.0002560129,0.00024005724,0.0000033832735,1.1996912e-7,0.000012336636,0.00057760807],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99122405,0.0046140556,0.0012319941,0.0003948172,0.0021174282,0.00041764078],"domain_scores_gemma":[0.9817017,0.01563108,0.00033402626,0.00036456596,0.0015843727,0.00038426806],"candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.10734973,0.00009428164,0.00032110472,0.0014185258,0.00017682371,0.00038696593,0.0007919965,0.00006187335,0.00061919674],"category_scores_gemma":[0.17303196,0.00007144219,0.00012593405,0.0023707796,0.00008585529,0.00037766786,0.00019814484,0.0010478039,0.0004324841],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.029221652,0.00018125579,0.04485087,0.0000065185377,0.000011588745,0.00021057855,0.0008766074,0.0003558691,0.014513001,0.000012221453,0.12565656,0.7841033],"study_design_scores_gemma":[0.0011857435,0.0011897862,0.35437012,0.00023370988,0.000010228956,0.00015998642,0.012240489,0.0006560484,0.0006504098,0.0047931927,0.62426203,0.0002482209],"about_ca_topic_score_codex":0.000021297523,"about_ca_topic_score_gemma":0.000028447246,"teacher_disagreement_score":0.7838551,"about_ca_system_score_codex":0.0004111118,"about_ca_system_score_gemma":0.00047458088,"threshold_uncertainty_score":0.9191713},"labels":[],"label_agreement":null},{"id":"W3002990142","doi":"10.1007/s11747-019-00717-y","title":"How and when weather boosts consumer product valuation","year":2020,"lang":"en","type":"article","venue":"Journal of the Academy of Marketing Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Valuation (finance); Snow; Product (mathematics); Business; Marketing; Rain and snow mixed; Environmental science; Meteorology; Geography; Mathematics","score_opus":0.17974607830450076,"score_gpt":0.382949906566836,"score_spread":0.2032038282623352,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3002990142","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94236326,0.00039947737,0.0001360411,0.056456234,0.0002748779,0.00008647803,0.0000016858125,0.0000035591008,0.00027840116],"genre_scores_gemma":[0.99496204,0.000032896805,0.0039229323,0.0007069808,0.00012322632,2.7361605e-7,7.171183e-9,0.00000481635,0.0002468014],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9965307,0.000460095,0.00070979533,0.00031026106,0.0018122732,0.0001768917],"domain_scores_gemma":[0.99593616,0.0017503259,0.0015722481,0.00019390412,0.00039224507,0.00015513173],"candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.030853197,0.000094565556,0.0002727704,0.00017418349,0.00022264052,0.0003951614,0.0018693098,0.000043756558,0.00003580698],"category_scores_gemma":[0.04537048,0.000051336927,0.00011149052,0.00064777007,0.00068743323,0.0009505236,0.00038244305,0.00032979978,0.0000056785225],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028807405,0.000031975313,0.064082205,0.000008433385,0.000010924389,0.0000015398831,0.0014020317,0.00012558383,0.06264418,0.00008794472,0.012942595,0.8583745],"study_design_scores_gemma":[0.0012421402,0.00025832574,0.78013486,0.0005130504,0.00014156851,0.00036372588,0.002217629,0.007615279,0.037026033,0.10019151,0.06981624,0.00047964044],"about_ca_topic_score_codex":8.897055e-7,"about_ca_topic_score_gemma":1.7130124e-7,"teacher_disagreement_score":0.85789484,"about_ca_system_score_codex":0.00003158961,"about_ca_system_score_gemma":0.00016590637,"threshold_uncertainty_score":0.9979406},"labels":[],"label_agreement":null},{"id":"W3004966899","doi":"10.1007/s11109-020-09594-6","title":"Politicians, the Representativeness Heuristic and Decision-Making Biases","year":2020,"lang":"en","type":"article","venue":"Political Behavior","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Institute of Population and Public Health; Nederlandse Organisatie voor Wetenschappelijk Onderzoek","keywords":"Representativeness heuristic; Heuristics; Heuristic; Neglect; Scope (computer science); Psychology; Sample (material); Satisficing; Cognitive psychology; Computer science; Conjunction (astronomy); Social psychology; Artificial intelligence","score_opus":0.26202033913744394,"score_gpt":0.47144519947287805,"score_spread":0.20942486033543412,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3004966899","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98883665,0.00013373999,0.0028809651,0.0059019937,0.0004163856,0.00029315992,0.00015152583,0.000079199555,0.0013063671],"genre_scores_gemma":[0.99337554,0.0000041488224,0.0015729038,0.0046062027,0.00033364035,0.000039114126,0.0000026100568,0.000028545106,0.000037310296],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99610215,0.00024032184,0.0009768558,0.00089418225,0.0010446702,0.00074183504],"domain_scores_gemma":[0.9859325,0.012188541,0.00017239446,0.00078769535,0.00024918222,0.00066968007],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.00097234803,0.0002675758,0.00048901956,0.00013694742,0.00040104854,0.00077122165,0.0010394746,0.00011701962,0.00074063445],"category_scores_gemma":[0.015978448,0.00016650208,0.00019771667,0.00049741333,0.00062883075,0.00029213337,0.0005706849,0.00033150113,0.00067726715],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012395465,0.00021545833,0.11481237,0.000005062325,0.000011640218,0.00031740745,0.00060689973,0.00002197034,0.00012746024,0.08017159,0.0033807128,0.80020547],"study_design_scores_gemma":[0.0007929969,0.00034210578,0.35937825,0.00015379908,0.00028572598,0.00024468446,0.0065844236,0.002659847,0.00033128698,0.6175698,0.010840793,0.00081630313],"about_ca_topic_score_codex":0.00009306984,"about_ca_topic_score_gemma":0.00001137752,"teacher_disagreement_score":0.7993892,"about_ca_system_score_codex":0.000060732516,"about_ca_system_score_gemma":0.00010196906,"threshold_uncertainty_score":0.9923104},"labels":[],"label_agreement":null},{"id":"W3005615619","doi":"10.3758/s13423-020-01710-1","title":"The environmental malleability of base-rate neglect","year":2020,"lang":"en","type":"article","venue":"Psychonomic Bulletin & Review","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Psychology; Malleability; Neglect; Social psychology; Cognitive psychology; Base (topology); Computer science; Computer security","score_opus":0.13328186434606845,"score_gpt":0.36730057399042587,"score_spread":0.23401870964435742,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3005615619","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7325,0.1061794,0.00038297413,0.15005927,0.001510442,0.0015851972,0.00013360275,0.000071286886,0.0075778165],"genre_scores_gemma":[0.9158992,0.06836056,0.0012817478,0.013454757,0.00020137735,0.000054387583,0.000006254934,0.00003897467,0.00070273376],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9966786,0.00049949373,0.001503537,0.00070107647,0.00036265026,0.00025467345],"domain_scores_gemma":[0.9962415,0.0017539246,0.0006447929,0.0011355295,0.00003791923,0.00018633256],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0039061322,0.00020648242,0.0006282793,0.000027635115,0.00016240175,0.00011551997,0.0014382909,0.000056423007,0.008017483],"category_scores_gemma":[0.0016276507,0.00012615602,0.00041902286,0.00020187999,0.00023415998,0.000054814216,0.00020647903,0.00020855128,0.008624659],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000052465195,0.000055900164,0.0009055853,0.000036963633,0.000010065027,0.0000013590134,0.000035708796,0.000010696361,0.00017265946,0.000046170982,0.20901404,0.78965837],"study_design_scores_gemma":[0.00019059193,0.0000840723,0.002500631,0.000164853,0.000027672484,0.000004331835,0.000056851964,0.00008266162,0.00003751964,0.0019782078,0.9947243,0.00014831929],"about_ca_topic_score_codex":0.000007310153,"about_ca_topic_score_gemma":0.0000022959898,"teacher_disagreement_score":0.7895101,"about_ca_system_score_codex":0.000047831178,"about_ca_system_score_gemma":0.000039073762,"threshold_uncertainty_score":0.99288934},"labels":[],"label_agreement":null},{"id":"W3006494287","doi":"10.5964/ejop.v16i2.1958","title":"Influences of complexity on decision making in young and older adults","year":2020,"lang":"en","type":"article","venue":"Europe’s Journal of Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Trent University; Nottingham Trent University","keywords":"Psychology; Medical decision making; Clinical decision making; Social psychology; Gerontology; Medicine; Family medicine","score_opus":0.2053550059401138,"score_gpt":0.4640934967058229,"score_spread":0.2587384907657091,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3006494287","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99508786,0.00018587755,0.0010932934,0.001253868,0.0006144054,0.000061007115,0.000005595305,0.0000041716953,0.0016939399],"genre_scores_gemma":[0.9942952,0.00006302037,0.0043262546,0.0012109886,0.00008952954,2.3208943e-7,1.2018259e-7,0.000009712789,0.000004942615],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99716437,0.00029360302,0.0014622919,0.00035378063,0.0005566439,0.00016933757],"domain_scores_gemma":[0.99733853,0.0009544459,0.0009870138,0.00025395644,0.0003429843,0.00012303883],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019801662,0.00013073202,0.0005114037,0.00043120244,0.00004226926,0.000073912925,0.00078727305,0.00007496585,0.00026777288],"category_scores_gemma":[0.0022041597,0.0000918699,0.00009648095,0.0005923703,0.00020471106,0.00024346205,0.00012604287,0.0003662377,0.000074021096],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017999423,0.00017507342,0.17207402,0.0000034529353,0.000008115132,0.00020974055,0.0019376957,0.00017393254,0.00031452032,0.00020548922,0.0028800124,0.820218],"study_design_scores_gemma":[0.001643108,0.00086338713,0.9741149,0.00029397526,0.000008220533,0.00026363175,0.00036030755,0.0002555631,0.000034587272,0.020004746,0.002036641,0.000120939425],"about_ca_topic_score_codex":0.00000456374,"about_ca_topic_score_gemma":0.00002527443,"teacher_disagreement_score":0.8200971,"about_ca_system_score_codex":0.000011576873,"about_ca_system_score_gemma":0.000031261323,"threshold_uncertainty_score":0.3746346},"labels":[],"label_agreement":null},{"id":"W3008359594","doi":"10.1111/risa.13443","title":"Improving Probability Judgment in Intelligence Analysis: From Structured Analysis to Statistical Aggregation","year":2020,"lang":"en","type":"article","venue":"Risk Analysis","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Bayes' theorem; Intelligence analysis; Computer science; Contrast (vision); Range (aeronautics); Coherence (philosophical gambling strategy); Value (mathematics); Machine learning; Econometrics; Artificial intelligence; Statistics; Bayesian probability; Psychology; Mathematics; Engineering","score_opus":0.09332863880444729,"score_gpt":0.37436152319975663,"score_spread":0.2810328843953093,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3008359594","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5524021,0.00003091493,0.44669104,0.0002580909,0.00003300343,0.00012715365,0.00041584208,0.000025424008,0.000016440092],"genre_scores_gemma":[0.96128696,0.00001068468,0.038247433,0.00021088621,0.000045308996,0.000017563416,0.00015684623,0.000009382519,0.000014928879],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9936611,0.00063167495,0.0020414966,0.0018483216,0.0014281477,0.00038927392],"domain_scores_gemma":[0.995312,0.001699645,0.00078137516,0.0013452697,0.00036203157,0.0004997049],"candidate_categories":["metaepi_narrow","bibliometrics","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0027987112,0.00030696383,0.0015717839,0.002971139,0.00016095255,0.0006650012,0.0011198544,0.00014728915,0.0038765224],"category_scores_gemma":[0.0062456494,0.00024692263,0.0011755102,0.030021247,0.0000790731,0.00029079837,0.00031273338,0.00031988538,0.00041833427],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000052751402,0.000044721055,0.3972968,5.181496e-7,0.0021768245,0.000006678645,0.00070776534,0.3289199,0.000025984653,0.000018490851,0.000029458497,0.27072012],"study_design_scores_gemma":[0.000081730475,0.00004026986,0.35935706,0.0000015354132,0.018124012,4.25076e-8,0.00069716416,0.6006341,0.00016794297,0.020585196,0.000055884415,0.0002550714],"about_ca_topic_score_codex":0.006054874,"about_ca_topic_score_gemma":0.03330267,"teacher_disagreement_score":0.40888488,"about_ca_system_score_codex":0.00025628493,"about_ca_system_score_gemma":0.00007909132,"threshold_uncertainty_score":0.99999833},"labels":[],"label_agreement":null},{"id":"W3008917289","doi":"10.3758/s13421-020-01027-3","title":"Reasoning strategies and semantic memory effects in deductive reasoning","year":2020,"lang":"en","type":"article","venue":"Memory & Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Psychology; Probabilistic logic; Deductive reasoning; Cognitive psychology; Counterexample; Logical reasoning; Statement (logic); Dual (grammatical number); Inductive reasoning; Relation (database); Verbal reasoning; Cognition; Artificial intelligence; Computer science; Linguistics; Mathematics","score_opus":0.0803756863639596,"score_gpt":0.3550247915525798,"score_spread":0.27464910518862024,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3008917289","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9898373,0.00024144871,0.001549258,0.00040379402,0.0002734831,0.00027303936,0.00000537163,0.000072015864,0.007344293],"genre_scores_gemma":[0.99784523,0.000015131666,0.0015051374,0.00041331237,0.0001298428,0.000018821518,0.000007748854,0.000018489542,0.000046254772],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.997783,0.00026509847,0.00051103916,0.000697598,0.00047353999,0.00026971367],"domain_scores_gemma":[0.9982328,0.0009981206,0.00022541433,0.0002305852,0.00015353556,0.00015954535],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012916412,0.00019675627,0.0003873763,0.00023856504,0.0001676843,0.00063405687,0.00024539704,0.00010600722,0.0001113435],"category_scores_gemma":[0.003033852,0.00017524765,0.000074047515,0.0005534437,0.00012150551,0.0011721394,0.0001332485,0.00027455442,0.000263528],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025910392,0.000108892105,0.003187882,0.000046340636,0.000019309398,0.00030880814,0.006472307,0.00078341796,0.008271392,0.000619105,0.0005938559,0.9793296],"study_design_scores_gemma":[0.007910991,0.0016623276,0.2603692,0.0025905368,0.00043637623,0.00042903403,0.1703127,0.059871923,0.026504856,0.46604386,0.0010435467,0.002824611],"about_ca_topic_score_codex":0.000047549634,"about_ca_topic_score_gemma":0.000066976005,"teacher_disagreement_score":0.976505,"about_ca_system_score_codex":0.000040759372,"about_ca_system_score_gemma":0.00009530182,"threshold_uncertainty_score":0.7146392},"labels":[],"label_agreement":null},{"id":"W3010781033","doi":"10.1016/j.jet.2020.105027","title":"Bayes and Hurwicz without Bernoulli","year":2020,"lang":"en","type":"article","venue":"Journal of Economic Theory","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Deutsche Forschungsgemeinschaft; Université Grenoble Alpes","keywords":"Ambiguity; Bernoulli's principle; Expected utility hypothesis; Certainty; Bayes' theorem; Subjective expected utility; Mathematical economics; Decision theory; Decision maker; Ambiguity aversion; Ranking (information retrieval); Mathematics; Computer science; Bayesian inference; Bayesian probability; Econometrics; Artificial intelligence; Operations research; Statistics","score_opus":0.14432492021204477,"score_gpt":0.3975724710055006,"score_spread":0.25324755079345584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3010781033","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99190813,0.0003852079,0.001181062,0.002166764,0.00069211354,0.00004201263,0.000011327123,0.000008409297,0.0036049918],"genre_scores_gemma":[0.99705136,0.00006145158,0.0012058736,0.0008854302,0.00043925332,3.2568283e-7,1.6428882e-7,0.000013317567,0.00034285468],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99821657,0.00014717648,0.0010503671,0.00025492292,0.00018383183,0.00014710307],"domain_scores_gemma":[0.99731976,0.0012204505,0.00087031524,0.00022685855,0.00008675648,0.00027585326],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0035013824,0.00012557498,0.00048790325,0.00015956802,0.00007591366,0.00030473992,0.0006417906,0.00006872035,0.0013788784],"category_scores_gemma":[0.0011598151,0.000089586865,0.00018359307,0.00006173856,0.00012595451,0.0005402743,0.00013361686,0.00021719626,0.0005168104],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00050228904,0.000047588754,0.03773625,0.0000032227044,0.00006703142,0.000050114093,0.0017582106,0.00076092593,0.0004477453,0.014322771,0.015710222,0.92859364],"study_design_scores_gemma":[0.0010587597,0.000422111,0.0052723032,0.00003196178,0.00005787162,0.00032074275,0.0025297499,0.0012042158,0.00037523196,0.88304955,0.10539557,0.0002819528],"about_ca_topic_score_codex":0.0000018037077,"about_ca_topic_score_gemma":0.0000034488219,"teacher_disagreement_score":0.9283117,"about_ca_system_score_codex":0.000047176232,"about_ca_system_score_gemma":0.00011407086,"threshold_uncertainty_score":0.999534},"labels":[],"label_agreement":null},{"id":"W3013191290","doi":"","title":"Rationality, intelligence, and the defining features of Type 1 and Type 2 processing.","year":2014,"lang":"en","type":"article","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":33,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University; University of Toronto","funders":"","keywords":"Rationality; Computer science; Type (biology); Artificial intelligence; Epistemology; Cognitive science; Psychology; Philosophy","score_opus":0.1250586006194288,"score_gpt":0.4034161849257864,"score_spread":0.2783575843063576,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3013191290","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9665073,0.00068467465,0.0022282747,0.0010006672,0.00020741005,0.000071494265,0.000001524396,0.000013285677,0.029285327],"genre_scores_gemma":[0.99638605,0.0000275873,0.002404388,0.0002633372,0.000018738989,6.692526e-7,6.775122e-7,0.0000030297917,0.00089553854],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99911064,0.00007274303,0.00029819398,0.00019377489,0.00025669415,0.00006798413],"domain_scores_gemma":[0.99788904,0.0014292962,0.0001314205,0.00018894438,0.00032845416,0.000032864336],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022564544,0.000060308903,0.00016754729,0.000064812295,0.00010533447,0.00022926195,0.00021340627,0.000038947568,0.000107293294],"category_scores_gemma":[0.003033267,0.00002959541,0.000017465434,0.00030454205,0.00027162145,0.000120946126,0.000121243946,0.00006249709,0.00003183233],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006476457,0.000009044268,0.006197128,0.0000016641437,0.0000018095019,1.0656871e-7,0.00024824138,0.000034729295,0.000011623209,0.057334777,0.0016117624,0.93448436],"study_design_scores_gemma":[0.00033786037,0.00014008846,0.03565765,0.000029683468,0.000020639018,0.000026483458,0.001002103,0.011415837,0.00025997427,0.9293765,0.021577748,0.00015543739],"about_ca_topic_score_codex":0.00002775025,"about_ca_topic_score_gemma":0.000043194534,"teacher_disagreement_score":0.9343289,"about_ca_system_score_codex":0.0000027612691,"about_ca_system_score_gemma":0.000037984646,"threshold_uncertainty_score":0.36313233},"labels":[],"label_agreement":null},{"id":"W3014392388","doi":"10.5539/ijef.v12n4p95","title":"A Risk-Neutral Consumer and His Coherent Decisions Under Uncertainty: A Methodological Analysis","year":2020,"lang":"en","type":"article","venue":"International Journal of Economics and Finance","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Expected utility hypothesis; Coherence (philosophical gambling strategy); Subjective expected utility; Univariate; Consumption (sociology); Econometrics; Function (biology); Space (punctuation); Computer science; Mathematical economics; Economics; Mathematical optimization; Mathematics; Multivariate statistics; Statistics","score_opus":0.29934730982684754,"score_gpt":0.4274971682218672,"score_spread":0.12814985839501963,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3014392388","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98549813,0.00054552313,0.0076400987,0.005608873,0.0004551215,0.000042423508,0.00010457659,0.0000028541785,0.00010242642],"genre_scores_gemma":[0.9839485,0.0059664887,0.008823372,0.0010971487,0.00012421432,0.0000011798028,0.0000016577482,0.0000058251017,0.000031610125],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9981179,0.00012799165,0.0010721493,0.0003625356,0.00018848466,0.00013088624],"domain_scores_gemma":[0.9956448,0.0025737735,0.0010908213,0.00015154229,0.00038794155,0.00015108369],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001775744,0.00013709273,0.000569787,0.00030471414,0.00008140758,0.00039452652,0.0006141927,0.000084128245,0.00009963293],"category_scores_gemma":[0.0020348672,0.000100600686,0.00028496882,0.00020007382,0.00015489126,0.0002869228,0.00019925044,0.0002395936,0.000016827653],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00077287346,0.00010472173,0.026648048,4.4429112e-7,0.00072603073,0.000062720464,0.00048756,0.21951477,0.000019036372,0.0118140215,0.0018389877,0.73801076],"study_design_scores_gemma":[0.0022146788,0.0004794225,0.092381336,0.00003071808,0.0005052473,0.00025372853,0.0008568991,0.2434168,0.00005664957,0.52559406,0.13374096,0.000469488],"about_ca_topic_score_codex":0.00003815112,"about_ca_topic_score_gemma":0.00009272314,"teacher_disagreement_score":0.7375413,"about_ca_system_score_codex":0.000053186937,"about_ca_system_score_gemma":0.00007765463,"threshold_uncertainty_score":0.41023767},"labels":[],"label_agreement":null},{"id":"W3014622127","doi":"10.1002/bdm.2179","title":"How representations of number and numeracy predict decision paradoxes: A fuzzy‐trace theory approach","year":2020,"lang":"en","type":"article","venue":"Journal of Behavioral Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Nursing Research; Savoy Foundation; National Science Foundation","keywords":"Numeracy; Categorical variable; GiST; Psychology; Mathematics; Cognitive psychology; Ordinal data; Statistics; Social psychology","score_opus":0.12275054784696351,"score_gpt":0.420808850625137,"score_spread":0.29805830277817347,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3014622127","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8462578,0.000476932,0.15146464,0.00039569117,0.00067051424,0.0002523848,0.00004551532,0.000024221446,0.00041228827],"genre_scores_gemma":[0.87194365,0.00007368594,0.12750402,0.0001288514,0.00023030337,0.000004226952,0.000001275603,0.000042621537,0.00007134656],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99220175,0.00046703516,0.0030563218,0.0008584545,0.0030018303,0.00041463872],"domain_scores_gemma":[0.98835933,0.0058940253,0.0029883222,0.0008938156,0.0013472985,0.0005172163],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.005031053,0.00041546536,0.0013043494,0.00066076167,0.00028711738,0.0011617173,0.0016544616,0.0002836691,0.00031810396],"category_scores_gemma":[0.0069204047,0.00030128373,0.0006986399,0.0013871092,0.0002864915,0.0021504748,0.0005614263,0.00075572194,0.000049248865],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012968853,0.00039613215,0.03570601,0.0000072599796,0.000025733445,0.0001442573,0.0017621039,0.0010061284,0.0007746186,0.0004543057,0.004359371,0.9540672],"study_design_scores_gemma":[0.0072915377,0.0025460506,0.094425306,0.001579921,0.0010369993,0.0034860922,0.034639973,0.011537939,0.001003771,0.82699746,0.013688278,0.0017666505],"about_ca_topic_score_codex":0.0000050491344,"about_ca_topic_score_gemma":0.0000029963815,"teacher_disagreement_score":0.95230055,"about_ca_system_score_codex":0.00007747873,"about_ca_system_score_gemma":0.0001845189,"threshold_uncertainty_score":0.9999439},"labels":[],"label_agreement":null},{"id":"W3016133661","doi":"","title":"Testing the Effect of Incentives on Effort Intensity Using Real-Effort Tasks","year":2018,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Task (project management); Incentive; Computer science; Test (biology); Cognitive psychology; Psychology; Human–computer interaction; Engineering; Microeconomics; Economics","score_opus":0.08534902525797174,"score_gpt":0.3868727462288363,"score_spread":0.30152372097086455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3016133661","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9961737,0.000083081155,0.0012024825,0.00009391172,0.00072707713,0.00015004085,0.000002293571,0.000017623326,0.0015498232],"genre_scores_gemma":[0.99920624,0.000039351708,0.00018953867,0.0000507778,0.00038847007,0.0000011000747,3.938373e-7,0.000017516035,0.000106599015],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9965301,0.00019634565,0.00080436456,0.00036824206,0.0008256679,0.0012752737],"domain_scores_gemma":[0.9967009,0.0013643824,0.0007841308,0.0005558732,0.0005087011,0.000086046224],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.014101897,0.00020583278,0.00045337164,0.00024854866,0.0006301889,0.0002115738,0.0010127922,0.00009250634,0.00003529347],"category_scores_gemma":[0.0022969386,0.00011024109,0.00023283994,0.00061194703,0.0003336962,0.00026362424,0.00018320917,0.0011982665,0.00009344514],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00053332566,0.00005262881,0.18504551,0.0000015074921,0.00006390031,0.00000713502,0.0001961442,0.00020012926,0.0030952082,0.0013432453,0.00017979443,0.80928147],"study_design_scores_gemma":[0.00208516,0.0122088855,0.14687458,0.000363921,0.00026092274,0.00208807,0.003054837,0.010591171,0.014439107,0.8057643,0.0015195904,0.0007494383],"about_ca_topic_score_codex":0.00018790472,"about_ca_topic_score_gemma":0.00018666264,"teacher_disagreement_score":0.80853206,"about_ca_system_score_codex":0.0005401672,"about_ca_system_score_gemma":0.00073882984,"threshold_uncertainty_score":0.5205938},"labels":[],"label_agreement":null},{"id":"W3016939514","doi":"10.1002/jcpy.1169","title":"Impatience and Savoring vs. Dread: Asymmetries in Anticipation Explain Consumer Time Preferences for Positive vs. Negative Events","year":2020,"lang":"en","type":"article","venue":"Journal of Consumer Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":68,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada; National Science Foundation","keywords":"Anticipation (artificial intelligence); Feeling; Psychology; Social psychology; Negative emotion; Negative information; Event (particle physics); Motivated reasoning","score_opus":0.16149951328275258,"score_gpt":0.4368891220080851,"score_spread":0.2753896087253325,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3016939514","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9937129,0.00031960136,0.0022169647,0.0027442304,0.0005159291,0.00024117436,0.000044899687,0.0000064433384,0.0001978372],"genre_scores_gemma":[0.9956611,0.00015179827,0.0031205243,0.0009744804,0.00005320716,0.0000068072723,0.0000016029261,0.000010331608,0.000020193753],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9972988,0.00031409916,0.0012967552,0.00040840427,0.00041674433,0.00026521098],"domain_scores_gemma":[0.9948174,0.0031861514,0.0011000369,0.00017477236,0.00053315714,0.00018852089],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018379283,0.00017826159,0.00067969685,0.00051420706,0.0000949942,0.0001219808,0.00048568967,0.00013252582,0.0001095007],"category_scores_gemma":[0.004603942,0.0001361559,0.00011456844,0.00048833847,0.00028448095,0.000645618,0.00007588211,0.00027789714,0.00006384708],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0029413272,0.00020579819,0.49300665,0.000006728134,0.00007563011,0.00003698448,0.0051346296,0.000040716805,0.0007807915,0.00010954323,0.0044930014,0.4931682],"study_design_scores_gemma":[0.0053621773,0.003519752,0.88444334,0.00022726385,0.00011967091,0.00019757322,0.0016275668,0.0011898241,0.0013640022,0.09581763,0.0056191874,0.0005120169],"about_ca_topic_score_codex":0.000014875396,"about_ca_topic_score_gemma":0.000020442823,"teacher_disagreement_score":0.49265617,"about_ca_system_score_codex":0.00003520944,"about_ca_system_score_gemma":0.00011471145,"threshold_uncertainty_score":0.55522764},"labels":[],"label_agreement":null},{"id":"W3017877307","doi":"10.1016/s2468-2667(20)30096-7","title":"Pitfalls of judgment during the COVID-19 pandemic","year":2020,"lang":"en","type":"review","venue":"The Lancet Public Health","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":37,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Health Sciences Centre; Sunnybrook Health Science Centre; Institute for Clinical Evaluative Sciences; University of Toronto","funders":"University of Toronto","keywords":"Isolation (microbiology); Social distance; Blame; Pandemic; Neglect; Coronavirus disease 2019 (COVID-19); Psychology; Social isolation; Coping (psychology); Mental health; Psychological resilience; Social psychology; Medicine; Disease; Psychiatry; Infectious disease (medical specialty)","score_opus":0.7439463160865961,"score_gpt":0.5579711582968446,"score_spread":0.1859751577897515,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3017877307","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005241925,0.9432525,0.00022967237,0.053129084,0.0007744456,0.0010210901,0.0003195676,0.00009821568,0.0006512343],"genre_scores_gemma":[0.0007268882,0.98958904,0.000088543165,0.008319339,0.000737295,0.00006763047,0.000016041771,0.00003592677,0.00041932613],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9921427,0.0023181906,0.002543604,0.00082118786,0.0013750391,0.00079931115],"domain_scores_gemma":[0.9890456,0.0051907883,0.002550786,0.0024653445,0.000121825644,0.00062561664],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.021508008,0.0003897296,0.003207024,0.00025470342,0.000536268,0.0005184568,0.0050333887,0.00019618668,0.00038880002],"category_scores_gemma":[0.0061725224,0.00016597481,0.0006316273,0.0013932846,0.0002655078,0.00015134209,0.0008290656,0.0009875637,0.00058068894],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000048660086,0.000025384797,0.0001230267,0.0007127605,0.000026719912,0.0000034770344,0.0004268287,0.0000046037285,2.6675009e-8,0.0005693464,0.031821363,0.9662816],"study_design_scores_gemma":[0.00018774525,0.000045998957,0.00004982812,0.00038387085,0.000031599713,0.00009994096,0.00016954151,0.000010939115,1.1832453e-8,0.0034928378,0.9953559,0.0001717921],"about_ca_topic_score_codex":0.00017710502,"about_ca_topic_score_gemma":0.00012385528,"teacher_disagreement_score":0.9661098,"about_ca_system_score_codex":0.000790701,"about_ca_system_score_gemma":0.0046079447,"threshold_uncertainty_score":0.93533725},"labels":[],"label_agreement":null},{"id":"W3021630820","doi":"10.1111/phpr.12669","title":"The Sequential Dominance Argument for the Independence Axiom of Expected Utility Theory","year":2020,"lang":"en","type":"article","venue":"Philosophy and Phenomenological Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Rationality; Axiom independence; Expected utility hypothesis; Lottery; Mathematical economics; Independence (probability theory); Axiom; Argument (complex analysis); Irrational number; Subjective expected utility; Economics; Mathematics; Philosophy; Epistemology; Microeconomics; Statistics","score_opus":0.6169989946602398,"score_gpt":0.5031804853143231,"score_spread":0.11381850934591664,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3021630820","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89980614,0.005408797,0.011210139,0.05252507,0.0004480139,0.0019744227,0.00016775189,0.00004803165,0.028411642],"genre_scores_gemma":[0.9990203,0.00023948602,0.00017799123,0.00020487003,0.00018497348,0.00008814418,9.78115e-7,0.0000059413933,0.000077355806],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99639934,0.00075637473,0.0006115013,0.0006038452,0.0012197063,0.00040921915],"domain_scores_gemma":[0.9809794,0.017572239,0.00016975804,0.00060568814,0.0005202804,0.00015267564],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.010777778,0.00012900069,0.00028740172,0.000059548212,0.0009886172,0.0002941214,0.0016980931,0.00011485214,0.00024754333],"category_scores_gemma":[0.0099957725,0.000056787823,0.00012414223,0.0005706222,0.0015811505,0.00011903514,0.00074919657,0.00053126056,0.000048635244],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017841703,0.0000990592,0.00039937714,0.000005883859,0.000022412287,0.0000035887517,0.0011034927,0.000016718835,0.0001664943,0.5009316,0.00041482403,0.49505234],"study_design_scores_gemma":[0.00031271114,0.00047895522,0.00075458176,0.0000062973677,0.0000062601816,0.0000013244669,0.0013188086,0.00093323266,0.000120401535,0.984975,0.011017655,0.00007477339],"about_ca_topic_score_codex":0.000008575463,"about_ca_topic_score_gemma":0.000003094357,"teacher_disagreement_score":0.49497756,"about_ca_system_score_codex":0.000025455747,"about_ca_system_score_gemma":0.00008622321,"threshold_uncertainty_score":0.99834347},"labels":[],"label_agreement":null},{"id":"W3021978697","doi":"10.3390/jrfm13050094","title":"The Investment Home Bias with Peer Effect","year":2020,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Bivariate analysis; Stochastic dominance; Economics; Econometrics; Stock (firearms); Diversification (marketing strategy); Financial economics; Microeconomics; Statistics; Mathematics; Business; Geography","score_opus":0.05968589283086834,"score_gpt":0.31166066427726685,"score_spread":0.2519747714463985,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3021978697","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9918398,0.00039213616,0.004279532,0.0020042418,0.0004524217,0.0001274127,0.00000465436,0.0000052818414,0.00089447416],"genre_scores_gemma":[0.99737704,0.00049905543,0.0010204763,0.000706129,0.00019531568,0.0000021458015,1.4982831e-7,0.000006552146,0.00019313862],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99810606,0.00011991625,0.0005551612,0.00018191875,0.0008895296,0.0001474203],"domain_scores_gemma":[0.99829906,0.0006571185,0.000534668,0.00018849922,0.00017503103,0.00014561722],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029403118,0.00011367866,0.00028021715,0.00010605179,0.00025252908,0.00040353806,0.00045207268,0.000030385965,0.000014189457],"category_scores_gemma":[0.0010795625,0.00005115841,0.000111530746,0.0003091899,0.00008207342,0.00016265805,0.00014929807,0.000198177,0.00004305008],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034710727,0.00002050849,0.01563459,0.0000022720487,0.000010772851,0.00010104668,0.0003414435,0.00013597413,8.280878e-7,0.0010811789,0.01631884,0.96600544],"study_design_scores_gemma":[0.0010107603,0.0012847264,0.090206735,0.000029795983,0.00009231416,0.000022810642,0.0005034972,0.00011993844,0.000014100575,0.033297792,0.8732968,0.00012070508],"about_ca_topic_score_codex":0.0000044919566,"about_ca_topic_score_gemma":0.000011472515,"teacher_disagreement_score":0.96588475,"about_ca_system_score_codex":0.0000223161,"about_ca_system_score_gemma":0.0000264994,"threshold_uncertainty_score":0.38913268},"labels":[],"label_agreement":null},{"id":"W3023839572","doi":"","title":"Analogy in Decision-Making","year":2009,"lang":"en","type":"article","venue":"Papyrus : Institutional Repository (Université de Montréal)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Analogy; Representation (politics); Analogical reasoning; Variety (cybernetics); Computer science; Context (archaeology); Decision problem; Artificial intelligence; Identification (biology); Management science; Theoretical computer science; Mathematics; Epistemology; Algorithm; Economics","score_opus":0.02269561806832284,"score_gpt":0.26658985585797135,"score_spread":0.2438942377896485,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3023839572","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9623377,0.0013745885,0.002148613,0.0005448665,0.000618157,0.00013014108,0.000011633974,0.000064727355,0.032769606],"genre_scores_gemma":[0.99466485,0.00003807937,0.0030365733,0.0004332582,0.000075386815,0.000002344344,0.0000031959698,0.000008405957,0.0017378867],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9969907,0.00013332286,0.00073639123,0.00074122864,0.0009719568,0.00042643907],"domain_scores_gemma":[0.99768573,0.00088715914,0.00029803856,0.00068938,0.00021453325,0.00022514502],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.001084835,0.00023537602,0.00040520448,0.000859277,0.0023117196,0.00017723048,0.0009800099,0.00020849865,0.00016060895],"category_scores_gemma":[0.0008137204,0.00022125294,0.00024701224,0.0009468583,0.00015844271,0.0006274473,0.0002384984,0.00027890573,0.00033190145],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00050513615,0.0002460987,0.06203323,0.0000010799508,0.00001382559,0.0032534008,0.0036547994,0.0100285355,0.001111373,0.010423168,0.0021386826,0.9065907],"study_design_scores_gemma":[0.0017131085,0.0002804986,0.59679335,0.00019889785,0.00004733601,0.0017912559,0.009485296,0.00961999,0.00045100905,0.3000824,0.07872591,0.00081097614],"about_ca_topic_score_codex":0.0013543345,"about_ca_topic_score_gemma":0.0025848309,"teacher_disagreement_score":0.9057797,"about_ca_system_score_codex":0.0025699087,"about_ca_system_score_gemma":0.0005447387,"threshold_uncertainty_score":0.99898714},"labels":[],"label_agreement":null},{"id":"W3026585542","doi":"10.1016/j.shpsa.2020.05.004","title":"Comparative infinite lottery logic","year":2020,"lang":"en","type":"article","venue":"Studies in History and Philosophy of Science Part A","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Lottery; Cardinality (data modeling); Mathematical economics; Independence (probability theory); Mathematics; Value (mathematics); Epistemology; Premise; Discrete mathematics; Computer science; Philosophy","score_opus":0.6226844429419854,"score_gpt":0.4611620035654826,"score_spread":0.16152243937650285,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3026585542","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9676322,0.004154371,0.000018354303,0.0018791426,0.0011228644,0.00010934039,0.000009265613,0.000013997146,0.025060484],"genre_scores_gemma":[0.99825996,0.000117452255,0.0003603542,0.0011294648,0.00009001255,0.0000054172756,1.7674559e-7,0.0000023783703,0.000034808156],"study_design_codex":"qualitative","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99795765,0.00006940098,0.0006218433,0.0005628367,0.0006000456,0.00018821713],"domain_scores_gemma":[0.99843055,0.00068398134,0.00026753836,0.00025182933,0.0002455338,0.00012055332],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0018254408,0.00012896968,0.0005240879,0.00029045026,0.00019920015,0.000024879593,0.0006500252,0.00003083957,0.00007021737],"category_scores_gemma":[0.0013358162,0.00009674954,0.000058419268,0.0007736844,0.006462395,0.0004592134,0.00034435673,0.00013546523,0.00007520087],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011236998,0.0009331195,0.10588849,0.00019135274,0.00010957268,0.00021523253,0.49210748,0.002492379,0.0060481257,0.12106469,0.13993773,0.12988812],"study_design_scores_gemma":[0.00060877757,0.0007278524,0.0035066956,0.00014419429,0.000017685477,0.000008559939,0.010782659,0.0008303649,0.000277985,0.86240834,0.1202198,0.0004670606],"about_ca_topic_score_codex":0.000003567158,"about_ca_topic_score_gemma":0.000005081216,"teacher_disagreement_score":0.7413437,"about_ca_system_score_codex":0.00010999416,"about_ca_system_score_gemma":0.00010810148,"threshold_uncertainty_score":0.99624145},"labels":[],"label_agreement":null},{"id":"W3036829954","doi":"10.1027/1864-9335/a000418","title":"Reducing the Halo Effect by Stimulating Analytic Thinking","year":2020,"lang":"en","type":"article","venue":"Social Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Psychology; Halo effect; Halo; Priming (agriculture); Task (project management); Social psychology; Interpersonal communication; Trait; Cognitive psychology","score_opus":0.18972567176674784,"score_gpt":0.48494810859023607,"score_spread":0.29522243682348825,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3036829954","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9637069,0.00007483063,0.0020448305,0.02460831,0.0010099177,0.00014548219,0.0000100434545,0.000070387156,0.0083292695],"genre_scores_gemma":[0.9928999,0.0000018177047,0.00021456297,0.006181075,0.00057261245,0.0000043546806,0.0000028092775,0.00001677918,0.0001060863],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9972788,0.0006622126,0.00060172676,0.00064240716,0.00050236663,0.00031245343],"domain_scores_gemma":[0.9967414,0.0024315023,0.000299995,0.0003655116,0.000072600684,0.00008897848],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0038122216,0.00015381502,0.0003881387,0.00006469158,0.00078755594,0.0003090696,0.0010823046,0.0001598206,0.0003780444],"category_scores_gemma":[0.0031292236,0.00009844228,0.00021789459,0.0006409444,0.00019360452,0.0001337876,0.0001592672,0.00048395336,0.0007545118],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000069917405,0.000028452112,0.005337101,0.000001444788,0.000022581338,0.000012329571,0.005123429,0.00022753967,0.0024096328,0.00027414082,0.1605134,0.82598],"study_design_scores_gemma":[0.005832035,0.0027466936,0.048179828,0.000076819706,0.00036945328,0.00008175496,0.009251465,0.027696948,0.00062650064,0.640371,0.26260448,0.0021630074],"about_ca_topic_score_codex":0.000021262496,"about_ca_topic_score_gemma":0.0000041807325,"teacher_disagreement_score":0.823817,"about_ca_system_score_codex":0.000028552953,"about_ca_system_score_gemma":0.00002411452,"threshold_uncertainty_score":0.96979743},"labels":[],"label_agreement":null},{"id":"W3037507981","doi":"10.1037/cep0000209","title":"When “bad” is good: How evaluative judgments eliminate the standard anchoring effect.","year":2020,"lang":"en","type":"article","venue":"Canadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Anchoring; Psychology; PsycINFO; Priming (agriculture); Cognitive psychology; Social psychology; Experimental psychology; Cognition; MEDLINE","score_opus":0.1583104538575124,"score_gpt":0.4096731112367655,"score_spread":0.25136265737925306,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3037507981","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96294075,0.0024548273,0.0003148482,0.024728725,0.0043301014,0.0005642496,0.00020731153,0.000023349736,0.0044358545],"genre_scores_gemma":[0.9854824,0.00002159184,0.0012917889,0.0121374065,0.00064062676,0.000036505957,0.000006691762,0.00006578029,0.0003172056],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9947095,0.0007163305,0.0013525554,0.0011866526,0.000532007,0.0015029632],"domain_scores_gemma":[0.994154,0.00057649746,0.0011261428,0.0011954012,0.00037353908,0.0025744708],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004531021,0.00057290535,0.0010165587,0.000577551,0.00060264155,0.00062201294,0.0034238514,0.00030915882,0.0021127628],"category_scores_gemma":[0.0012337103,0.0004366847,0.0005494923,0.00072968495,0.0006897233,0.0006647077,0.0001461784,0.00095581857,0.00026867926],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014913379,0.00025913608,0.05426376,0.0000106202115,0.0004326459,0.0025528367,0.06316274,0.00009960876,0.057813615,0.00035145401,0.62032914,0.19923313],"study_design_scores_gemma":[0.019528817,0.025883049,0.042791545,0.00058661046,0.0005006731,0.0048087947,0.104609646,0.0005476957,0.14180954,0.040598765,0.614578,0.0037568724],"about_ca_topic_score_codex":0.00080496963,"about_ca_topic_score_gemma":0.0034536107,"teacher_disagreement_score":0.19547625,"about_ca_system_score_codex":0.0013200907,"about_ca_system_score_gemma":0.00054688996,"threshold_uncertainty_score":0.9998085},"labels":[],"label_agreement":null},{"id":"W3038075178","doi":"10.1609/aaai.v34i09.7122","title":"The St. Petersburg Paradox: A Fresh Algorithmic Perspective","year":2020,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Perspective (graphical); Normative; Lottery; Expected utility hypothesis; Valuation (finance); Cognition; Epistemology; Stochastic game; Computer science; Positive economics; Mathematical economics; Psychology; Economics; Artificial intelligence; Philosophy; Microeconomics","score_opus":0.26155700513411934,"score_gpt":0.40065885441190724,"score_spread":0.1391018492777879,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3038075178","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91680664,0.0001018397,0.0021661406,0.055165846,0.0012749267,0.00082721206,0.00006481252,0.00010471355,0.02348785],"genre_scores_gemma":[0.99850893,0.0000456805,0.00041112286,0.00054604054,0.0001888764,0.000021000928,2.2609531e-7,0.000017487991,0.00026064852],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9963551,0.000047562477,0.0010893755,0.0008132106,0.001277875,0.00041686237],"domain_scores_gemma":[0.9958635,0.0009783811,0.00079949445,0.00046215826,0.0016932171,0.00020324944],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017056427,0.00027663657,0.000413564,0.00010643197,0.0005859942,0.0010336731,0.0036107048,0.00010594042,0.0004293543],"category_scores_gemma":[0.006951491,0.00015138266,0.00031281283,0.0009908192,0.0007296146,0.00035483946,0.0005340935,0.0005023928,0.0007287892],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037781178,0.00012696054,0.0003458594,0.0000041233156,0.000024511912,0.0000021053215,0.004612477,0.00008862796,0.00669829,0.43806705,0.007056583,0.54259557],"study_design_scores_gemma":[0.000042185497,0.0003583009,0.0001834903,0.000069275615,0.000024349212,0.0000057849943,0.03136262,0.024070734,0.04897419,0.89057815,0.0040459265,0.00028496518],"about_ca_topic_score_codex":0.00005583301,"about_ca_topic_score_gemma":0.000030080117,"teacher_disagreement_score":0.54231066,"about_ca_system_score_codex":0.00008557426,"about_ca_system_score_gemma":0.00015541258,"threshold_uncertainty_score":0.9967733},"labels":[],"label_agreement":null},{"id":"W3040193520","doi":"10.1016/j.cognition.2020.104381","title":"The smart intuitor: Cognitive capacity predicts intuitive rather than deliberate thinking","year":2020,"lang":"en","type":"article","venue":"Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":122,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; Agence Nationale de la Recherche","keywords":"Psychology; Cognition; Cognitive load; Intuition; Cognitive psychology; Cognitive science","score_opus":0.1931658009798375,"score_gpt":0.3593794691454466,"score_spread":0.16621366816560912,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3040193520","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96728724,0.00007400775,0.008695826,0.0020213453,0.0008682929,0.0003920641,0.00014046095,0.00013600144,0.02038478],"genre_scores_gemma":[0.9969333,0.000031436914,0.00021374556,0.0022366405,0.00036228122,0.000037115897,0.000024873285,0.000023904622,0.00013672902],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9971096,0.00036374276,0.00067259435,0.00063397724,0.0008952275,0.00032488303],"domain_scores_gemma":[0.9956235,0.00265689,0.00037655872,0.00027744766,0.00085179985,0.0002137607],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0019692879,0.00021950019,0.00028113398,0.00008836163,0.000778964,0.0010141557,0.000624507,0.00013507104,0.000255814],"category_scores_gemma":[0.0054594786,0.00014369236,0.00017155019,0.0005034377,0.00029424267,0.00060740474,0.00023826408,0.0003882998,0.0020795409],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003828921,0.00008905611,0.002063122,0.0000030735193,0.000051561317,0.000024383946,0.005884328,0.000015281545,0.00064852694,0.0007081237,0.008070839,0.9820588],"study_design_scores_gemma":[0.0022455337,0.00083997514,0.014066097,0.00030174074,0.00023384298,0.000040233484,0.013872593,0.005867553,0.015826972,0.90137947,0.04440961,0.00091638416],"about_ca_topic_score_codex":0.000009257336,"about_ca_topic_score_gemma":0.000072646064,"teacher_disagreement_score":0.9811424,"about_ca_system_score_codex":0.0000469649,"about_ca_system_score_gemma":0.000088538356,"threshold_uncertainty_score":0.99869746},"labels":[],"label_agreement":null},{"id":"W3043284836","doi":"10.1177/0272989x20938056","title":"The Effect of Information Formats and Incidental Affect on Prior and Posterior Probability Judgments","year":2020,"lang":"en","type":"article","venue":"Medical Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University; St. Michael's Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Ontario Ministry of Research, Innovation and Science; Canada Research Chairs","keywords":"Computer science; Bayesian probability; Test (biology); Table (database); Bayesian inference; Task (project management); Posterior probability; Inference; Probabilistic logic; Psychology; Artificial intelligence; Machine learning; Natural language processing; Information retrieval; Statistics; Data mining; Mathematics","score_opus":0.04839277711880483,"score_gpt":0.37641689393958977,"score_spread":0.3280241168207849,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3043284836","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99630004,0.00007177826,0.0015701678,0.0009690963,0.00035914042,0.00046053904,0.000011148716,0.00002397594,0.00023410238],"genre_scores_gemma":[0.99849737,0.000021872207,0.0007797968,0.0006444735,0.00003592207,0.000010306116,9.949148e-7,0.0000067718684,0.000002509555],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99590194,0.00028590788,0.0011283943,0.00036459585,0.0020913132,0.000227864],"domain_scores_gemma":[0.9879865,0.010818681,0.000428015,0.00038801873,0.00009362021,0.00028514984],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.006296173,0.00018447729,0.00043095363,0.00012875051,0.00032166063,0.00047805696,0.00063322193,0.00012422293,0.00009770114],"category_scores_gemma":[0.03220035,0.00009611679,0.00010135607,0.00031348754,0.00024044784,0.00062428735,0.00071637443,0.00026666335,0.00008632362],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006730668,0.000009665932,0.016188286,0.000012226192,0.0000039819674,0.0000060384687,0.00024658945,0.0000081466205,0.000023368724,0.000031433043,0.00047925906,0.9823179],"study_design_scores_gemma":[0.012955771,0.016846113,0.663988,0.0031812282,0.00016978131,0.00065899524,0.0021172313,0.11052173,0.0025477158,0.15274324,0.03269305,0.00157718],"about_ca_topic_score_codex":0.0000030596061,"about_ca_topic_score_gemma":0.000009220947,"teacher_disagreement_score":0.9807408,"about_ca_system_score_codex":0.000039029917,"about_ca_system_score_gemma":0.000043220083,"threshold_uncertainty_score":0.97595185},"labels":[],"label_agreement":null},{"id":"W3043991219","doi":"10.1016/j.cognition.2020.104390","title":"Future thinking about social targets: The influence of prediction outcome on memory","year":2020,"lang":"en","type":"article","venue":"Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":35,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Psychology; Cognitive psychology; Outcome (game theory); Expectancy theory; Trait; Social cognition; Cognition; Social psychology; Developmental psychology","score_opus":0.11499376377240744,"score_gpt":0.3734941258676917,"score_spread":0.25850036209528426,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3043991219","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9921864,0.000035613077,0.00034248107,0.0038795616,0.00046857414,0.00015365785,0.00010311736,0.00005106045,0.0027795332],"genre_scores_gemma":[0.99663055,0.0000078642,0.0000934101,0.0026966787,0.0005182735,0.000007469421,0.000013403821,0.000008133019,0.000024230083],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9981171,0.00011246845,0.00059922267,0.0003032509,0.0007451126,0.00012285056],"domain_scores_gemma":[0.99871093,0.000399775,0.00036211335,0.00019385671,0.00028301973,0.00005027559],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010671082,0.00010517831,0.00020079626,0.00007582934,0.00031364182,0.00014339245,0.00045575583,0.000104179635,0.00016906438],"category_scores_gemma":[0.0011520804,0.00006697455,0.00012867904,0.00034338827,0.00009593689,0.00031319726,0.000080679376,0.00022916374,0.000338488],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005426253,0.00018815561,0.011668015,0.000020848684,0.00003295156,0.000017463206,0.012216598,0.0026587525,0.004504396,0.0013475036,0.02045967,0.946343],"study_design_scores_gemma":[0.0017053968,0.0007932412,0.6885066,0.0001389143,0.00018072638,0.000014472607,0.011723577,0.0027654148,0.0038121575,0.25633737,0.033454742,0.00056741084],"about_ca_topic_score_codex":0.0000020617038,"about_ca_topic_score_gemma":0.000002824219,"teacher_disagreement_score":0.9457756,"about_ca_system_score_codex":0.00002330245,"about_ca_system_score_gemma":0.000029427145,"threshold_uncertainty_score":0.43506914},"labels":[],"label_agreement":null},{"id":"W3045518291","doi":"10.48550/arxiv.2007.14361","title":"Assessing Risks of Biases in Cognitive Decision Support Systems","year":2020,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Probabilistic logic; Computer science; Component (thermodynamics); Biometrics; Cognition; Process (computing); Decision support system; Risk analysis (engineering); Cognitive bias; Face (sociological concept); Risk assessment; Machine learning; Artificial intelligence; Computer security; Psychology; Business","score_opus":0.6998893331342111,"score_gpt":0.4081550050253572,"score_spread":0.2917343281088539,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3045518291","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96163577,0.00006529014,0.033213113,0.000023476869,0.0012976162,0.0003722732,0.00019315656,0.000053139745,0.0031461825],"genre_scores_gemma":[0.9992615,0.00008466508,0.00028139632,0.000036685076,0.00006533724,0.0000010286932,0.00003110891,0.00002700054,0.00021125731],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9957691,0.00040025602,0.0012508684,0.0017252084,0.00046799626,0.0003866075],"domain_scores_gemma":[0.99150425,0.005176586,0.0013800992,0.0010237028,0.00064659864,0.0002687663],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0024929824,0.00038986892,0.0011472609,0.001132516,0.000106929976,0.0005785664,0.0017436384,0.0004924939,0.00029933354],"category_scores_gemma":[0.0048799906,0.00038002586,0.00042369103,0.0014166312,0.00023521595,0.0007201809,0.001854389,0.0007699053,0.00033615576],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00067712145,0.00059555576,0.19017197,0.000062520216,0.000101277714,0.0028245703,0.0006842591,0.61846983,0.00008054601,0.0015218497,0.0017446724,0.18306583],"study_design_scores_gemma":[0.0031652434,0.00042717854,0.076271534,0.003919456,0.0004844226,0.000033571334,0.017403614,0.61438155,0.00031310745,0.2806598,0.0010530476,0.0018874953],"about_ca_topic_score_codex":0.00066183467,"about_ca_topic_score_gemma":0.00015080864,"teacher_disagreement_score":0.27913794,"about_ca_system_score_codex":0.00024882559,"about_ca_system_score_gemma":0.00058196747,"threshold_uncertainty_score":0.9998652},"labels":[],"label_agreement":null},{"id":"W3046183466","doi":"10.1007/s10683-020-09668-6","title":"Learn or react? An experimental study of preventive health decision making","year":2020,"lang":"en","type":"article","venue":"Experimental Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Southern Methodist University; York University; Universität Basel","keywords":"Actuarial science; Health risk; Adverse effect; Risk analysis (engineering); Business; Emerging technologies; Medicine; Environmental health; Computer science; Pharmacology","score_opus":0.21520137863268252,"score_gpt":0.4693561955269315,"score_spread":0.25415481689424896,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3046183466","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9969468,0.00025057676,0.00020858666,0.00013412026,0.00071268977,0.0007561741,0.000040318657,0.00006301279,0.00088769535],"genre_scores_gemma":[0.99488825,0.000010517835,0.004040396,0.0007328798,0.00016022321,0.00003219395,0.0000069850903,0.00005431192,0.000074262265],"study_design_codex":"design_other","study_design_gemma":"qualitative","domain_scores_codex":[0.995585,0.00028738464,0.0019562056,0.0012582047,0.0005037453,0.00040945347],"domain_scores_gemma":[0.9969861,0.00053345796,0.0010677292,0.00091441773,0.00007703869,0.00042126985],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0013032748,0.00036405865,0.00094688335,0.00023633568,0.0002795212,0.00037026827,0.0013168975,0.0001079626,0.0016497938],"category_scores_gemma":[0.0002973382,0.0003055828,0.0002191154,0.00033111908,0.000118445205,0.0011145222,0.00066093594,0.00021732479,0.00031628186],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.006346001,0.015564336,0.008194096,0.000007445865,0.00011081925,0.00006515145,0.09846989,0.0047872877,0.007367974,0.0005706261,0.0048771612,0.8536392],"study_design_scores_gemma":[0.012034054,0.050619382,0.0055962033,0.00018840558,0.00004828483,0.00010520291,0.79517204,0.02558718,0.08395727,0.0069065355,0.017323904,0.0024615196],"about_ca_topic_score_codex":0.000086467466,"about_ca_topic_score_gemma":0.00010187662,"teacher_disagreement_score":0.8511777,"about_ca_system_score_codex":0.00036133686,"about_ca_system_score_gemma":0.00021758548,"threshold_uncertainty_score":0.9999396},"labels":[],"label_agreement":null},{"id":"W3048604892","doi":"10.1007/s40070-020-00114-9","title":"Effects of information presentation on regulatory decisions for products of biotechnology","year":2020,"lang":"en","type":"article","venue":"EURO Journal on Decision Processes","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Genome Canada","keywords":"Presentation (obstetrics); Psychology; Knowledge management; Computer science; Management science; Medicine; Engineering","score_opus":0.09087609137174651,"score_gpt":0.3723480374679482,"score_spread":0.2814719460962017,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3048604892","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9442658,0.00019479336,0.05147062,0.002453208,0.0008244952,0.00055372826,0.000036365058,0.000034926234,0.00016608436],"genre_scores_gemma":[0.9895182,0.00021380048,0.009464901,0.00061334256,0.00012076655,0.000011368297,0.0000036588713,0.000020429845,0.000033505486],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9954235,0.000120243865,0.002032127,0.0004378245,0.0017522656,0.00023407071],"domain_scores_gemma":[0.984181,0.01089584,0.002018003,0.00053283427,0.0021803463,0.00019200155],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.001917618,0.00023024605,0.00061331125,0.0010591223,0.00018890103,0.0002041613,0.0012279866,0.00018084102,0.000044595472],"category_scores_gemma":[0.12044383,0.00015991509,0.00019792703,0.0017909271,0.00012520462,0.001032173,0.0001399406,0.0003146954,0.000142536],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020674344,0.00027059505,0.00012818226,0.00007590628,0.000016614016,0.000007959628,0.00043330036,0.0028072814,0.0046629235,0.00084736233,0.023093654,0.9655888],"study_design_scores_gemma":[0.0040066773,0.006653543,0.005857237,0.0010049666,0.00008506005,0.00007358875,0.0006450198,0.0010193536,0.70316714,0.16575074,0.111271694,0.00046494967],"about_ca_topic_score_codex":4.3502726e-7,"about_ca_topic_score_gemma":4.7752826e-7,"teacher_disagreement_score":0.96512383,"about_ca_system_score_codex":0.000036637302,"about_ca_system_score_gemma":0.0003395405,"threshold_uncertainty_score":0.88696504},"labels":[],"label_agreement":null},{"id":"W3080434239","doi":"10.1109/isit44484.2020.9174378","title":"Comparison of Information Structures for Zero-Sum Games in Standard Borel Spaces","year":2020,"lang":"en","type":"article","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Converse; Mathematics; Generalization; Corollary; Mathematical economics; Zero-sum game; Characterization (materials science); Zero (linguistics); Complete information; Space (punctuation); Discrete mathematics; Combinatorics; Game theory; Computer science; Mathematical analysis","score_opus":0.1580900804845851,"score_gpt":0.4411473153183732,"score_spread":0.2830572348337881,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3080434239","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9538778,0.000034919165,0.042717732,0.0012735787,0.00019820986,0.00020738233,0.00009670676,0.00002240732,0.0015712716],"genre_scores_gemma":[0.98692244,0.000002661906,0.012726535,0.00028572127,0.000017710878,0.0000040738,0.000007696294,0.00000385774,0.000029315013],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9982436,0.000027385788,0.0009206806,0.00018300583,0.0004891334,0.00013620648],"domain_scores_gemma":[0.99856776,0.00058566354,0.00035415613,0.00020593092,0.0002125041,0.000073972216],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006667264,0.00009573233,0.0003988078,0.00019102945,0.000039106457,0.00025314846,0.0004273365,0.00007049463,0.00021131657],"category_scores_gemma":[0.001709596,0.00006596752,0.000088779125,0.00032527858,0.000052004958,0.0006398632,0.00008139765,0.00007655621,0.000038577447],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003924714,0.000026625423,0.086599275,0.000011597551,0.0000049399378,3.1973576e-7,0.0035714295,0.0044750394,0.00015966866,0.006310003,0.062234666,0.83621395],"study_design_scores_gemma":[0.0027633337,0.0013499067,0.053362284,0.000045305493,0.000026558011,0.0000016070833,0.024181366,0.0677028,0.018734418,0.4444526,0.3868023,0.0005775251],"about_ca_topic_score_codex":0.000031446194,"about_ca_topic_score_gemma":0.000068064925,"teacher_disagreement_score":0.83563644,"about_ca_system_score_codex":0.000022284008,"about_ca_system_score_gemma":0.000061827624,"threshold_uncertainty_score":0.26900774},"labels":[],"label_agreement":null},{"id":"W3082627313","doi":"10.31234/osf.io/gkduw","title":"Cultivating credibility with probability words and numbers","year":2019,"lang":"en","type":"article","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"Ministère de la Défense Nationale","keywords":"Credibility; Probability distribution; Probability model; Computer science; Econometrics; Psychology; Statistics; Mathematics","score_opus":0.10962276744340586,"score_gpt":0.3752661060700869,"score_spread":0.26564333862668105,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3082627313","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9631533,0.000005626062,0.00086488546,0.000227845,0.00014686203,0.0002463889,0.0000037322327,0.00004989331,0.035301477],"genre_scores_gemma":[0.9814572,4.5976194e-7,0.016047461,0.000112853806,0.00001683775,0.000004005994,6.134798e-7,0.000006405749,0.0023541946],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9980241,0.00007669365,0.0004664011,0.000704375,0.0005330094,0.00019542608],"domain_scores_gemma":[0.9978032,0.0010113702,0.00015070547,0.0007562865,0.00016648165,0.00011194395],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0027362802,0.00012338966,0.00027044283,0.00006361357,0.00008619628,0.00031492504,0.00032984317,0.00006201609,0.0016043737],"category_scores_gemma":[0.0010670496,0.00006974822,0.000049241105,0.00033265876,0.00013360448,0.00042799147,0.0001652409,0.00012515791,0.00040159308],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004220186,0.000042348056,0.76619273,0.0000020457533,0.0000022928314,8.6056673e-7,0.00028413493,0.000060285747,0.0000715103,0.0003601186,0.00032758378,0.23261389],"study_design_scores_gemma":[0.0019054356,0.0006375581,0.55593544,0.0000847406,0.000022035085,0.0000545563,0.008963185,0.006255563,0.00071994634,0.3996013,0.024895433,0.0009247992],"about_ca_topic_score_codex":0.000119281445,"about_ca_topic_score_gemma":0.00018693054,"teacher_disagreement_score":0.39924118,"about_ca_system_score_codex":0.000042048978,"about_ca_system_score_gemma":0.000056609668,"threshold_uncertainty_score":0.9993083},"labels":[],"label_agreement":null},{"id":"W3084133646","doi":"10.7554/elife.54051.sa2","title":"Author response: Neural arbitration between social and individual learning systems","year":2020,"lang":"en","type":"peer-review","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health","funders":"","keywords":"Arbitration; Social decision making; Dorsolateral prefrontal cortex; Social learning; Psychology; Prefrontal cortex; Computer science; Cognitive psychology; Knowledge management; Cognition; Neuroscience","score_opus":0.4572059540925723,"score_gpt":0.4854881480733975,"score_spread":0.02828219398082521,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3084133646","genre_codex":"commentary","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3810827,0.022203997,0.0017678412,0.5596095,0.016818509,0.0030549031,0.0030040783,0.00081566675,0.011642817],"genre_scores_gemma":[0.42988658,0.00019945268,0.00063239597,0.0050570406,0.004819077,0.00008417736,0.0010526954,0.00015380153,0.55811477],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99284995,0.0015337561,0.0018485095,0.0012093197,0.0021852397,0.00037319987],"domain_scores_gemma":[0.994075,0.0036357008,0.0011732909,0.00042362505,0.00042487157,0.00026749566],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.009906435,0.00045014257,0.0015234775,0.00041130726,0.0005116878,0.0019735312,0.0011309019,0.0006020483,0.00050321233],"category_scores_gemma":[0.007884823,0.0003440478,0.0003168048,0.0006498343,0.00013209342,0.00033820412,0.0005408113,0.0013251412,0.00061342394],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003715727,0.000007066494,0.00040589238,0.000060385297,0.00002028967,0.00001301124,0.00017251114,0.000010044703,0.0000018074107,0.000030559782,0.7675831,0.23165822],"study_design_scores_gemma":[0.00017016991,0.00017505295,0.0043792976,0.00031831063,0.0002085783,0.000017844728,0.00033449763,0.00052838994,9.539888e-7,0.0007933326,0.99264646,0.00042708789],"about_ca_topic_score_codex":0.000082567414,"about_ca_topic_score_gemma":0.00002467112,"teacher_disagreement_score":0.55455244,"about_ca_system_score_codex":0.000079411526,"about_ca_system_score_gemma":0.00033619572,"threshold_uncertainty_score":0.9999012},"labels":[],"label_agreement":null},{"id":"W3084582880","doi":"10.1038/s41562-020-00941-5","title":"Divisive normalization does influence decisions with multiple alternatives","year":2020,"lang":"en","type":"letter","venue":"Nature Human Behaviour","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":46,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"National Institute of Mental Health; U.S. Department of Health and Human Services","keywords":"Normalization (sociology); Psychology; Computer science; Sociology","score_opus":0.06577026278852935,"score_gpt":0.3768451235969591,"score_spread":0.3110748608084297,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3084582880","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90454495,0.00014046421,0.0006772996,0.09036023,0.0016568636,0.0008531162,0.0009024264,0.00027341652,0.0005912329],"genre_scores_gemma":[0.8176546,0.000018444523,0.0010905156,0.17626502,0.0017880377,0.000064803,0.000594353,0.00014678115,0.00237745],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99155265,0.00036205284,0.0015845131,0.002238213,0.0035335224,0.0007290205],"domain_scores_gemma":[0.992311,0.0022897664,0.0016125925,0.0019193077,0.0015824323,0.00028488145],"candidate_categories":["metaepi_narrow","scholarly_communication","research_integrity"],"consensus_categories":["research_integrity"],"category_scores_codex":[0.00072686153,0.0009261497,0.0012374477,0.000996641,0.0008319106,0.0017298791,0.0036961348,0.001995827,0.0006470783],"category_scores_gemma":[0.0036087825,0.0005610765,0.00046284613,0.0010349852,0.00039500665,0.0010422617,0.00071056583,0.0062758224,0.00066386425],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006123894,0.00012259702,0.14458337,0.000008249077,0.000050120565,0.0022156036,0.00082994584,0.00018900787,0.00009624698,0.000071892515,0.8381214,0.013650287],"study_design_scores_gemma":[0.0018534221,0.0006613539,0.10720563,0.0007213311,0.0004364287,0.00013259565,0.00061729184,0.0002447858,0.00042690578,0.036747336,0.8482819,0.002670981],"about_ca_topic_score_codex":0.00012855754,"about_ca_topic_score_gemma":0.0005474673,"teacher_disagreement_score":0.08689035,"about_ca_system_score_codex":0.00021519898,"about_ca_system_score_gemma":0.00020587069,"threshold_uncertainty_score":0.9996841},"labels":[],"label_agreement":null},{"id":"W3086204950","doi":"10.1111/jems.12402","title":"The effects of ambiguity on entrepreneurship","year":2020,"lang":"en","type":"article","venue":"Journal of Economics & Management Strategy","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Ambiguity; Entrepreneurship; Ambiguity aversion; Investment (military); Microeconomics; Economics; Risk aversion (psychology); Econometrics; Expected utility hypothesis; Financial economics; Computer science; Political science","score_opus":0.1266603414303841,"score_gpt":0.3552229724469493,"score_spread":0.22856263101656518,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3086204950","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9880651,0.00010022103,0.00015327199,0.0019328775,0.0010055373,0.0001472055,0.0000039629795,0.0000052637347,0.008586545],"genre_scores_gemma":[0.998456,0.0004606098,0.0001469946,0.00049734826,0.00015473897,0.0000013793098,2.8087413e-7,0.000010667782,0.00027196322],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9976918,0.00012940205,0.0014008202,0.00027924048,0.00029360436,0.00020513836],"domain_scores_gemma":[0.99604243,0.001645692,0.0015370268,0.00046732038,0.00013894246,0.0001686141],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018959211,0.0001533089,0.00043076585,0.0001629474,0.00011133682,0.00039564093,0.0013909835,0.000050491526,0.00007441565],"category_scores_gemma":[0.0006910889,0.00009832483,0.00032069997,0.0001844489,0.000084148865,0.0002698065,0.00016944755,0.00021497883,0.0001318285],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004226239,0.00016456282,0.0025507575,0.000021023534,0.00014022435,0.00007953048,0.00014786008,0.013756601,0.00007560392,0.025316086,0.012444587,0.94488055],"study_design_scores_gemma":[0.0035371825,0.004331017,0.04706943,0.00016752642,0.0002878182,0.0000324992,0.002565655,0.0035859095,0.0035718968,0.8260218,0.10822156,0.0006077284],"about_ca_topic_score_codex":0.000002968596,"about_ca_topic_score_gemma":0.0000073599467,"teacher_disagreement_score":0.9442728,"about_ca_system_score_codex":0.00005662629,"about_ca_system_score_gemma":0.00004847066,"threshold_uncertainty_score":0.40095702},"labels":[],"label_agreement":null},{"id":"W3087152258","doi":"10.1111/1911-3846.12649","title":"Root Cause Analysis and Its Effect on Auditors' Judgments and Decisions in an Integrated Audit*","year":2020,"lang":"en","type":"article","venue":"Contemporary Accounting Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Materiality (auditing); Audit; Accounting; Quality audit; Psychology; Control (management); Cognition; Audit risk; Business; Management; Economics","score_opus":0.25757745694492734,"score_gpt":0.4658375207085678,"score_spread":0.20826006376364048,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3087152258","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99678344,0.00030142823,0.00008070269,0.0014975577,0.00022012508,0.00046289497,0.00004787668,0.00004986825,0.0005561321],"genre_scores_gemma":[0.9993218,0.00002460908,0.000085121625,0.00019427374,0.00015812472,0.000024849538,0.000024027506,0.000025966692,0.00014118558],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9941487,0.0012007918,0.0009791128,0.0014090089,0.001745023,0.0005173944],"domain_scores_gemma":[0.9897699,0.008159513,0.00024559486,0.00071038364,0.00061846507,0.00049618125],"candidate_categories":["metaresearch","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.011620138,0.00028095779,0.00076660444,0.0020619058,0.00047009796,0.001558159,0.0010283276,0.00020808587,0.00013104636],"category_scores_gemma":[0.020058058,0.0002090121,0.00011704451,0.004641714,0.00018392032,0.0012814234,0.0006972079,0.0009443431,0.00028431416],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00056861085,0.00013212879,0.79304147,0.0000061969413,0.0000652193,0.00017751382,0.0006176883,0.0000919679,0.0010402635,0.00003720278,0.0067802947,0.19744146],"study_design_scores_gemma":[0.0039879484,0.0036380002,0.8681909,0.00047383888,0.00012024789,0.000011478277,0.0026185294,0.08112703,0.0017500687,0.0052353293,0.03165016,0.0011965004],"about_ca_topic_score_codex":0.0001901562,"about_ca_topic_score_gemma":0.00041463113,"teacher_disagreement_score":0.19624496,"about_ca_system_score_codex":0.00008687669,"about_ca_system_score_gemma":0.000219038,"threshold_uncertainty_score":0.99947834},"labels":[],"label_agreement":null},{"id":"W3087846925","doi":"10.1007/s10683-020-09678-4","title":"Is the Allais paradox due to appeal of certainty or aversion to zero?","year":2020,"lang":"en","type":"article","venue":"Experimental Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"University of Technology Sydney; Carnegie Mellon University","keywords":"Certainty; Zero (linguistics); Economics; Nothing; Mathematical economics; Phenomenon; Contrast (vision); Prospect theory; Positive economics; Microeconomics; Physics; Philosophy; Epistemology","score_opus":0.20023718666876034,"score_gpt":0.40577978501148987,"score_spread":0.20554259834272953,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3087846925","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9877291,0.00003434929,0.0005948247,0.008613684,0.000593587,0.00039311405,0.0000934804,0.000025021902,0.0019228637],"genre_scores_gemma":[0.9864677,0.0000055660835,0.0021470545,0.01086922,0.00011670009,0.00001742151,0.0000026243622,0.000023265877,0.00035040168],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9977661,0.0000606431,0.0008960335,0.0007124166,0.00027372607,0.00029107687],"domain_scores_gemma":[0.9981071,0.0004406769,0.0002522433,0.0007214265,0.00006165687,0.0004169179],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0006256345,0.00022109387,0.0004930503,0.0001194064,0.0001719327,0.00024361449,0.0013809258,0.00008413158,0.0019336658],"category_scores_gemma":[0.00030202128,0.00014773553,0.00023014584,0.0003190868,0.00008304382,0.00022890158,0.00071353035,0.000109805835,0.0034466973],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0044012433,0.00061349844,0.0036220644,0.000008147116,0.00010939818,0.00006271735,0.05078535,0.016747246,0.01656951,0.0031334895,0.44423792,0.4597094],"study_design_scores_gemma":[0.0019472912,0.0026658492,0.0020290597,0.000043610387,0.000029926347,0.00005710962,0.02693997,0.0130663,0.2394753,0.0084089795,0.70413715,0.0011994666],"about_ca_topic_score_codex":0.00008943749,"about_ca_topic_score_gemma":0.00002680042,"teacher_disagreement_score":0.45850995,"about_ca_system_score_codex":0.00015067903,"about_ca_system_score_gemma":0.0000848252,"threshold_uncertainty_score":0.9989787},"labels":[],"label_agreement":null},{"id":"W3089376958","doi":"10.1002/bdm.2210","title":"The moderating role of processing style in risk perceptions and risky decision making","year":2020,"lang":"en","type":"article","venue":"Journal of Behavioral Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Laurentian University","funders":"","keywords":"Affect (linguistics); Risk perception; Perception; Psychology; Social psychology; Risk aversion (psychology); Risk analysis (engineering); Style (visual arts); Risk assessment; Medicine; Computer science; Economics; Expected utility hypothesis; Computer security","score_opus":0.08454026949192234,"score_gpt":0.4135205257038696,"score_spread":0.32898025621194726,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3089376958","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95943815,0.0013262534,0.038449742,0.00012471835,0.0003406198,0.00019362252,0.000018875977,0.000015360349,0.000092675335],"genre_scores_gemma":[0.94048154,0.00017055997,0.059075452,0.0000739725,0.00015460001,0.0000030723465,2.2091834e-7,0.000035890185,0.000004714019],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99282086,0.00037476176,0.0035847435,0.0006129865,0.0021608511,0.0004457901],"domain_scores_gemma":[0.9899465,0.005084128,0.0032302486,0.00053228455,0.00097201276,0.00023484464],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0063690785,0.00033369468,0.00092699326,0.0007107198,0.0007714703,0.0012689568,0.0013804493,0.0002153954,0.00012106496],"category_scores_gemma":[0.005781884,0.00021765199,0.00039889914,0.0012299586,0.00020980828,0.001303943,0.00057484955,0.0010099827,0.000022150658],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039935738,0.00009884835,0.08635632,0.0000022717904,0.0000041784724,0.000032481476,0.0025697213,0.006809933,0.00085793354,0.000015156384,0.00016615825,0.90268767],"study_design_scores_gemma":[0.0033078827,0.0016015493,0.34763262,0.0033220598,0.0003139661,0.00056520227,0.055790216,0.29554367,0.00019741587,0.28850117,0.0021338076,0.0010904318],"about_ca_topic_score_codex":0.000017728353,"about_ca_topic_score_gemma":0.0001415643,"teacher_disagreement_score":0.9015972,"about_ca_system_score_codex":0.00013527214,"about_ca_system_score_gemma":0.00019241919,"threshold_uncertainty_score":0.99976784},"labels":[],"label_agreement":null},{"id":"W3091841424","doi":"10.1016/j.econlet.2020.109608","title":"On expected utility theorems on mixture sets","year":2020,"lang":"en","type":"article","venue":"Economics Letters","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Axiom independence; Axiom; Transitive relation; Mathematical economics; Expected utility hypothesis; Mathematics; Axiom of choice; Independence (probability theory); Zermelo–Fraenkel set theory; Subjective expected utility; Combinatorics; Computer science; Set theory; Set (abstract data type); Statistics","score_opus":0.13063911144692988,"score_gpt":0.34717741494844373,"score_spread":0.21653830350151385,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3091841424","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9638315,0.0000066259217,0.00031446392,0.025700618,0.0010166963,0.00016106348,0.00008413574,0.00008433404,0.008800589],"genre_scores_gemma":[0.9542329,0.0000036878182,0.0003326359,0.045126993,0.0001993954,0.0000062918502,0.000010360809,0.000026344629,0.00006140408],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99758065,0.00013032446,0.00072169147,0.0009862367,0.00025777117,0.00032335287],"domain_scores_gemma":[0.9971561,0.0013351194,0.0003071573,0.0008946199,0.000040955358,0.00026607575],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0008341372,0.00026470132,0.00043832776,0.00016569214,0.0001501667,0.00043233894,0.0010637597,0.00012461137,0.0019997677],"category_scores_gemma":[0.0010172905,0.00021657771,0.00025864685,0.00021124088,0.00011861029,0.00022374015,0.00013132821,0.00034348396,0.0041901413],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00072129536,0.00018013992,0.0031987438,0.0000023307364,0.00003867279,0.00005494417,0.0014039382,0.006927643,0.00096011854,0.0055863527,0.49797183,0.482954],"study_design_scores_gemma":[0.0045309076,0.0014556266,0.029783739,0.00007843435,0.00006356325,0.000031592535,0.0024005228,0.04849158,0.0065414086,0.45101312,0.45255646,0.0030530605],"about_ca_topic_score_codex":0.0000061379105,"about_ca_topic_score_gemma":0.000006872202,"teacher_disagreement_score":0.47990093,"about_ca_system_score_codex":0.000099448094,"about_ca_system_score_gemma":0.000037104764,"threshold_uncertainty_score":0.9989125},"labels":[],"label_agreement":null},{"id":"W3092085399","doi":"10.1016/j.cognition.2020.104420","title":"Thinking in a foreign language distorts allocation of cognitive effort: Evidence from reasoning","year":2020,"lang":"en","type":"article","venue":"Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":56,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Narodowe Centrum Nauki","keywords":"Syllogism; Psychology; Logical reasoning; Cognitive psychology; Foreign language; Cognition; Context (archaeology); Psychology of reasoning; Cognitive science; Linguistics; Verbal reasoning","score_opus":0.14096198959551698,"score_gpt":0.3882695714349855,"score_spread":0.24730758183946855,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3092085399","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9846376,0.00024208442,0.011983435,0.00016945231,0.000087887915,0.00019488604,0.000046234778,0.000030542666,0.0026078569],"genre_scores_gemma":[0.99852186,0.000014278204,0.0010128396,0.00029138988,0.00006485954,0.000013235547,0.00006362006,0.00000974474,0.000008173854],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9981597,0.00009402943,0.00059138105,0.0004264391,0.00059843325,0.00013000102],"domain_scores_gemma":[0.99742097,0.0017422548,0.00036564402,0.00017117999,0.0002260018,0.00007396796],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010595251,0.00010618969,0.0002543315,0.00013717721,0.000067177665,0.00012152227,0.00030370775,0.000077154546,0.00025504816],"category_scores_gemma":[0.007232429,0.000094692274,0.000079738595,0.00045660057,0.000056358782,0.00059516326,0.00010069781,0.00013321576,0.00016514542],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004145024,0.00011932594,0.08887041,0.000011156102,0.000014322009,0.000073858246,0.020527724,0.00015590257,0.005715235,0.00020232487,0.0003155779,0.8835797],"study_design_scores_gemma":[0.0031992723,0.00075091346,0.48233908,0.0077378154,0.0002918394,0.000016964925,0.05256054,0.037572388,0.061695993,0.3525193,0.00018219084,0.00113368],"about_ca_topic_score_codex":0.0000922005,"about_ca_topic_score_gemma":0.000111963775,"teacher_disagreement_score":0.882446,"about_ca_system_score_codex":0.000038596052,"about_ca_system_score_gemma":0.000050530947,"threshold_uncertainty_score":0.8658415},"labels":[],"label_agreement":null},{"id":"W3092980512","doi":"10.3758/s13421-020-01108-3","title":"Reasoning strategies predict use of very fast logical reasoning","year":2020,"lang":"en","type":"article","venue":"Memory & Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Psychology; Logical reasoning; Verbal reasoning; Cognitive science; Deductive reasoning; Cognition; Cognitive psychology; Analytic reasoning; Causal reasoning; Psychology of reasoning; Artificial intelligence; Mathematics education; Computer science; Neuroscience","score_opus":0.22554403598104905,"score_gpt":0.37119629759959405,"score_spread":0.145652261618545,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3092980512","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98538685,0.00004317057,0.006577383,0.00018729141,0.0002494433,0.00014030108,0.00006591687,0.00009398411,0.007255682],"genre_scores_gemma":[0.9964993,0.000015497028,0.002865813,0.0003343385,0.0001496763,0.000006509813,0.000028892735,0.000014454873,0.000085511245],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99755454,0.00018344876,0.000740076,0.00054543774,0.00075106305,0.00022541876],"domain_scores_gemma":[0.99790525,0.0008890767,0.00038407726,0.0003130269,0.00034395923,0.00016460996],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00093817443,0.00016829895,0.00037831618,0.00013638346,0.00014120193,0.0005222931,0.0003579628,0.00012471597,0.0006601283],"category_scores_gemma":[0.003913954,0.00013675398,0.00016611266,0.00046070555,0.00014849925,0.0011870988,0.00015074942,0.0002227833,0.00034596396],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006360255,0.00023061836,0.0069714664,0.000019315034,0.000036265836,0.00014304317,0.0016882521,0.004405415,0.011122237,0.00086756144,0.007376814,0.96650296],"study_design_scores_gemma":[0.010193544,0.0066403775,0.31494844,0.0032665725,0.00127855,0.00051357003,0.1002179,0.21018791,0.049228072,0.23133187,0.06701142,0.0051817787],"about_ca_topic_score_codex":0.000019383528,"about_ca_topic_score_gemma":0.000009649955,"teacher_disagreement_score":0.96132123,"about_ca_system_score_codex":0.000024038874,"about_ca_system_score_gemma":0.00010123081,"threshold_uncertainty_score":0.7227942},"labels":[],"label_agreement":null},{"id":"W3093398578","doi":"10.1177/0022243720956642","title":"Preference Dynamics in Sequential Consumer Choice with Defaults","year":2020,"lang":"en","type":"article","venue":"Journal of Marketing Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Science Foundation; Erasmus Research Institute of Management; Canada Research Chairs; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Social Sciences and Humanities Research Council of Canada; Network for Studies on Pensions, Aging and Retirement","keywords":"Default; Spillover effect; Preference; Economics; Consumer choice; Product (mathematics); Microeconomics; Marketing; Business","score_opus":0.4765421875752669,"score_gpt":0.49566332838703386,"score_spread":0.019121140811766968,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3093398578","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9929552,0.00008850986,0.00027724556,0.0028248217,0.00013966787,0.00010912345,0.0000066981374,0.000005974953,0.003592779],"genre_scores_gemma":[0.99811554,0.000049934923,0.0013952132,0.00008568486,0.00014153733,0.0000014246472,4.932905e-7,0.0000137396555,0.00019640617],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9936315,0.0018809633,0.0010906734,0.0003636867,0.0025656682,0.00046752006],"domain_scores_gemma":[0.98343617,0.013790631,0.0005357235,0.0003182242,0.0016034463,0.00031580843],"candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.037054297,0.0001162676,0.00038221944,0.00057352736,0.00012767747,0.0005122782,0.0013138164,0.000093323215,0.0003660428],"category_scores_gemma":[0.04703376,0.000076735676,0.00009355855,0.0012829668,0.00019525857,0.00041616888,0.0003016379,0.001304731,0.000107117725],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004071988,0.00013206735,0.4830228,0.000014847207,0.000019503253,0.00037982233,0.0004267214,0.0005917624,0.00021059356,0.000052472784,0.0074357158,0.5036417],"study_design_scores_gemma":[0.009809349,0.0038964718,0.7021664,0.0022464155,0.00007018937,0.00095055776,0.020859286,0.11370643,0.00044361973,0.023724308,0.12079699,0.0013300151],"about_ca_topic_score_codex":0.000053186697,"about_ca_topic_score_gemma":0.0004085645,"teacher_disagreement_score":0.5023117,"about_ca_system_score_codex":0.00029316885,"about_ca_system_score_gemma":0.0005704378,"threshold_uncertainty_score":0.9915552},"labels":[],"label_agreement":null},{"id":"W3096710371","doi":"10.1162/rest_a_01232","title":"Identifying Rule-Based Rationality","year":2022,"lang":"en","type":"article","venue":"The Review of Economics and Statistics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Simple (philosophy); Rationality; Decision rule; Preference; Set (abstract data type); Portfolio; Admissible decision rule; Mathematical economics; Function (biology); Rule-based system; Computer science; Observer (physics); Economics; Econometrics; Microeconomics; Artificial intelligence; Decision analysis; Evidential reasoning approach; Business decision mapping; Financial economics","score_opus":0.20415181746430902,"score_gpt":0.42076364377819875,"score_spread":0.21661182631388973,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3096710371","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87152153,0.048809167,0.058726232,0.008315884,0.0019711438,0.0010575792,0.006321583,0.00002368544,0.003253171],"genre_scores_gemma":[0.88148844,0.06023599,0.049337137,0.007814903,0.00011851125,0.000089262656,0.00016942846,0.00003918722,0.0007071442],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9983979,0.00020724638,0.00087606395,0.00023025124,0.00018863732,0.00009989622],"domain_scores_gemma":[0.9971306,0.0016727514,0.00058239466,0.00046267963,0.00010733428,0.000044291042],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004883521,0.0000850471,0.00034903275,0.00005779556,0.000314768,0.000102878344,0.0005107557,0.000012479087,0.00092701183],"category_scores_gemma":[0.0006905169,0.00005981158,0.00008302695,0.00012308454,0.00010344377,0.0000644827,0.0002234023,0.00010524474,0.00002796353],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016711316,0.000053116208,0.0006200609,0.00015329791,0.000012731575,0.0000014920149,0.0000653566,0.001976361,0.0000025129802,0.1322656,0.01258269,0.85225004],"study_design_scores_gemma":[0.00022842005,0.00005962346,0.0021496844,0.00013912698,0.000055385954,0.000013490802,0.00017191148,0.020090045,0.00000845702,0.7764867,0.20042877,0.00016839356],"about_ca_topic_score_codex":0.000018051764,"about_ca_topic_score_gemma":0.000011923628,"teacher_disagreement_score":0.85208166,"about_ca_system_score_codex":0.00004193959,"about_ca_system_score_gemma":0.00012989643,"threshold_uncertainty_score":0.9999863},"labels":[],"label_agreement":null},{"id":"W3098475884","doi":"10.1007/978-3-030-48853-6_7","title":"A QP Framework: A Contextual Representation of Agents’ Preferences in Investment Choice","year":2020,"lang":"en","type":"book-chapter","venue":"Studies in computational intelligence","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Representation (politics); Computer science; Artificial intelligence; Investment (military); Microeconomics; Economics; Political science; Law","score_opus":0.5692821209477834,"score_gpt":0.5178456250499837,"score_spread":0.05143649589779975,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3098475884","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24301313,0.021873098,0.115730256,0.0067909616,0.013504659,0.006676013,0.0011473984,0.00027413626,0.59099036],"genre_scores_gemma":[0.9837931,0.00064644346,0.009199751,0.00076886325,0.00013908681,0.00004433081,0.000031514337,0.000029964642,0.0053469795],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99495256,0.00012946143,0.0023052022,0.0010221275,0.0013769501,0.00021369671],"domain_scores_gemma":[0.9875363,0.010197061,0.0010578606,0.00042284024,0.00070454855,0.00008140366],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0010150984,0.0003587282,0.0010752043,0.00068777386,0.00006614317,0.00008642118,0.0009775236,0.00023627785,0.0003501786],"category_scores_gemma":[0.0066018747,0.0003126164,0.00020571663,0.00045794024,0.00065342884,0.00020597232,0.0006048747,0.0005697956,0.00026841584],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016546062,0.00018790875,0.006258447,0.000059902715,0.0001804869,0.00010677194,0.009739626,0.15947157,8.601451e-7,0.37623522,0.004406508,0.44318724],"study_design_scores_gemma":[0.00010326409,0.00014422392,0.0014601381,0.0007729114,0.000016864502,0.0000034235338,0.0023078062,0.0067811543,0.000010993587,0.984783,0.0033425821,0.00027365444],"about_ca_topic_score_codex":0.00006993022,"about_ca_topic_score_gemma":0.00037007447,"teacher_disagreement_score":0.74077994,"about_ca_system_score_codex":0.00024387772,"about_ca_system_score_gemma":0.00020268685,"threshold_uncertainty_score":0.9999326},"labels":[],"label_agreement":null},{"id":"W3100577619","doi":"10.3758/s13421-020-01112-7","title":"Harm to others reduces the sunk-cost effect","year":2020,"lang":"en","type":"article","venue":"Memory & Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; Kwantlen Polytechnic University","funders":"Social Sciences and Humanities Research Council of Canada; Canada Research Chairs; Deutsche Forschungsgemeinschaft; Kwantlen Polytechnic University","keywords":"Psychology; Harm; Sunk costs; Social psychology; Cognitive psychology; Economics; Microeconomics","score_opus":0.20925522979849376,"score_gpt":0.41764632780098426,"score_spread":0.2083910980024905,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3100577619","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9782839,0.000026421689,0.00045830943,0.008241736,0.00058355706,0.0004797459,0.00003512291,0.0000736379,0.011817596],"genre_scores_gemma":[0.9936047,0.0000029567548,0.00013413724,0.0055833673,0.00026404488,0.000043110653,0.0000074769364,0.000016427988,0.00034374194],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99800396,0.00023703724,0.00041874783,0.0005116296,0.0006139237,0.00021467594],"domain_scores_gemma":[0.99796426,0.0011958003,0.0001470499,0.00035007103,0.00015218736,0.00019062121],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0018533668,0.00015061157,0.00023747064,0.00010376188,0.0002458621,0.00046046608,0.00064866344,0.000060305418,0.0012177106],"category_scores_gemma":[0.002580472,0.000091409,0.00014567991,0.0005679514,0.00007611975,0.00024351463,0.000115579125,0.00016367191,0.008291316],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014247677,0.000023369836,0.0001057388,0.0000013891979,0.000006366516,0.000010496107,0.0009436923,0.00013601249,0.010538579,0.00000868634,0.029492678,0.9585905],"study_design_scores_gemma":[0.0033073407,0.0024029112,0.013493614,0.00022614634,0.0003526381,0.00007282247,0.012671552,0.0033013138,0.392021,0.034900613,0.5355562,0.0016938341],"about_ca_topic_score_codex":0.000011598118,"about_ca_topic_score_gemma":0.000010491324,"teacher_disagreement_score":0.95689666,"about_ca_system_score_codex":0.00002834243,"about_ca_system_score_gemma":0.000034628058,"threshold_uncertainty_score":0.9996953},"labels":[],"label_agreement":null},{"id":"W3100984816","doi":"10.31234/osf.io/mktgj","title":"Effect of Confidence Interval Construction on Judgment Accuracy","year":2020,"lang":"en","type":"article","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Confidence interval; Univariate; Statistics; Range (aeronautics); Skepticism; Interval (graph theory); Psychology; Expert elicitation; Mathematics; Social psychology; Engineering; Multivariate statistics; Epistemology","score_opus":0.1453684563854634,"score_gpt":0.42860886850240126,"score_spread":0.28324041211693785,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3100984816","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9878936,0.000007297961,0.0033906111,0.0011702067,0.0005422907,0.00013998644,0.0000075711114,0.00003273372,0.006815703],"genre_scores_gemma":[0.99867535,0.0000030963045,0.0006343645,0.0005478372,0.000044584158,0.0000028676125,6.8414e-7,0.0000047024837,0.00008649779],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9982022,0.00015267618,0.000604243,0.00037241305,0.0005561398,0.0001123312],"domain_scores_gemma":[0.99610305,0.0030765848,0.0002699724,0.0003328083,0.000105355146,0.00011221488],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0012911899,0.00010996246,0.0003246278,0.00008878443,0.000041587904,0.00012338287,0.00050245854,0.000050141993,0.001724979],"category_scores_gemma":[0.004321064,0.000068933026,0.000142169,0.00024860623,0.00010480355,0.00020329322,0.0001197424,0.000107424086,0.0012358795],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026183345,0.000019079727,0.0024060109,0.0000031874426,0.0000043570485,0.000004076965,0.000117461255,0.0001257156,0.0012295088,0.0016121243,0.004342414,0.98987424],"study_design_scores_gemma":[0.005163921,0.020246865,0.005978604,0.00035428652,0.00013682694,0.00009303274,0.003347373,0.028061345,0.7926285,0.07685158,0.06587164,0.001265989],"about_ca_topic_score_codex":0.000016072541,"about_ca_topic_score_gemma":0.0000024688784,"teacher_disagreement_score":0.98860824,"about_ca_system_score_codex":0.000021042908,"about_ca_system_score_gemma":0.000027457696,"threshold_uncertainty_score":0.99954176},"labels":[],"label_agreement":null},{"id":"W3102774394","doi":"","title":"A PREQUENTIAL TEST FOR EXCHANGEABLE THEORIES","year":2016,"lang":"en","type":"article","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Construct (python library); Test (biology); Probabilistic logic; Computer science; Econometrics; Mathematics; Artificial intelligence; Geology; Programming language","score_opus":0.16950472369260655,"score_gpt":0.4197963985967314,"score_spread":0.25029167490412485,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3102774394","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.73830837,0.00004104819,0.19760075,0.0039171223,0.0021786096,0.00044462067,0.00018104559,0.00014833486,0.057180103],"genre_scores_gemma":[0.9293212,0.0000042463744,0.0041383617,0.0001981848,0.00017055715,0.000036817506,6.326275e-7,0.000009952834,0.066120036],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99867564,0.000023169057,0.00038415048,0.00037700156,0.00031411776,0.00022590834],"domain_scores_gemma":[0.9948792,0.0042235004,0.00011430435,0.00048493547,0.00021930887,0.0000787864],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001536338,0.00009404316,0.00018119482,0.00011459395,0.00012480782,0.0002687926,0.0005472495,0.000058908703,0.0034226307],"category_scores_gemma":[0.004491638,0.00004347761,0.00012461646,0.00014493466,0.00009258105,0.00039235223,0.000103385966,0.00002158216,0.00144834],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003098697,0.000048183498,0.0020152875,4.9047026e-7,0.0000022282081,9.977367e-7,0.00004471777,7.188192e-7,0.0025160874,0.017601341,0.037584465,0.9401545],"study_design_scores_gemma":[0.0003395948,0.00011869846,0.00031329854,0.000008783086,0.0000048864854,0.000003709739,0.00010478236,0.00005083736,0.004328404,0.7402383,0.2543835,0.00010518795],"about_ca_topic_score_codex":0.000009763529,"about_ca_topic_score_gemma":0.000057912912,"teacher_disagreement_score":0.9400493,"about_ca_system_score_codex":0.000025746249,"about_ca_system_score_gemma":0.000044446115,"threshold_uncertainty_score":0.99932915},"labels":[],"label_agreement":null},{"id":"W3105916523","doi":"10.1002/bdm.2214","title":"Resistance to cognitive biases: Longitudinal trajectories and associations with cognitive abilities and academic achievement across development","year":2020,"lang":"en","type":"article","venue":"Journal of Behavioral Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Psychology; Cognition; Sophistication; Developmental psychology; Cognitive psychology; Cognitive bias; Cognitive development","score_opus":0.25177638378962885,"score_gpt":0.46229602915947454,"score_spread":0.2105196453698457,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3105916523","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98570627,0.00038829332,0.012690793,0.00048512622,0.0002253951,0.00030081894,0.00016098717,0.000017961027,0.00002433087],"genre_scores_gemma":[0.98281723,0.00003115612,0.016573237,0.00039194713,0.00011517855,0.000010016342,0.0000021000026,0.000025294052,0.00003384529],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9951529,0.00015968837,0.0018103245,0.00066387415,0.0018056291,0.00040758145],"domain_scores_gemma":[0.9904051,0.006210736,0.0012687619,0.00015850394,0.0014963264,0.00046057493],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028343496,0.00032490742,0.0007999209,0.00033399896,0.0005641156,0.000773835,0.00045825212,0.00015374318,0.000054658518],"category_scores_gemma":[0.0068374695,0.00023515362,0.00012085708,0.0007707115,0.00023275481,0.00096594566,0.00037570146,0.0005965284,0.000019872861],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018741069,0.00013547331,0.37023392,0.000004869468,0.00003857623,0.00015158649,0.017776474,0.0000595098,0.000117942356,0.00001844281,0.00033967258,0.6092494],"study_design_scores_gemma":[0.0021010798,0.0014700084,0.93932384,0.0024037391,0.00020819798,0.00013109592,0.04816121,0.000037959308,0.0005519005,0.0040148436,0.0009919443,0.00060421065],"about_ca_topic_score_codex":0.0000057357456,"about_ca_topic_score_gemma":0.00024189745,"teacher_disagreement_score":0.6086452,"about_ca_system_score_codex":0.00017027852,"about_ca_system_score_gemma":0.00024395938,"threshold_uncertainty_score":0.95892864},"labels":[],"label_agreement":null},{"id":"W3111313474","doi":"10.1016/j.jeconom.2020.11.003","title":"Optimal frequency of portfolio evaluation in a choice experiment with ambiguity and loss aversion","year":2020,"lang":"en","type":"article","venue":"Journal of Econometrics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Ambiguity aversion; Ambiguity; Econometrics; Portfolio; Loss aversion; Economics; Mathematics; Statistics; Computer science; Financial economics; Microeconomics","score_opus":0.38443441874916884,"score_gpt":0.39841937936487454,"score_spread":0.0139849606157057,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111313474","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9975145,0.0004956195,0.0007560704,0.0003337168,0.00018520534,0.00009772263,0.0000067492256,0.0000018312458,0.00060862314],"genre_scores_gemma":[0.9953872,0.000064440756,0.0043898397,0.00008115912,0.000062536215,8.599237e-7,5.063111e-7,0.0000059223216,0.000007526755],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9976852,0.000079419035,0.0011735947,0.00023342238,0.0007055665,0.00012282541],"domain_scores_gemma":[0.99726313,0.00059707754,0.0012602322,0.00017657068,0.000525589,0.00017739914],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034918624,0.00010133798,0.00043855622,0.0011417979,0.000031081498,0.0001105202,0.00036857423,0.00006307177,0.00039924998],"category_scores_gemma":[0.0031408619,0.00007409061,0.00008776386,0.0014739335,0.00006075022,0.0006520582,0.00007990209,0.00017035365,0.0000101925725],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022169127,0.0002811347,0.76385665,0.0000071918266,0.000026237682,0.00005854729,0.0010369779,0.0126655325,0.00026473956,0.000067156456,0.00079011935,0.22072405],"study_design_scores_gemma":[0.008627258,0.005214764,0.92304033,0.00018167048,0.00017843561,0.0002667643,0.005850883,0.03421143,0.0027034907,0.014585171,0.004433297,0.00070648803],"about_ca_topic_score_codex":0.000026698528,"about_ca_topic_score_gemma":0.000010111369,"teacher_disagreement_score":0.22001755,"about_ca_system_score_codex":0.00014583205,"about_ca_system_score_gemma":0.00018636326,"threshold_uncertainty_score":0.43715072},"labels":[],"label_agreement":null},{"id":"W3113583650","doi":"10.1177/0952695120976330","title":"The past of predicting the future: A review of the multidisciplinary history of affective forecasting","year":2020,"lang":"en","type":"review","venue":"History of the Human Sciences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Multidisciplinary approach; Utilitarianism; Affect (linguistics); TRACE (psycholinguistics); Psychology; Cognition; Order (exchange); Cognitive psychology; Social psychology; Positive economics; Epistemology; Economics; Sociology; Social science; Philosophy","score_opus":0.30838342556340076,"score_gpt":0.4150042689328311,"score_spread":0.10662084336943034,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3113583650","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0013670537,0.98550886,0.0000043441555,0.00026515138,0.005935253,0.0010104455,0.000049979866,0.000009463371,0.005849464],"genre_scores_gemma":[0.003987935,0.99149436,0.00016557473,0.0000905172,0.0004182991,0.000060075494,0.0000012922179,0.00003617424,0.00374575],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9923296,0.001698128,0.002731658,0.0007225311,0.0022277203,0.00029038574],"domain_scores_gemma":[0.98327816,0.0053646453,0.008854123,0.0019480761,0.0004917184,0.00006330341],"candidate_categories":["sts","open_science"],"consensus_categories":[],"category_scores_codex":[0.013297284,0.00038906687,0.0019653304,0.00019761472,0.0008252496,0.000028649118,0.00844159,0.00014453703,0.00007567606],"category_scores_gemma":[0.003890137,0.0001426137,0.0017357029,0.0012229613,0.006444939,0.00019590449,0.0016934704,0.0006129781,0.000005346456],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000061241713,0.000060057635,0.00019389676,0.0038006217,0.000036143956,7.73958e-7,0.0031749224,0.00001299346,0.0000090413005,0.0003060549,0.048648972,0.9437504],"study_design_scores_gemma":[0.0000623494,0.000121831916,0.00015842867,0.024606744,0.00038885046,0.000017280794,0.001076406,0.00008609001,0.0000017801075,0.0012842137,0.9720319,0.00016410758],"about_ca_topic_score_codex":0.00006570246,"about_ca_topic_score_gemma":0.00011306852,"teacher_disagreement_score":0.9435863,"about_ca_system_score_codex":0.0009775466,"about_ca_system_score_gemma":0.0024867428,"threshold_uncertainty_score":0.9969232},"labels":[],"label_agreement":null},{"id":"W3113686433","doi":"10.23919/eusipco47968.2020.9287384","title":"Assessing Risks of Biases in Cognitive Decision Support Systems","year":2020,"lang":"en","type":"article","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Probabilistic logic; Computer science; Component (thermodynamics); Biometrics; Decision support system; Process (computing); Cognitive bias; Cognition; Face (sociological concept); Risk analysis (engineering); Facial recognition system; Machine learning; Artificial intelligence; Feature extraction; Psychology","score_opus":0.6861791172779647,"score_gpt":0.5509767838581452,"score_spread":0.13520233341981946,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3113686433","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97866243,0.00005368566,0.011391038,0.00013896628,0.00039606818,0.00016360961,0.000028579276,0.000029776684,0.009135857],"genre_scores_gemma":[0.9982245,0.000008049788,0.0013816081,0.0002368656,0.000045676934,0.0000040825753,0.0000037923587,0.000010571702,0.00008483831],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99688,0.00013826738,0.0013269606,0.00055268174,0.0008681197,0.00023396917],"domain_scores_gemma":[0.99256015,0.006203222,0.00041650585,0.00029408044,0.00034382296,0.00018223665],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002482008,0.0001420382,0.0005346763,0.00033411282,0.000053158776,0.0005337401,0.0005443645,0.00010364477,0.0010853991],"category_scores_gemma":[0.011549002,0.000101007754,0.00012717718,0.0009258314,0.00008175123,0.00078080787,0.00020356517,0.00014678188,0.0005203044],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009139884,0.00010901238,0.07912214,0.0000028696325,0.000004628469,0.00006228967,0.00038663845,0.0019214519,0.0002536334,0.00006612625,0.0031574161,0.9148224],"study_design_scores_gemma":[0.008914017,0.0025130364,0.41843107,0.0025157128,0.00018947564,0.00015311378,0.13394907,0.35542092,0.01170405,0.044850845,0.018716298,0.0026423777],"about_ca_topic_score_codex":0.00019537355,"about_ca_topic_score_gemma":0.00004989189,"teacher_disagreement_score":0.91218,"about_ca_system_score_codex":0.000031462292,"about_ca_system_score_gemma":0.00014843023,"threshold_uncertainty_score":0.99982774},"labels":[],"label_agreement":null},{"id":"W3118559982","doi":"10.1109/cdc42340.2020.9303898","title":"Mean field social optimization: feedback person-by-person optimality and the master equation","year":2020,"lang":"en","type":"article","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Field (mathematics); Mathematical optimization; Measure (data warehouse); Dynamic programming; Computer science; Hamilton–Jacobi–Bellman equation; Quadratic programming; Optimization problem; Mathematics; Quadratic equation; Applied mathematics; Bellman equation","score_opus":0.2694410763813087,"score_gpt":0.35954635642446636,"score_spread":0.09010528004315765,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3118559982","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.43775922,0.00011508603,0.3142142,0.20607795,0.00043294212,0.00043147604,0.000030123596,0.000098512864,0.040840495],"genre_scores_gemma":[0.98739445,0.000005920522,0.0047769514,0.0060656182,0.0001665948,0.0000054619436,0.0000049652213,0.000008855636,0.0015711676],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99836844,0.00016964284,0.0003553996,0.00043689672,0.0005145175,0.00015507604],"domain_scores_gemma":[0.99840564,0.0009857771,0.00017200274,0.00021111319,0.00012842336,0.000097054464],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0013331699,0.00012707394,0.0002533813,0.00003536489,0.00031638387,0.000720051,0.00042012436,0.000097503085,0.003233648],"category_scores_gemma":[0.0007945582,0.00007459743,0.000113172246,0.00025350638,0.000111883026,0.00036094256,0.00009108307,0.00013618557,0.00020037922],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00082274555,0.000073561016,0.003064573,0.00000560436,0.00003327485,0.000004400271,0.02087843,0.007920177,0.000064612796,0.0043554334,0.39211446,0.57066274],"study_design_scores_gemma":[0.0031467348,0.00022991435,0.00067410903,0.000008677953,0.00006367125,0.000007094236,0.029138355,0.9486692,0.00021055512,0.005828145,0.011530737,0.0004927837],"about_ca_topic_score_codex":0.00006601454,"about_ca_topic_score_gemma":0.000013572244,"teacher_disagreement_score":0.94074905,"about_ca_system_score_codex":0.000024632709,"about_ca_system_score_gemma":0.000027042544,"threshold_uncertainty_score":0.9976775},"labels":[],"label_agreement":null},{"id":"W3119219909","doi":"10.3758/s13423-020-01848-y","title":"Confidence in risky value-based choice","year":2021,"lang":"en","type":"article","venue":"Psychonomic Bulletin & Review","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Wellcome Trust","keywords":"Psychology; Value (mathematics); Certainty; Confidence interval; Context (archaeology); Social psychology; Overconfidence effect; Perception; Cognitive psychology; Statistics","score_opus":0.14896986695084452,"score_gpt":0.4449513080087829,"score_spread":0.2959814410579384,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3119219909","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4469243,0.35481948,0.004715215,0.12540475,0.0077426075,0.0020947228,0.000103425446,0.00023877817,0.057956744],"genre_scores_gemma":[0.7615357,0.10249389,0.025290607,0.09867216,0.0008145233,0.00038010246,0.00005114865,0.00018474035,0.010577102],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9955107,0.0005681695,0.0017724565,0.0011848984,0.00055295235,0.00041082967],"domain_scores_gemma":[0.9947319,0.0025566926,0.0005463801,0.0017253433,0.00024457465,0.00019509143],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0048347325,0.00028113287,0.00094527495,0.00017936583,0.00009396511,0.00030198094,0.0012615068,0.0001170527,0.013834824],"category_scores_gemma":[0.0047304365,0.00024032533,0.00038069728,0.0007862964,0.000102979844,0.00009778915,0.00014381565,0.00036132667,0.015391745],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001962428,0.00022325345,0.0038780335,0.000104368744,0.0000069366797,0.00005451186,0.000020265863,0.00018520442,0.000044039723,0.00078065286,0.23864092,0.7560422],"study_design_scores_gemma":[0.0005199272,0.000024311743,0.0037817392,0.002042641,0.000025079786,0.000024342784,0.00002754519,0.00015997242,0.00004242554,0.010342593,0.9827079,0.00030151376],"about_ca_topic_score_codex":0.00012565374,"about_ca_topic_score_gemma":0.00007783003,"teacher_disagreement_score":0.75574064,"about_ca_system_score_codex":0.00012743656,"about_ca_system_score_gemma":0.00026055344,"threshold_uncertainty_score":0.9870667},"labels":[],"label_agreement":null},{"id":"W3121210304","doi":"10.1287/moor.2015.0736","title":"Local Utility and Multivariate Risk Aversion","year":2016,"lang":"en","type":"article","venue":"Mathematics of Operations Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Multivariate statistics; Multivariate analysis; Expected utility hypothesis; Independence (probability theory); Risk aversion (psychology); Risk measure; Measure (data warehouse); Rank (graph theory); Extension (predicate logic)","score_opus":0.3745943975959188,"score_gpt":0.5166390033561686,"score_spread":0.14204460576024985,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3121210304","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8901276,0.00001713962,0.10772442,0.00043792254,0.000050619477,0.00018128804,0.000058512393,0.000009923269,0.0013925724],"genre_scores_gemma":[0.9802708,0.000035731315,0.018405907,0.000004036338,0.000011893632,0.0000080267655,6.095003e-7,0.0000071411105,0.001255824],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.997493,0.00030808666,0.00062226213,0.00033538914,0.0010344591,0.00020674506],"domain_scores_gemma":[0.9946096,0.0035889433,0.000067434376,0.00074293977,0.0008797631,0.00011130702],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.008730515,0.00008100226,0.00022817541,0.0003431593,0.00035468308,0.00020621464,0.0005028845,0.000076863675,0.00085658295],"category_scores_gemma":[0.008871023,0.00004377466,0.000056148365,0.00038041951,0.00049799535,0.0003154853,0.0004046988,0.00014765516,0.0006009173],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030470846,0.0003567899,0.0022983542,0.000008610032,0.0000103305565,0.0000029150551,0.0013568082,0.00021655005,0.0051668817,0.0071638743,0.0018042297,0.9815842],"study_design_scores_gemma":[0.0014396138,0.00036071177,0.012024655,0.00021456087,0.00001986687,0.000017557097,0.0058325785,0.33855203,0.0131098,0.62147164,0.006627627,0.00032936348],"about_ca_topic_score_codex":0.00014168526,"about_ca_topic_score_gemma":0.000121876794,"teacher_disagreement_score":0.9812548,"about_ca_system_score_codex":0.000038967,"about_ca_system_score_gemma":0.00009017285,"threshold_uncertainty_score":0.9994777},"labels":[],"label_agreement":null},{"id":"W3121263656","doi":"10.1111/j.1559-1816.2008.00432.x","title":"The Effect of Incentive Structure on Heuristic Decision Making: The Proportion Heuristic<sup>1</sup>","year":2009,"lang":"en","type":"article","venue":"Journal of Applied Social Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Heuristics; Incentive; Heuristic; Compensation (psychology); Psychology; Test (biology); Social psychology; Computer science; Operations research; Cognitive psychology; Artificial intelligence; Microeconomics; Economics; Mathematics","score_opus":0.038334182065178406,"score_gpt":0.4239470602971141,"score_spread":0.3856128782319357,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3121263656","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99174166,0.00006761315,0.0021644637,0.0018201704,0.0010269615,0.00031083514,0.000012147826,0.0000086569025,0.0028474727],"genre_scores_gemma":[0.9984271,0.00002028367,0.00028938512,0.0006682879,0.0005599813,0.0000021395817,7.4098136e-7,0.000013339788,0.000018758785],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9959915,0.00039898892,0.0016171675,0.00035706622,0.0013214584,0.00031376604],"domain_scores_gemma":[0.9929547,0.003912589,0.0021521451,0.0005021516,0.00040622576,0.000072246534],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004727871,0.00023241967,0.0006701333,0.00023775615,0.0006178116,0.00019443876,0.0013887167,0.0002592956,0.000084054314],"category_scores_gemma":[0.0019102324,0.00010815036,0.00034396618,0.0005416411,0.00041091983,0.000092224625,0.00006765985,0.0007813267,0.000048475238],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0040816767,0.00009240985,0.0005228587,0.0000011989775,0.000028793178,0.000020832682,0.0007740236,0.0008385018,0.0002298322,0.0023339672,0.024067365,0.96700853],"study_design_scores_gemma":[0.0019521659,0.0030124702,0.057379536,0.000054411135,0.00012034487,0.00009545966,0.0009486341,0.00019427098,0.00030678968,0.9223973,0.013308587,0.0002300404],"about_ca_topic_score_codex":6.313653e-7,"about_ca_topic_score_gemma":0.0000020011203,"teacher_disagreement_score":0.9667785,"about_ca_system_score_codex":0.0000909224,"about_ca_system_score_gemma":0.000069186746,"threshold_uncertainty_score":0.47517696},"labels":[],"label_agreement":null},{"id":"W3121266462","doi":"10.4018/ijsds.2011040101","title":"Strategic Diffusion of Information and Preference Manipulation","year":2011,"lang":"en","type":"article","venue":"International Journal of Strategic Decision Sciences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Lexicographical order; Preference; Computer science; Communication source; Decision maker; Verifiable secret sharing; Preference relation; Relation (database); Mathematical economics; Revealed preference; Operations research; Microeconomics; Mathematics; Economics; Data mining","score_opus":0.4893803146272365,"score_gpt":0.42394793504141537,"score_spread":0.06543237958582115,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3121266462","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97975504,0.0000732048,0.007026662,0.00008313857,0.0015064023,0.000068150126,0.000013934231,0.0000063592915,0.011467093],"genre_scores_gemma":[0.98630357,0.00011493371,0.013455446,0.000048016693,0.000059553724,6.980145e-7,0.0000011494107,0.0000032485248,0.000013412067],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.994855,0.00007735109,0.0020322558,0.00024652114,0.0026337414,0.00015516944],"domain_scores_gemma":[0.9947805,0.000838978,0.0021148697,0.00021311508,0.0019183599,0.00013417061],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0045591006,0.00014916855,0.0003347024,0.0011909801,0.00011346307,0.0006076334,0.0017790056,0.000095294905,0.0005576805],"category_scores_gemma":[0.0008318071,0.000095931966,0.00013735455,0.00057369965,0.00035185754,0.002862884,0.00019404439,0.0001635279,0.000049057395],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006186733,0.00026091415,0.028995069,0.000003335106,0.000031949967,0.00003341041,0.0016403802,0.00076340005,0.0012977982,0.0810182,0.00020083888,0.885136],"study_design_scores_gemma":[0.0005604194,0.00050924363,0.04273967,0.00011461448,0.000012477743,0.00021690404,0.0043688435,0.0031707198,0.0004630388,0.94743586,0.00027499616,0.00013320209],"about_ca_topic_score_codex":0.00006810959,"about_ca_topic_score_gemma":0.000020184001,"teacher_disagreement_score":0.88500285,"about_ca_system_score_codex":0.000039083872,"about_ca_system_score_gemma":0.00026517746,"threshold_uncertainty_score":0.61062104},"labels":[],"label_agreement":null},{"id":"W3121427863","doi":"10.1017/s1930297500007695","title":"Performance on the Cognitive Reflection Test is stable across time","year":2018,"lang":"en","type":"article","venue":"Judgment and Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":110,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Conservatism; Psychology; Cognition; Test (biology); Cognitive psychology; Set (abstract data type); Cognitive style; Stability (learning theory); Reflection (computer programming); Social psychology; Computer science; Machine learning","score_opus":0.14685114588288914,"score_gpt":0.4260042680523236,"score_spread":0.27915312216943444,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3121427863","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9832978,0.000030594238,0.00091957755,0.00036520825,0.0005613264,0.00022186611,0.000030939573,0.00004371313,0.014528944],"genre_scores_gemma":[0.9948418,0.000024567917,0.00090755743,0.0020614786,0.00024168829,0.000011998851,8.954928e-7,0.000017800456,0.0018921997],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9970456,0.000050596085,0.0006710369,0.00072456716,0.0011132628,0.0003949882],"domain_scores_gemma":[0.99274254,0.0058381464,0.00032914092,0.00058718765,0.00041381692,0.00008915747],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0033735975,0.00022321257,0.0002883868,0.00019039842,0.0012649847,0.0010645292,0.0005056196,0.00011569717,0.0020595929],"category_scores_gemma":[0.0020938972,0.00012967428,0.00010041561,0.0006531615,0.00022984429,0.00044838147,0.0003592041,0.00021225015,0.0057972525],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025335158,0.00006985075,0.009409419,6.6834866e-7,0.000005292342,0.0000030892438,0.00065335317,0.000009357773,0.00020758469,0.000032923796,0.023453288,0.9659018],"study_design_scores_gemma":[0.0040826392,0.005661898,0.18272382,0.0025227866,0.00013267972,0.00017647918,0.008663177,0.18899617,0.013445597,0.3928054,0.19838102,0.0024083466],"about_ca_topic_score_codex":0.0000041740004,"about_ca_topic_score_gemma":0.000012749331,"teacher_disagreement_score":0.96349347,"about_ca_system_score_codex":0.00006984408,"about_ca_system_score_gemma":0.000032256743,"threshold_uncertainty_score":0.99997246},"labels":[],"label_agreement":null},{"id":"W3121430297","doi":"","title":"Rationality, External Norms and the Epistemic Value of Menus","year":2008,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Rationality; Rationalizability; Epistemology; Norm (philosophy); Decision maker; Value (mathematics); Mathematical economics; Autonomy; Preference; Social psychology; Psychology; Mathematics; Economics; Microeconomics; Philosophy; Management science; Political science","score_opus":0.13718959150118637,"score_gpt":0.42977059897093484,"score_spread":0.29258100746974847,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3121430297","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9731488,0.00031266676,0.000034412646,0.0010080514,0.00064106344,0.00061713235,0.000096537085,0.000011350104,0.024129976],"genre_scores_gemma":[0.9886263,0.008503496,0.0009401398,0.00008778582,0.00017329467,0.0000819873,0.000009774098,0.000030038864,0.0015472026],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9942669,0.000951359,0.0020210694,0.0011721068,0.0010873687,0.0005011732],"domain_scores_gemma":[0.98968583,0.0071062376,0.0008121898,0.0018410622,0.00038210652,0.00017259453],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01458959,0.00029815387,0.0010162599,0.0006545003,0.00026671964,0.00044028135,0.0022284572,0.0003895805,0.00011801727],"category_scores_gemma":[0.0042421254,0.00020330717,0.0003435434,0.00021573456,0.0018852088,0.00018238857,0.002793934,0.0014304484,0.000033466866],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004675085,0.000144434,0.017290674,0.000027814274,0.000046575475,0.000034504657,0.0009081147,0.017789437,0.000056104764,0.006931755,0.00018613393,0.956117],"study_design_scores_gemma":[0.0025717905,0.000111498266,0.035906576,0.00033954292,0.000019684981,0.00017406391,0.00095435506,0.04708536,0.00015150943,0.9012306,0.010862713,0.000592322],"about_ca_topic_score_codex":0.00027318203,"about_ca_topic_score_gemma":0.00017311568,"teacher_disagreement_score":0.9555246,"about_ca_system_score_codex":0.00040408256,"about_ca_system_score_gemma":0.00077127584,"threshold_uncertainty_score":0.8290625},"labels":[],"label_agreement":null},{"id":"W3121432893","doi":"","title":"On the Necessity of Using Lottery Qualities","year":2004,"lang":"en","type":"article","venue":"Cahiers de recherche","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Lottery; Key (lock); Element (criminal law); Point (geometry); Prospect theory; Expected utility hypothesis; Decision theory; Computer science; Mathematical economics; Management science; Economics; Risk analysis (engineering); Microeconomics; Mathematics; Business; Computer security; Political science; Law","score_opus":0.7214948118791766,"score_gpt":0.5356992069958036,"score_spread":0.185795604883373,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3121432893","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9768632,0.000054991422,0.015898293,0.0011438045,0.00022840036,0.000071852875,0.000009135964,0.000018708586,0.0057116128],"genre_scores_gemma":[0.99052024,0.000012253949,0.0075458465,0.0011800956,0.000038771366,0.000002199678,3.986877e-7,0.000010541972,0.00068967586],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9975274,0.0011209976,0.00045344027,0.00025992063,0.00043058017,0.00020765472],"domain_scores_gemma":[0.9899322,0.008981226,0.00024314098,0.0006368718,0.00013232064,0.00007426787],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.014318457,0.00011026584,0.00023838821,0.00013364198,0.00015060494,0.00013647552,0.00075142656,0.00035311212,0.00015893989],"category_scores_gemma":[0.013260955,0.00006625067,0.000153135,0.00046594406,0.00036961882,0.00013896651,0.000057758873,0.0006716924,0.00010577467],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029328818,0.00045659227,0.0036660607,0.000017907907,0.00006265081,0.000047015015,0.027472012,0.0133815445,0.013218131,0.1610596,0.005865053,0.77446014],"study_design_scores_gemma":[0.0001676606,0.000041208255,0.00040014973,0.00004686404,0.00001112612,0.000010914683,0.004643981,0.0002119902,0.008424388,0.9851055,0.00082429993,0.00011193064],"about_ca_topic_score_codex":0.000088308356,"about_ca_topic_score_gemma":0.000013632024,"teacher_disagreement_score":0.8240459,"about_ca_system_score_codex":0.0006431203,"about_ca_system_score_gemma":0.00028891885,"threshold_uncertainty_score":0.9950508},"labels":[],"label_agreement":null},{"id":"W3121488803","doi":"10.1007/s10683-006-1467-1","title":"An experimental examination of the house money effect in a multi-period setting","year":2006,"lang":"en","type":"article","venue":"Experimental Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":153,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Economics; Cash; Monetary economics; Endowment; Period (music); Money market; Endowment effect; Microeconomics; Monetary policy; Finance","score_opus":0.05563209705592237,"score_gpt":0.3709444316091812,"score_spread":0.31531233455325886,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3121488803","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.997863,0.00018704864,0.000036208534,0.00003591187,0.0006484102,0.00037728477,0.00002159428,0.000041719395,0.00078882906],"genre_scores_gemma":[0.9984089,0.0000011825515,0.0012937025,0.000065015236,0.00006457131,0.000043742166,0.0000052693213,0.00004082377,0.00007676892],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9974795,0.00029373314,0.0010683514,0.0006233141,0.00025168117,0.00028339677],"domain_scores_gemma":[0.99835545,0.0002596844,0.00048167675,0.00079677673,0.000032723645,0.00007370577],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016349143,0.00024636017,0.00041964548,0.00024207261,0.00016010147,0.0002650425,0.0009066359,0.00012702703,0.0001254566],"category_scores_gemma":[0.00010304821,0.00018990645,0.00019700537,0.000225445,0.0001782841,0.00070742494,0.00023151877,0.0001424693,0.000085403575],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035642792,0.004806127,0.160724,0.0000067380815,0.00002042056,0.000024034762,0.012290474,0.0248225,0.653339,0.0015228927,0.0005714942,0.14151588],"study_design_scores_gemma":[0.002163797,0.00040083576,0.07095014,0.000025278328,0.000005780549,0.000016917507,0.007192486,0.032994065,0.8847904,0.0008117035,0.00024120767,0.0004073804],"about_ca_topic_score_codex":0.00025122988,"about_ca_topic_score_gemma":0.00015687606,"teacher_disagreement_score":0.23145139,"about_ca_system_score_codex":0.00037931153,"about_ca_system_score_gemma":0.000052657815,"threshold_uncertainty_score":0.774416},"labels":[],"label_agreement":null},{"id":"W3121500403","doi":"","title":"Efficient and Non-Deteriorating Choice","year":2002,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Rationalizability; Generalization; Preference; Choice function; Status quo; Mathematical economics; Revealed preference; Set (abstract data type); Function (biology); Selection (genetic algorithm); Mathematics; Choice set; Domain (mathematical analysis); Economics; Mathematical optimization; Computer science; Econometrics; Microeconomics; Nash equilibrium; Artificial intelligence","score_opus":0.15019257303669334,"score_gpt":0.43092029617688643,"score_spread":0.2807277231401931,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3121500403","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9494507,0.00012974943,0.000011485259,0.00029187062,0.0009781509,0.00059209357,0.000070248876,0.000034186975,0.048441555],"genre_scores_gemma":[0.99469376,0.0008650829,0.0016164127,0.0000838593,0.00028816934,0.000094895426,0.000006714393,0.000065238244,0.0022858966],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99356335,0.0004328031,0.0018562468,0.002215895,0.0009286491,0.0010030543],"domain_scores_gemma":[0.99198556,0.004483799,0.000605644,0.0022037595,0.00031917926,0.00040205516],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0087856725,0.00046457027,0.0010514738,0.0013818244,0.00037372098,0.0016841666,0.001974648,0.00064321625,0.00040416123],"category_scores_gemma":[0.0055484553,0.0004275413,0.00026682514,0.00036212173,0.0005282008,0.0001250646,0.0038558561,0.002156541,0.0001982282],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025055491,0.0001212007,0.011607343,0.00001990414,0.000012673929,0.000038376256,0.00044599583,0.026255187,0.00007981395,0.000013972538,0.00014045848,0.96124],"study_design_scores_gemma":[0.0016711404,0.0003445372,0.055021565,0.0007391398,0.000021938391,0.00006163233,0.0027939614,0.84794044,0.000098144556,0.025826635,0.063578404,0.0019024407],"about_ca_topic_score_codex":0.00011877356,"about_ca_topic_score_gemma":0.000288643,"teacher_disagreement_score":0.9593376,"about_ca_system_score_codex":0.00070333056,"about_ca_system_score_gemma":0.00033231906,"threshold_uncertainty_score":0.9998176},"labels":[],"label_agreement":null},{"id":"W3121513386","doi":"10.5539/ijef.v12n2p1","title":"Does Reminding of Behavioural Biases Increase Returns from Financial Trading? A Field Experiment","year":2020,"lang":"en","type":"article","venue":"International Journal of Economics and Finance","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Portfolio; Incentive; Status quo; Psychological intervention; Set (abstract data type); Status quo bias; Economics; Behavioral economics; Finance; Business; Psychology; Microeconomics; Computer science","score_opus":0.14843089232090467,"score_gpt":0.35754879132001105,"score_spread":0.20911789899910638,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3121513386","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9952686,0.00018634554,0.00013020556,0.002759465,0.0013531774,0.000034496552,0.00014619876,0.0000018396207,0.00011970305],"genre_scores_gemma":[0.9968158,0.0005021985,0.0017788275,0.00050058414,0.00037176185,8.5553063e-7,0.0000021676792,0.0000061839864,0.00002163274],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9983998,0.000023929455,0.0010552914,0.00022981987,0.00019588559,0.00009530284],"domain_scores_gemma":[0.9977599,0.0007497376,0.0010614013,0.00012437179,0.00022150045,0.00008309205],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004701708,0.000108218475,0.00037098143,0.00014105099,0.000038398455,0.00017211707,0.0006798582,0.00006762241,0.00014174618],"category_scores_gemma":[0.001590504,0.00007373257,0.00017410243,0.000057494166,0.000055966797,0.0004040234,0.00012179831,0.00014791521,0.0000041028375],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002260372,0.00036836523,0.10398904,0.0000026398445,0.00011939387,0.00029499936,0.0054883854,0.0018226837,0.0023915283,0.0052242368,0.007955483,0.87008286],"study_design_scores_gemma":[0.010328617,0.0036746876,0.10172996,0.0012217948,0.00023229964,0.00041344145,0.0058080023,0.08345019,0.16231516,0.47974563,0.14908412,0.0019961104],"about_ca_topic_score_codex":0.0001101225,"about_ca_topic_score_gemma":0.000041576368,"teacher_disagreement_score":0.86808676,"about_ca_system_score_codex":0.00004966888,"about_ca_system_score_gemma":0.00010662765,"threshold_uncertainty_score":0.30067268},"labels":[],"label_agreement":null},{"id":"W3121584422","doi":"","title":"Applying Behavioral Economics to Public Policy in Canada","year":2016,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Canadian Institute for Advanced Research; University of Toronto","funders":"","keywords":"Download; Behavioral economics; Government (linguistics); Behavioural economics; Public policy; Public economics; Field (mathematics); Economics; Point (geometry); Behavioural sciences; Developing country; Positive economics; Political science; Sociology; Economic growth; Social science; Microeconomics; Computer science","score_opus":0.07068466798682037,"score_gpt":0.35615136113545387,"score_spread":0.2854666931486335,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3121584422","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9900983,0.000095572104,0.0015003382,0.007159354,0.00053624116,0.00017403594,0.000017933195,0.000009386401,0.00040881624],"genre_scores_gemma":[0.99800235,0.00027809324,0.00012156232,0.0004802597,0.00026206998,0.000023086062,5.38298e-7,0.000024000574,0.0008080191],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9952011,0.00011566155,0.0010179402,0.00048269963,0.00052091916,0.002661645],"domain_scores_gemma":[0.9982739,0.0003795324,0.00032842782,0.00049995625,0.00014278608,0.00037538202],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0045828274,0.00020288242,0.0003768562,0.0008684041,0.00018840183,0.00036969213,0.0014151791,0.00007394251,0.00016023831],"category_scores_gemma":[0.00085594517,0.000135144,0.00012639552,0.00066902174,0.000033717995,0.0006404985,0.00018553111,0.00074381917,0.00029380497],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":true,"study_design_scores_codex":[0.000020942014,0.000029482777,0.05159813,9.560962e-8,0.0000052344512,0.0000075839394,0.000021583106,0.000069132446,0.000063795575,0.0076097394,0.00034999073,0.9402243],"study_design_scores_gemma":[0.0009441941,0.00021793017,0.0065450515,0.00002246216,0.000007410483,0.0004487219,0.0031320767,0.000061053855,0.0000584682,0.9173504,0.07076185,0.0004503506],"about_ca_topic_score_codex":0.425546,"about_ca_topic_score_gemma":0.984506,"teacher_disagreement_score":0.9397739,"about_ca_system_score_codex":0.012198415,"about_ca_system_score_gemma":0.028717006,"threshold_uncertainty_score":0.9915936},"labels":[],"label_agreement":null},{"id":"W3121722981","doi":"10.1007/s11238-017-9612-1","title":"Confidence biases and learning among intuitive Bayesians","year":2018,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Center for Interuniversity Research and Analysis on Organizations","funders":"","keywords":"Overconfidence effect; Contrarian; Bayesian probability; Task (project management); Perception; Conservatism; Phenomenon; Computer science; Artificial intelligence; Cognitive psychology; Probabilistic logic; Psychology; Machine learning; Social psychology; Economics","score_opus":0.05195641067456367,"score_gpt":0.31595005995896197,"score_spread":0.2639936492843983,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3121722981","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90191483,0.00010411775,0.053553432,0.0016146611,0.00014409322,0.00011898013,0.000010828025,0.000100725956,0.04243835],"genre_scores_gemma":[0.9820365,0.000058510024,0.010754952,0.00010829274,0.00002542583,0.000008345439,0.000010055944,0.000017520746,0.0069804504],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99461865,0.0033319485,0.0005494618,0.0007016372,0.0005182426,0.00028007134],"domain_scores_gemma":[0.98775166,0.0083431,0.000407706,0.0010358792,0.002255388,0.00020623833],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.010587196,0.00017540182,0.00027131685,0.00024193154,0.00075604627,0.00090500974,0.0009294965,0.00010987528,0.00060965517],"category_scores_gemma":[0.019710928,0.00015484722,0.000091329406,0.00060692494,0.0008893802,0.00047027745,0.00052940624,0.0003001174,0.0003088562],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016359756,0.00016515015,0.064940415,0.0000028865998,0.000013060612,0.000007643484,0.011369417,0.000013290517,0.0014450062,0.020122966,0.0013820807,0.9005217],"study_design_scores_gemma":[0.0024928655,0.000019150479,0.41325524,0.0029950698,0.000113737566,0.00013699604,0.011417091,0.1000942,0.098651834,0.22587349,0.14270562,0.0022447284],"about_ca_topic_score_codex":0.0005445635,"about_ca_topic_score_gemma":0.0019278168,"teacher_disagreement_score":0.898277,"about_ca_system_score_codex":0.000040429728,"about_ca_system_score_gemma":0.00008577353,"threshold_uncertainty_score":0.9885465},"labels":[],"label_agreement":null},{"id":"W3121876819","doi":"","title":"Measuring the Output and Prices of the Lottery Sector: An Application of Implicit Expected Utility Theory","year":2008,"lang":"en","type":"article","venue":"National Bureau of Economic Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Lottery; Economics; Index (typography); Econometrics; Parametric statistics; Price index; Yield (engineering); Microeconomics; Marginal utility; Expected utility hypothesis; Metric (unit); Mathematical economics; Mathematics; Statistics; Computer science; Operations management","score_opus":0.6108723953484728,"score_gpt":0.5283074552787898,"score_spread":0.08256494006968307,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3121876819","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9915558,0.00009376422,0.00015487864,0.00025266665,0.00006857689,0.00028139906,0.000031751544,0.0000045972624,0.007556557],"genre_scores_gemma":[0.99966323,0.000015524582,0.00012758133,0.000015191394,0.000054149164,0.000017585353,0.0000028424633,0.000006663512,0.000097250246],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9972928,0.00040835174,0.00077888754,0.00036151757,0.0010038906,0.00015452768],"domain_scores_gemma":[0.9940068,0.0039257403,0.0004435522,0.0006704228,0.0009039048,0.000049571816],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009358001,0.00008346233,0.0002533128,0.00028862015,0.00023274974,0.000041916566,0.0011413394,0.00007770018,0.0000909224],"category_scores_gemma":[0.0017223146,0.000048777565,0.000099919685,0.0003097443,0.00075629423,0.00026404747,0.00026809936,0.00018849512,0.000014472778],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00070272194,0.00065271754,0.34302178,0.000034451838,0.000110512716,6.9908407e-7,0.004403772,0.0023706506,0.021078989,0.31598604,0.0027883125,0.30884936],"study_design_scores_gemma":[0.00020701822,0.00005180407,0.29141796,0.000009504603,0.0000038286344,0.000008508407,0.00059608865,0.0032711658,0.004593682,0.69947404,0.00030532447,0.00006107457],"about_ca_topic_score_codex":0.00028689372,"about_ca_topic_score_gemma":0.00011570335,"teacher_disagreement_score":0.383488,"about_ca_system_score_codex":0.000092311835,"about_ca_system_score_gemma":0.00032541552,"threshold_uncertainty_score":0.3243315},"labels":[],"label_agreement":null},{"id":"W3122068380","doi":"10.1509/jmkr.47.6.1070","title":"Can Uncertainty Improve Promotions?","year":2010,"lang":"en","type":"article","venue":"Journal of Marketing Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":194,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Incentive; Marketing; Business; Economics; Microeconomics","score_opus":0.22681476193033015,"score_gpt":0.504219783122352,"score_spread":0.27740502119202193,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3122068380","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98856264,0.000022013493,0.00003324789,0.0051706703,0.0014622003,0.00011094236,0.000008110015,0.000007472659,0.0046227057],"genre_scores_gemma":[0.9959284,0.000013973487,0.0015891904,0.000036268717,0.00056841114,0.0000022833285,2.813997e-7,0.000013077028,0.0018481213],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9937362,0.001517361,0.0011635077,0.00031542152,0.0027457506,0.0005217346],"domain_scores_gemma":[0.98128015,0.01351618,0.0006332865,0.0006683846,0.003570081,0.0003319134],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.13362125,0.000105057086,0.00031367628,0.00091160065,0.00037344787,0.0007755674,0.0015931375,0.00013071808,0.0012625188],"category_scores_gemma":[0.09940202,0.00006907184,0.00021222861,0.0008437949,0.00025285193,0.00029026714,0.00031204306,0.0020904194,0.00014343075],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037098702,0.00014714318,0.01209827,0.0000033434105,0.000009787484,0.00006512717,0.00019247101,0.000041752453,0.010825232,0.00012095677,0.02012002,0.9560049],"study_design_scores_gemma":[0.0022173391,0.0014425066,0.14330104,0.00031779238,0.000032658707,0.0010757805,0.0064828354,0.0049513862,0.0020888282,0.4844789,0.35295722,0.0006537241],"about_ca_topic_score_codex":0.000046102723,"about_ca_topic_score_gemma":0.0002026376,"teacher_disagreement_score":0.9553512,"about_ca_system_score_codex":0.00011581412,"about_ca_system_score_gemma":0.00067802175,"threshold_uncertainty_score":0.9996505},"labels":[],"label_agreement":null},{"id":"W3122152317","doi":"10.3386/w18820","title":"Estimating the Effect of Salience in Wholesale and Retail Car Markets","year":2013,"lang":"en","type":"report","venue":"National Bureau of Economic Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Business; Salience (neuroscience); Commerce; Econometrics; Industrial organization; Economics; Computer science; Artificial intelligence","score_opus":0.4918722551205483,"score_gpt":0.5852813668369244,"score_spread":0.09340911171637617,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3122152317","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9036364,0.0004735669,0.0000041313738,0.00030774693,0.00050255825,0.00057213317,0.00005932787,0.0000043305404,0.09443983],"genre_scores_gemma":[0.9963222,0.000121386736,0.00028304692,0.0000052802416,0.00018615997,0.000043665746,0.000018602865,0.000021220969,0.002998415],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99338573,0.0007956955,0.0017607517,0.00077533914,0.002933061,0.00034943185],"domain_scores_gemma":[0.97822124,0.01837661,0.0009631225,0.00072609767,0.0016176755,0.00009522805],"candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.04732677,0.00021537548,0.00086628174,0.0012189865,0.00013409196,0.0002574763,0.0015496478,0.0003246716,0.000546714],"category_scores_gemma":[0.022058824,0.00013993359,0.00017678158,0.00041832073,0.00075636327,0.00031267092,0.0005881014,0.00076217746,0.0001681336],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002672136,0.00009204689,0.10720671,0.00023444119,0.00008765981,0.00001524893,0.0003438085,0.008626727,0.00032195987,0.0036413018,0.088171534,0.79099137],"study_design_scores_gemma":[0.0017424584,0.00090844376,0.066157706,0.001373421,0.0000452925,0.0001582436,0.00040939514,0.075706184,0.00089449866,0.83580554,0.016005876,0.00079292955],"about_ca_topic_score_codex":0.0013207325,"about_ca_topic_score_gemma":0.00018324432,"teacher_disagreement_score":0.8321642,"about_ca_system_score_codex":0.0006267168,"about_ca_system_score_gemma":0.0015893178,"threshold_uncertainty_score":0.9861788},"labels":[],"label_agreement":null},{"id":"W3122159922","doi":"","title":"Conditional Expected Utility","year":2013,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Subjective expected utility; Expected utility hypothesis; Axiom; Preference; Mathematical economics; Von Neumann–Morgenstern utility theorem; Class (philosophy); Conditional probability; Separable space; Decision theory; Axiom independence; Event (particle physics); Invariant (physics); Mathematics; Representation (politics); Utility theory; Computer science; Artificial intelligence; Statistics","score_opus":0.21464586941068373,"score_gpt":0.45608154072341,"score_spread":0.24143567131272628,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3122159922","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89706975,0.00006955544,0.000022685363,0.00050500524,0.0013336652,0.00077592995,0.0003514616,0.00006846977,0.09980347],"genre_scores_gemma":[0.9929666,0.0005529798,0.0011490644,0.00013397506,0.00034429107,0.00031546838,0.00016716178,0.00006156238,0.0043089],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99180937,0.0008904858,0.0023211055,0.0024532732,0.0014161494,0.001109599],"domain_scores_gemma":[0.98981136,0.004988111,0.00066863734,0.003180338,0.0008656645,0.000485868],"candidate_categories":["metaepi_narrow","scholarly_communication","research_integrity","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.008829054,0.0005049084,0.001175478,0.0015700997,0.0003282956,0.0014673214,0.0033329458,0.0009240273,0.0068095354],"category_scores_gemma":[0.006821481,0.00046686555,0.0005117771,0.00040960326,0.00086069846,0.00040272163,0.0034803073,0.0027565556,0.0014220654],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007709057,0.00030256694,0.012383814,0.00001157076,0.000034017725,0.00004248281,0.00023060666,0.0027077617,0.000028299804,0.0005128348,0.0044601997,0.97920877],"study_design_scores_gemma":[0.0008883141,0.0001162351,0.075561896,0.0001453816,0.000010978741,0.000029875046,0.0018244834,0.036191694,0.000088843044,0.7477506,0.13633718,0.0010545517],"about_ca_topic_score_codex":0.00017116877,"about_ca_topic_score_gemma":0.00030608292,"teacher_disagreement_score":0.9781542,"about_ca_system_score_codex":0.0010223038,"about_ca_system_score_gemma":0.0012017575,"threshold_uncertainty_score":0.99977833},"labels":[],"label_agreement":null},{"id":"W3122501643","doi":"10.1016/j.geb.2017.11.009","title":"Belief updating and the demand for information","year":2017,"lang":"en","type":"article","venue":"Games and Economic Behavior","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":101,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Stanford University","keywords":"Certainty; Value of information; Value (mathematics); Explanatory power; Subjective expected utility; Quality (philosophy); Information quality; Yield (engineering); Aptitude; Econometrics; Psychology; Expected utility hypothesis; Economics; Social psychology; Microeconomics; Computer science; Mathematical economics; Information system; Mathematics; Machine learning","score_opus":0.07985142296356297,"score_gpt":0.3751320584919505,"score_spread":0.29528063552838757,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3122501643","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9960255,0.00006546203,0.00018933897,0.0010330834,0.0005170443,0.00033320553,0.0000627376,0.000010956283,0.0017626559],"genre_scores_gemma":[0.99863875,0.00006709639,0.0006860004,0.00017806033,0.00008304654,0.00007058401,0.000003905475,0.0000059945137,0.0002665345],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99895036,0.000020724907,0.00053740945,0.00024632594,0.000079433,0.00016572968],"domain_scores_gemma":[0.9983482,0.00046688825,0.0005009619,0.00056426314,0.000046523935,0.00007317832],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0020653484,0.00011177855,0.0002699511,0.00007002683,0.00087376824,0.0022767927,0.00046060162,0.00006870666,0.00006482762],"category_scores_gemma":[0.0004391158,0.00006985663,0.00008196886,0.000010781548,0.00030038832,0.001224376,0.00024325227,0.00006877789,0.00008702371],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000047447753,0.0000063513917,0.028750638,0.0000014111303,0.0000034776165,2.3567644e-7,0.00036404442,0.000007805599,0.0000032809653,0.0042369682,0.0012371183,0.9653412],"study_design_scores_gemma":[0.00662735,0.00015125608,0.7018485,0.00003496517,0.00019212985,0.000082463695,0.005007404,0.010023657,0.00009035452,0.08372583,0.19162,0.0005960847],"about_ca_topic_score_codex":0.00012691678,"about_ca_topic_score_gemma":0.00011132435,"teacher_disagreement_score":0.96474516,"about_ca_system_score_codex":0.000019515206,"about_ca_system_score_gemma":0.000024411163,"threshold_uncertainty_score":0.9987589},"labels":[],"label_agreement":null},{"id":"W3122592429","doi":"10.1111/j.1468-0262.2005.00640.x","title":"A Smooth Model of Decision Making under Ambiguity","year":2005,"lang":"en","type":"article","venue":"Econometrica","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1948,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"Economic and Social Research Council; Ministero dell’Istruzione, dell’Università e della Ricerca","keywords":"Ambiguity; Decision-making models; Mathematical economics; Economics; Computer science; Artificial intelligence","score_opus":0.21576175321837493,"score_gpt":0.41759901682382844,"score_spread":0.2018372636054535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3122592429","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9090992,0.00016318732,0.07026913,0.00034111913,0.00029355337,0.00010711808,0.00004476356,0.000037153008,0.019644782],"genre_scores_gemma":[0.96124583,0.000020244826,0.037719958,0.0003707266,0.00008394434,0.0000047463636,0.0000010397637,0.000018849069,0.00053465215],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9969206,0.00004726298,0.00138487,0.00068195275,0.0006335315,0.0003318167],"domain_scores_gemma":[0.9958407,0.0021161977,0.00061188446,0.0010623672,0.00022093522,0.00014790273],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002464858,0.00019021641,0.0005574108,0.0019001922,0.0001281387,0.00025612072,0.0012104979,0.00013767593,0.0017490721],"category_scores_gemma":[0.0023927963,0.00015682791,0.00029683975,0.0019163887,0.00010078928,0.0006242725,0.00034540528,0.00016587926,0.0013836635],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032108313,0.00012718479,0.0019999568,6.70284e-7,0.0000050539384,9.524633e-7,0.000083245395,0.066807665,0.000023096534,0.00095733383,0.0035741618,0.92638856],"study_design_scores_gemma":[0.0008145441,0.00013990818,0.021361154,0.000041540898,0.000026497595,0.000010550702,0.0003194791,0.38929185,0.00025148876,0.5520987,0.035102837,0.0005414756],"about_ca_topic_score_codex":0.000009953101,"about_ca_topic_score_gemma":0.000037787424,"teacher_disagreement_score":0.9258471,"about_ca_system_score_codex":0.00019302401,"about_ca_system_score_gemma":0.000107456784,"threshold_uncertainty_score":0.9993939},"labels":[],"label_agreement":null},{"id":"W3122664019","doi":"10.1257/app.20170048","title":"Do Risk Preferences Change? Evidence from the Great East Japan Earthquake","year":2018,"lang":"en","type":"article","venue":"American Economic Journal Applied Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":325,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Natural disaster; Seismology; Geography; Geology; Meteorology","score_opus":0.1746640953632861,"score_gpt":0.3562616397659082,"score_spread":0.1815975444026221,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3122664019","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99152434,0.00021512616,0.000343224,0.0015767501,0.0021954656,0.00033380394,0.00024531136,0.000048948663,0.0035170242],"genre_scores_gemma":[0.9911297,0.0015790727,0.0018599806,0.0013057409,0.003907895,0.000039320832,0.0000045296965,0.00005697386,0.000116774994],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99538106,0.0002671362,0.0019815217,0.0012919207,0.000292897,0.0007854784],"domain_scores_gemma":[0.99135065,0.0032104366,0.0030680024,0.0017142154,0.00015788601,0.00049879245],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0043940847,0.00051806297,0.0010426819,0.00029511153,0.0010973945,0.0025915252,0.0034502335,0.00013605107,0.0030709181],"category_scores_gemma":[0.0005081648,0.00036095642,0.0004152036,0.0002770249,0.0015778134,0.001216273,0.00054488564,0.00076144066,0.010790552],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001621592,0.000023132216,0.101242274,2.1727814e-7,0.000068632726,0.0000010194681,0.0016494441,0.000460916,0.000007039695,0.00021194531,0.003350882,0.8928223],"study_design_scores_gemma":[0.0012926311,0.00094250747,0.5001333,0.00009980613,0.00023698891,0.00023189303,0.019694468,0.0040454376,0.00015049653,0.35189515,0.11953802,0.0017393195],"about_ca_topic_score_codex":0.0018471676,"about_ca_topic_score_gemma":0.004847347,"teacher_disagreement_score":0.891083,"about_ca_system_score_codex":0.00035890867,"about_ca_system_score_gemma":0.00032751408,"threshold_uncertainty_score":0.99988425},"labels":[],"label_agreement":null},{"id":"W3122672574","doi":"10.1287/mnsc.2016.2539","title":"When Do People Prefer Carrots to Sticks? A Robust “Matching Effect” in Policy Evaluation","year":2016,"lang":"en","type":"article","venue":"Management Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Framing (construction); Framing effect; Deliberation; Social psychology; Public economics; Psychology; Marketing; Public relations; Political science; Economics; Business; Persuasion; Engineering; Law; Politics","score_opus":0.10867624145138219,"score_gpt":0.4212578164481191,"score_spread":0.3125815749967369,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3122672574","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96697086,0.000008705361,0.018492723,0.0024905475,0.00052590476,0.00083355245,0.0000041460075,0.000034751585,0.010638797],"genre_scores_gemma":[0.99559516,0.0000028010363,0.0025922214,0.0003491997,0.000049776994,0.000091200236,3.206489e-7,0.000008959947,0.0013103465],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99512976,0.0001876318,0.00056931766,0.0010672334,0.0025195363,0.0005265334],"domain_scores_gemma":[0.9978019,0.0006161428,0.00015964222,0.0010302374,0.00019353055,0.00019854361],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.015530628,0.00016937897,0.0002535985,0.0016836174,0.00025089286,0.0008991858,0.0018748238,0.00003744907,0.0004535926],"category_scores_gemma":[0.0032263687,0.0001028505,0.00005998794,0.002503104,0.00012764089,0.0009103386,0.0009341321,0.000066177796,0.001755181],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019920282,0.00003496398,0.011899092,0.000002506437,0.0000014975637,0.000003913657,0.0011299327,0.0069089415,0.00043647143,0.0010533307,0.0007694711,0.97773993],"study_design_scores_gemma":[0.0020144328,0.00034751897,0.5542553,0.00043735973,0.000043058033,0.000004830529,0.0018527309,0.012107519,0.00042544195,0.42004716,0.0076722526,0.000792388],"about_ca_topic_score_codex":0.00023231424,"about_ca_topic_score_gemma":0.0005300408,"teacher_disagreement_score":0.97694755,"about_ca_system_score_codex":0.000587653,"about_ca_system_score_gemma":0.0001195902,"threshold_uncertainty_score":0.99902207},"labels":[],"label_agreement":null},{"id":"W3122782278","doi":"","title":"Loss Aversion in Financial Markets","year":2019,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Loss aversion; Financial market; Risk aversion (psychology); Economics; Asset (computer security); Behavioral economics; Financial economics; Monetary economics; Microeconomics; Finance; Expected utility hypothesis","score_opus":0.025904207709719462,"score_gpt":0.32481067836933963,"score_spread":0.29890647065962017,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3122782278","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9946532,0.00025667445,0.00054232543,0.00050887465,0.0010331679,0.00008982627,0.000001943512,0.000010510576,0.0029034382],"genre_scores_gemma":[0.9954693,0.00034844867,0.00007096097,0.00013445031,0.00013200972,8.533989e-7,6.591574e-7,0.000011471652,0.003831873],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99652785,0.0001547453,0.0006595801,0.0003761241,0.0007221801,0.0015595418],"domain_scores_gemma":[0.9987875,0.00036213646,0.00027843384,0.00036457562,0.000118242984,0.00008910436],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.008631849,0.00014096487,0.00029601634,0.00044533,0.00011382084,0.00020732633,0.00088364107,0.0001253493,0.0007750279],"category_scores_gemma":[0.00080742827,0.00010755664,0.00017783516,0.0004895437,0.000034129404,0.00047946407,0.00011621567,0.0014972178,0.002744137],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023775168,0.00008637679,0.08357599,5.697782e-7,0.000005327493,0.00002938677,0.000093390816,0.00015535328,0.000101892896,0.007980131,0.0010860678,0.90664774],"study_design_scores_gemma":[0.0009662589,0.00021101744,0.025141852,0.00002395555,0.00000466034,0.0003804098,0.00074097165,0.0003577937,0.000027813832,0.9509986,0.020955376,0.00019129291],"about_ca_topic_score_codex":0.000023249266,"about_ca_topic_score_gemma":0.00050103373,"teacher_disagreement_score":0.9430185,"about_ca_system_score_codex":0.0008410932,"about_ca_system_score_gemma":0.001739255,"threshold_uncertainty_score":0.99803233},"labels":[],"label_agreement":null},{"id":"W3123335834","doi":"10.1111/1911-3846.12368","title":"Auditing Complex Estimates: How Do Construal Level and Evidence Formatting Impact Auditors' Consideration of Inconsistent Evidence?","year":2018,"lang":"en","type":"article","venue":"Contemporary Accounting Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":51,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Audit; Skepticism; Accounting; Context (archaeology); Disk formatting; Psychology; Business; Computer science","score_opus":0.6477451642451761,"score_gpt":0.53674767082475,"score_spread":0.1109974934204262,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3123335834","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99288285,0.0012442819,0.0010657096,0.0024253004,0.0005860585,0.0005357888,0.00005192651,0.000058508005,0.0011496046],"genre_scores_gemma":[0.99427354,0.00002491863,0.0047606425,0.0000907358,0.0007163281,0.000014577479,0.0000046164346,0.000028277173,0.00008634616],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99325866,0.0007344283,0.0015899948,0.0010241052,0.0026442597,0.00074855966],"domain_scores_gemma":[0.959954,0.029641597,0.0016076468,0.0012743326,0.007179467,0.0003429108],"candidate_categories":["metaresearch","metaepi_narrow","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.02714304,0.00032400189,0.0007783079,0.00116819,0.0014501,0.0032088156,0.0011492573,0.00020713836,0.00031178803],"category_scores_gemma":[0.07680061,0.00025443512,0.0001812348,0.0013764822,0.0026661851,0.0045143124,0.0012307147,0.0006197362,0.00017413059],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034427198,0.00007108604,0.6562465,0.00008891791,0.000047036647,0.000030275945,0.0020258944,0.000011887609,0.01356456,0.0002784864,0.05292498,0.27436614],"study_design_scores_gemma":[0.003791533,0.004927211,0.6996696,0.021869652,0.000095516,0.0008528155,0.03945416,0.11705558,0.01819933,0.080632426,0.010647733,0.002804437],"about_ca_topic_score_codex":0.00048824903,"about_ca_topic_score_gemma":0.000111991496,"teacher_disagreement_score":0.2715617,"about_ca_system_score_codex":0.00018630926,"about_ca_system_score_gemma":0.0014256395,"threshold_uncertainty_score":0.99999076},"labels":[],"label_agreement":null},{"id":"W3123358931","doi":"10.1111/mafi.12027","title":"OPTIMAL INSURANCE DESIGN UNDER RANK‐DEPENDENT EXPECTED UTILITY","year":2013,"lang":"en","type":"article","venue":"Mathematical Finance","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":122,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Expected utility hypothesis; Distortion (music); Isoelastic utility; Economics; Mathematical economics; Mathematical optimization; Function (biology); Deductible; Regular polygon; Rank (graph theory); Distortion function; Concave function; Econometrics; Computer science; Actuarial science; Mathematics; Statistics","score_opus":0.17888993934591077,"score_gpt":0.3734268161444817,"score_spread":0.19453687679857093,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3123358931","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6995789,0.000053946034,0.2966786,0.00044727867,0.00018652489,0.00032743622,0.00000887883,0.0000653961,0.00265307],"genre_scores_gemma":[0.9404415,0.00000686159,0.0572781,0.00018610712,0.00003675372,0.000082568054,7.293629e-7,0.000018090057,0.0019492831],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99661326,0.00018750361,0.0010869441,0.0007207025,0.0009476007,0.00044400655],"domain_scores_gemma":[0.99590784,0.0022423188,0.00026510746,0.0011496991,0.00029725276,0.00013777209],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0018492294,0.00024671084,0.0005655069,0.000109127126,0.00017433577,0.0004857828,0.0010732095,0.00015204825,0.0046457914],"category_scores_gemma":[0.002351178,0.00017394443,0.00016847902,0.0004482651,0.00020618767,0.00053188717,0.00021044876,0.00023576681,0.013199097],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018855873,0.0016975264,0.0031361235,0.00002651813,0.00003082948,0.000048891165,0.0012796698,0.008828711,0.0013439002,0.026561528,0.033128157,0.9237296],"study_design_scores_gemma":[0.0004944453,0.00008534796,0.025357174,0.00005702844,0.000007977249,0.000033234526,0.00028219735,0.037375204,0.0012489364,0.9335539,0.0011280953,0.00037649888],"about_ca_topic_score_codex":0.000012843904,"about_ca_topic_score_gemma":0.0000014013584,"teacher_disagreement_score":0.9233531,"about_ca_system_score_codex":0.000052734405,"about_ca_system_score_gemma":0.0000615555,"threshold_uncertainty_score":0.9962641},"labels":[],"label_agreement":null},{"id":"W3123525914","doi":"10.2139/ssrn.1443865","title":"Economic Incentives and Social Preferences: A Preference-Based Lucas Critique of Public Policy","year":2009,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Incentive; Preference; Economics; Social preferences; Public economics; Public choice; Public policy; Positive economics; Microeconomics; Political science; Economic growth","score_opus":0.12360791166538662,"score_gpt":0.3879534530412645,"score_spread":0.26434554137587785,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3123525914","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9907499,0.00045166886,0.002836112,0.0042957077,0.00012593319,0.000102752216,0.000018455921,0.000019122515,0.001400363],"genre_scores_gemma":[0.9986505,0.0005262894,0.00017848217,0.00021283356,0.00023575535,0.000002436893,0.0000023496211,0.000010008245,0.00018135752],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99650204,0.00031001572,0.0009105339,0.0004190698,0.00045978965,0.0013985364],"domain_scores_gemma":[0.99835265,0.00037408533,0.0006245589,0.00026084494,0.00025119228,0.00013667035],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0049583735,0.00020515562,0.00046003095,0.0006694129,0.00031869928,0.0005190045,0.00087904744,0.0001480188,0.00011105456],"category_scores_gemma":[0.00059217546,0.00015995842,0.00019198946,0.00029202073,0.00020090472,0.0006847463,0.00006476804,0.0009024806,0.000036080255],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000065681656,0.00011516881,0.0048094178,0.0000012747824,0.000016678072,0.0000010513472,0.00027152992,0.000017508593,0.0001267433,0.118380666,0.00011681455,0.8760775],"study_design_scores_gemma":[0.0006371327,0.00055180857,0.0108760875,0.000016179216,0.000014649716,0.00006542792,0.0017764533,0.00018185204,0.00013374934,0.98429805,0.0012629213,0.00018566127],"about_ca_topic_score_codex":0.00009363218,"about_ca_topic_score_gemma":0.0009287654,"teacher_disagreement_score":0.8758918,"about_ca_system_score_codex":0.00071284507,"about_ca_system_score_gemma":0.0063901716,"threshold_uncertainty_score":0.99924266},"labels":[],"label_agreement":null},{"id":"W3123531672","doi":"10.1093/ej/uez054","title":"Nudge Versus Boost: Agency Dynamics Under Libertarian Paternalism","year":2019,"lang":"en","type":"article","venue":"The Economic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":45,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Novelty; Economics; Dynamic inconsistency; Competence (human resources); Public economics; Agency (philosophy); Microeconomics; Order (exchange); Positive economics; Psychology; Social psychology; Sociology","score_opus":0.10481147138127267,"score_gpt":0.37297665652252315,"score_spread":0.2681651851412505,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3123531672","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96795326,0.00007895853,0.00039473464,0.003225307,0.010789812,0.000116582734,0.000026461186,0.000020355528,0.017394513],"genre_scores_gemma":[0.991592,0.0000419113,0.00016769812,0.0007030698,0.0004822961,0.0000016024055,0.000002498561,0.00002905515,0.006979906],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9975475,0.00017871306,0.0010647818,0.00041551382,0.0003670491,0.00042641466],"domain_scores_gemma":[0.9969592,0.0010984911,0.0006967368,0.00095602294,0.00007985603,0.00020965505],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0033929031,0.00022000214,0.0003904581,0.0002101991,0.0003370329,0.0012385573,0.0020414686,0.000120195014,0.0076188166],"category_scores_gemma":[0.00014645579,0.00013760499,0.00034283721,0.00010602265,0.000094648305,0.0006648417,0.0002590739,0.0005423785,0.01782819],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008854609,0.00010076471,0.018612606,0.0000018401371,0.00016687028,0.00006385806,0.0022197743,0.021003308,0.000088943125,0.01997591,0.038857687,0.89802295],"study_design_scores_gemma":[0.0027824703,0.00028121332,0.018497951,0.000016643917,0.00006116464,0.00059557613,0.001821678,0.031137025,0.00003679927,0.8990486,0.045155417,0.0005654114],"about_ca_topic_score_codex":0.00013702721,"about_ca_topic_score_gemma":0.00027518035,"teacher_disagreement_score":0.89745754,"about_ca_system_score_codex":0.000688545,"about_ca_system_score_gemma":0.0002954609,"threshold_uncertainty_score":0.99979824},"labels":[],"label_agreement":null},{"id":"W3123605739","doi":"10.1016/j.joep.2007.07.001","title":"The risk perceptions of individual investors","year":2007,"lang":"en","type":"article","venue":"Journal of Economic Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":133,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Simon Fraser University; Universiteit van Tilburg; Northwestern University; Harvard University; Università degli Studi di Sassari; Nederlandse Organisatie voor Wetenschappelijk Onderzoek","keywords":"Variance (accounting); Econometrics; Actuarial science; Benchmark (surveying); Bond; Risk measure; Financial economics; Market risk; Economics; Stock market; Stock (firearms); Portfolio; Finance","score_opus":0.15538970118702686,"score_gpt":0.4707797110751112,"score_spread":0.3153900098880843,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3123605739","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9894795,0.0001457749,0.0011625459,0.0007604886,0.0037876836,0.000041897594,0.000017967992,0.0000032015573,0.0046009542],"genre_scores_gemma":[0.9977602,0.00017061157,0.0013046197,0.0002877058,0.00031624193,3.602924e-7,2.6504867e-7,0.000008209079,0.0001518374],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9971661,0.00017898851,0.001964853,0.00020110316,0.0002592092,0.00022976052],"domain_scores_gemma":[0.9942704,0.0026257318,0.0022733202,0.00051723135,0.00017047727,0.00014286446],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.013763761,0.00010306704,0.0003853383,0.0004745867,0.00016857377,0.000102507685,0.0014909189,0.00012715923,0.00047182152],"category_scores_gemma":[0.0011809968,0.00006298904,0.0003176554,0.00014478734,0.00037375398,0.000239309,0.000085719446,0.00036811447,0.00033299366],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017618257,0.00009223429,0.16452913,2.3314054e-7,0.00005852273,0.000008924385,0.00059592776,0.00026998925,0.00015670783,0.0009070666,0.060731053,0.77247405],"study_design_scores_gemma":[0.0007536437,0.00045999643,0.66456485,0.0000073592632,0.000045833258,0.000376716,0.0022833436,0.00003322878,0.000046083744,0.23193647,0.09937145,0.000121035046],"about_ca_topic_score_codex":0.000008012088,"about_ca_topic_score_gemma":0.00013599766,"teacher_disagreement_score":0.772353,"about_ca_system_score_codex":0.00007191091,"about_ca_system_score_gemma":0.00011285013,"threshold_uncertainty_score":0.5166115},"labels":[],"label_agreement":null},{"id":"W3123635459","doi":"","title":"When Does Feeling of Fluency Matter? How Abstract and Concrete Thinking Influence Fluency Effects","year":2011,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Fluency; Feeling; Processing fluency; Cognitive psychology; Psychology; Priming (agriculture); Value (mathematics); Verbal fluency test; Social psychology; Computer science; Cognition; Neuropsychology; Mathematics education","score_opus":0.03358314662971594,"score_gpt":0.3020886817453877,"score_spread":0.26850553511567177,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3123635459","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9954879,0.0012384435,0.0017957092,0.00024687816,0.00041069658,0.00014484087,0.0000048012844,0.000023977105,0.0006467109],"genre_scores_gemma":[0.99706125,0.00047251963,0.001985602,0.00012183013,0.00008682713,0.0000030822525,4.5174107e-7,0.000025110208,0.00024331332],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9961423,0.00015022453,0.00094261643,0.00050657097,0.0008292461,0.0014290131],"domain_scores_gemma":[0.9972896,0.0007319373,0.00095223513,0.0004952128,0.00036177898,0.00016926152],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00623626,0.0002693078,0.00053807796,0.00037955822,0.0003643236,0.0004422287,0.0011727352,0.00015605205,0.00017233094],"category_scores_gemma":[0.0009317329,0.000175244,0.00019096903,0.00023538117,0.0001810726,0.0012114064,0.00016968387,0.0013409306,0.00010181623],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035170413,0.00010838161,0.14288388,0.000036752637,0.00019154708,0.00006409282,0.008715373,0.00004862437,0.013981003,0.015777664,0.00019534113,0.8176456],"study_design_scores_gemma":[0.00076470163,0.00040498603,0.016636707,0.00013360701,0.000048484082,0.00029951293,0.002110926,0.000052852534,0.0011792853,0.97798043,0.00012733761,0.00026117373],"about_ca_topic_score_codex":0.00012163777,"about_ca_topic_score_gemma":0.000096171636,"teacher_disagreement_score":0.9622028,"about_ca_system_score_codex":0.0002030152,"about_ca_system_score_gemma":0.00062690134,"threshold_uncertainty_score":0.7146243},"labels":[],"label_agreement":null},{"id":"W3123676357","doi":"10.1037/a0016074","title":"Immediacy bias in emotion perception: Current emotions seem more intense than previous emotions.","year":2009,"lang":"en","type":"article","venue":"Journal of Experimental Psychology General","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":53,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Immediacy; Psychology; Perception; Salience (neuroscience); Emotion perception; Cognitive psychology; Social psychology; Attentional bias; Cognition","score_opus":0.22361745299687172,"score_gpt":0.5006723849807303,"score_spread":0.27705493198385855,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3123676357","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9895729,0.0009025107,0.0007414746,0.0033741447,0.0047416133,0.00017091591,0.000008881586,0.00001752837,0.00047007433],"genre_scores_gemma":[0.99544555,0.00022318371,0.0024320055,0.0009389858,0.0007666786,0.0000033342483,0.0000072737394,0.000014896102,0.00016807736],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9960565,0.00048405776,0.0018580914,0.0005167372,0.00072081166,0.00036378947],"domain_scores_gemma":[0.99784535,0.00015374999,0.00087019434,0.00054654875,0.00033798208,0.0002461935],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022060692,0.0002696496,0.0005945545,0.0009806823,0.0001737274,0.0001822151,0.00077427505,0.00018282633,0.00068542],"category_scores_gemma":[0.0003771915,0.00020977696,0.0004616144,0.0006085342,0.00017880143,0.00067637337,0.00007323118,0.00068437506,0.00022783925],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00050957187,0.00389294,0.029701564,0.0000014532421,0.00002792225,0.0001913235,0.007927966,0.0005189359,0.056984708,0.0001499169,0.051477022,0.84861666],"study_design_scores_gemma":[0.0038550377,0.0028860783,0.9561011,0.00016420017,0.00003774661,0.0025452764,0.007955233,0.00089838926,0.00077775086,0.018392377,0.0058365804,0.0005501842],"about_ca_topic_score_codex":0.0000072795992,"about_ca_topic_score_gemma":0.000005861716,"teacher_disagreement_score":0.9263996,"about_ca_system_score_codex":0.0002599283,"about_ca_system_score_gemma":0.00007844145,"threshold_uncertainty_score":0.8554456},"labels":[],"label_agreement":null},{"id":"W3123771500","doi":"","title":"Physical Contact and Financial Risk Taking","year":2009,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Feeling; Handshake; Social psychology; Psychology; Physical security; Financial risk; Risk perception; Actuarial science; Business; Computer security; Computer science; Perception","score_opus":0.037261389995646224,"score_gpt":0.35924727547542235,"score_spread":0.32198588547977613,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3123771500","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9942095,0.00050229154,0.0036636798,0.00042146022,0.00025340423,0.000052765896,0.0000035546132,0.00001917994,0.0008741445],"genre_scores_gemma":[0.9985291,0.00044848438,0.00012033315,0.00018797313,0.00049228134,5.136307e-7,3.0952157e-7,0.000007802958,0.00021319644],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9972215,0.00012941049,0.00046249194,0.0003461294,0.00054311776,0.001297294],"domain_scores_gemma":[0.9984173,0.00037951182,0.00070798246,0.00024800535,0.00011880451,0.00012837465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004179447,0.00015594906,0.00032221124,0.00018609894,0.00040699597,0.00042966212,0.0004972034,0.000075395816,0.000037400994],"category_scores_gemma":[0.0023461762,0.000111410285,0.00017624577,0.00025187735,0.00004080853,0.00040083437,0.000044414868,0.0015809389,0.000117510426],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005095902,0.00005855104,0.0038532866,7.422945e-8,0.000004736301,0.000007323589,0.00015598947,0.000021876735,0.00017102617,0.018563224,0.00018422889,0.9769287],"study_design_scores_gemma":[0.0004554729,0.00061493355,0.02657994,0.000008342066,0.000021330326,0.00035073177,0.00043959176,0.0004993056,0.000037806512,0.9683723,0.0024669396,0.0001533341],"about_ca_topic_score_codex":0.000021426047,"about_ca_topic_score_gemma":0.00018235047,"teacher_disagreement_score":0.9767754,"about_ca_system_score_codex":0.00026988934,"about_ca_system_score_gemma":0.00077386637,"threshold_uncertainty_score":0.6868481},"labels":[],"label_agreement":null},{"id":"W3123794477","doi":"","title":"The Income Effect under Uncertainty: a Slutsky-Like Decomposition with Risk Aversion","year":2013,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Separable space; Economics; Decomposition; Econometrics; Risk aversion (psychology); Representation (politics); Microeconomics; Mathematics; Expected utility hypothesis; Mathematical economics; Chemistry","score_opus":0.05411818427398222,"score_gpt":0.4017375702321382,"score_spread":0.34761938595815595,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3123794477","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98669934,0.00011527437,0.000051847557,0.0005515472,0.001316521,0.0014055367,0.00008010501,0.000059379945,0.00972047],"genre_scores_gemma":[0.9939996,0.003069852,0.0005786301,0.00009002426,0.00019717748,0.00031709115,0.000038211754,0.00008313843,0.0016262875],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9917238,0.0020601014,0.0015933214,0.0020264403,0.0014136662,0.001182694],"domain_scores_gemma":[0.9804573,0.0144186765,0.00097442954,0.003218834,0.000532725,0.0003980071],"candidate_categories":["metaepi_narrow","scholarly_communication","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.015578093,0.00060612155,0.0010519258,0.0010564895,0.0011537529,0.0024547628,0.003235938,0.00071118714,0.0002527853],"category_scores_gemma":[0.002011173,0.00037652266,0.00043581447,0.00048288706,0.00089439674,0.00037360442,0.0029122923,0.003164058,0.0006006853],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005581622,0.0000881979,0.015861733,0.00001269056,0.00007021014,0.00002568532,0.00015532343,0.12360846,0.000016555196,0.00010142207,0.0004382918,0.85906327],"study_design_scores_gemma":[0.0062374887,0.003085324,0.09300355,0.0017048789,0.00018052988,0.00016978207,0.0057645068,0.34691942,0.00020058722,0.4095933,0.1294796,0.003661023],"about_ca_topic_score_codex":0.0007108826,"about_ca_topic_score_gemma":0.0020684786,"teacher_disagreement_score":0.85540223,"about_ca_system_score_codex":0.001927452,"about_ca_system_score_gemma":0.0007447447,"threshold_uncertainty_score":0.9998687},"labels":[],"label_agreement":null},{"id":"W3123875623","doi":"","title":"Expected utility without full transitivity","year":2014,"lang":"en","type":"preprint","venue":"Institutional Repositories DataBase (IRDB)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Transitive relation; Economics; Mathematical economics; Mathematics; Combinatorics","score_opus":0.1364512198960772,"score_gpt":0.39465415593691483,"score_spread":0.25820293604083766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3123875623","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8780654,0.00025860555,0.09264972,0.00042589277,0.015329506,0.000569021,0.004167388,0.00032919916,0.008205265],"genre_scores_gemma":[0.98834544,0.00002434525,0.007621073,0.000163865,0.0019828838,0.000097671655,0.0013117944,0.000040333773,0.00041259572],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9904447,0.0006576225,0.0023389228,0.002666643,0.0032540245,0.0006380588],"domain_scores_gemma":[0.99108905,0.0016314788,0.0011535458,0.0040615364,0.0015505279,0.00051385735],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0042978283,0.0008169801,0.0013904126,0.0005045353,0.0010654159,0.0017626695,0.002434959,0.0007021405,0.00044089142],"category_scores_gemma":[0.006813926,0.0006934897,0.00067161943,0.00057415344,0.0011583028,0.001179598,0.0021407753,0.0015088517,0.00065302534],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.007436217,0.005889289,0.12386208,0.00068573235,0.0010784498,0.0037338901,0.0035219844,0.021181626,0.0133418245,0.049563374,0.14273386,0.62697166],"study_design_scores_gemma":[0.002536453,0.00035007138,0.0419883,0.0019103071,0.00057125016,0.0013167307,0.0005804978,0.02368177,0.0057659354,0.15037066,0.76648957,0.004438469],"about_ca_topic_score_codex":0.0008867496,"about_ca_topic_score_gemma":0.0006358464,"teacher_disagreement_score":0.6237557,"about_ca_system_score_codex":0.00047621736,"about_ca_system_score_gemma":0.0019288353,"threshold_uncertainty_score":0.99955165},"labels":[],"label_agreement":null},{"id":"W3123929703","doi":"10.26481/umamet.2012026","title":"Single-Plateaued Choice","year":2012,"lang":"en","type":"preprint","venue":"Papyrus : Institutional Repository (Université de Montréal)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Universiteit Maastricht","keywords":"Convexity; Matching (statistics); Mathematical economics; Property (philosophy); Independence of irrelevant alternatives; Independence (probability theory); Voting; Term (time); Interval (graph theory); Mathematics; Economics; Econometrics; Social choice theory; Combinatorics; Statistics; Epistemology; Political science","score_opus":0.05848906986529711,"score_gpt":0.2673358534192914,"score_spread":0.20884678355399428,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3123929703","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9376524,0.0058851205,0.00072594435,0.0005260182,0.0047926144,0.00033003243,0.00014401384,0.00020234322,0.04974153],"genre_scores_gemma":[0.9761089,0.00006923877,0.0016736598,0.00018492248,0.0005592815,0.000015527825,0.00006409233,0.00003746663,0.02128693],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9949614,0.00027587658,0.0010380805,0.0013040205,0.0017435048,0.0006771412],"domain_scores_gemma":[0.9951943,0.00090986927,0.0010283163,0.0016618875,0.00055720605,0.0006483818],"candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0013503418,0.00057058886,0.0007838945,0.00067512185,0.0044085677,0.00051618,0.0020698232,0.0008000119,0.0003453678],"category_scores_gemma":[0.0007916839,0.00054884,0.0006866828,0.00043580096,0.0003961531,0.00066934316,0.0026090937,0.0009270706,0.001077751],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010454612,0.0019235507,0.14242369,0.00007457124,0.00056793913,0.003554545,0.024922144,0.022565575,0.014531321,0.007679366,0.03060471,0.7501071],"study_design_scores_gemma":[0.001504436,0.00012909972,0.06417953,0.00030596822,0.000487979,0.0014097285,0.006917385,0.0030174041,0.004339887,0.036022488,0.8797082,0.001977918],"about_ca_topic_score_codex":0.011485219,"about_ca_topic_score_gemma":0.0020490712,"teacher_disagreement_score":0.84910345,"about_ca_system_score_codex":0.0060912557,"about_ca_system_score_gemma":0.0012879331,"threshold_uncertainty_score":0.9997},"labels":[],"label_agreement":null},{"id":"W3123962758","doi":"10.1002/bdm.735","title":"Effects of Spikes in the Price of Gasoline on Behavioral Intentions: A Mental Accounting Explanation","year":2011,"lang":"en","type":"article","venue":"Journal of Behavioral Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Gallon (US); Mental accounting; Gasoline; Economics; Affect (linguistics); Perception; Public economics; Microeconomics; Psychology","score_opus":0.16415801977220304,"score_gpt":0.4335051786725509,"score_spread":0.2693471589003479,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3123962758","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9956763,0.00013835193,0.002361841,0.000028483937,0.0012100588,0.0003181338,0.000013610515,0.0000068528557,0.0002463744],"genre_scores_gemma":[0.9907884,0.000028824319,0.009028251,0.000048996768,0.00006933525,0.000006161095,8.953305e-7,0.000020523219,0.000008584948],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9931432,0.00032290685,0.003119982,0.00036380024,0.0027466982,0.00030343691],"domain_scores_gemma":[0.9922088,0.0028215428,0.0033380322,0.00059040944,0.0009629884,0.00007825295],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006089029,0.0002655447,0.00079849776,0.001692005,0.00012121675,0.00015760117,0.0017267078,0.00016665323,0.00016203128],"category_scores_gemma":[0.0021157693,0.0001679519,0.0005351818,0.0011753052,0.00013981845,0.00097066385,0.00020495278,0.0005148815,0.000016517468],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013758864,0.0045295097,0.08126008,0.000015118241,0.000010280694,0.00028479449,0.00698434,0.0001301428,0.013504677,0.00026492547,0.00076345954,0.89087677],"study_design_scores_gemma":[0.006541163,0.009165042,0.85201705,0.006039559,0.0006142765,0.0010240414,0.026147256,0.00088070583,0.027614532,0.0680867,0.0008163348,0.0010533648],"about_ca_topic_score_codex":0.000051975283,"about_ca_topic_score_gemma":0.00006997262,"teacher_disagreement_score":0.88982344,"about_ca_system_score_codex":0.00013488231,"about_ca_system_score_gemma":0.00010784365,"threshold_uncertainty_score":0.68488795},"labels":[],"label_agreement":null},{"id":"W3124117302","doi":"10.3982/qe856","title":"Eliciting risk preferences using choice lists","year":2019,"lang":"en","type":"article","venue":"Quantitative Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":48,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Lottery; Pairwise comparison; Incentive; Payment; Actuarial science; Econometrics; Computer science; Economics; Microeconomics; Psychology; Artificial intelligence; Finance","score_opus":0.2975611152905501,"score_gpt":0.45625722434889754,"score_spread":0.1586961090583474,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3124117302","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9880307,0.00008985504,0.0011499459,0.00006141393,0.0014738758,0.00022876084,0.00011071448,0.000045339573,0.008809403],"genre_scores_gemma":[0.98512757,0.000048632788,0.014303191,0.00013592235,0.00010661931,0.000003967248,0.0000053033054,0.000028231365,0.00024059202],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9971639,0.00022817901,0.0010926959,0.00088465604,0.00025285504,0.00037773207],"domain_scores_gemma":[0.99316674,0.004607278,0.001077836,0.00074220967,0.0002668892,0.00013902392],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002496117,0.00025518343,0.00058010337,0.00035571912,0.00023798752,0.0007060811,0.00095105736,0.00013119832,0.00096660183],"category_scores_gemma":[0.0027355647,0.00021984566,0.00021687086,0.00032526575,0.00012424852,0.0010438542,0.0002331838,0.0002715957,0.0046397736],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006808194,0.00008333279,0.36386588,0.0000045886977,0.000046292633,0.0000021504402,0.0010805828,0.024564484,0.00032375267,0.006903269,0.00043049845,0.6026271],"study_design_scores_gemma":[0.00084092544,0.00035368747,0.039635662,0.00006706639,0.000046491674,0.0000110187275,0.0053103757,0.22812983,0.0003873293,0.70409966,0.020255543,0.00086240715],"about_ca_topic_score_codex":0.00045540254,"about_ca_topic_score_gemma":0.00041426552,"teacher_disagreement_score":0.69719636,"about_ca_system_score_codex":0.00014928075,"about_ca_system_score_gemma":0.00014164258,"threshold_uncertainty_score":0.99994665},"labels":[],"label_agreement":null},{"id":"W3124191659","doi":"10.1002/bdm.2232","title":"Arithmetic computation with probability words and numbers","year":2021,"lang":"en","type":"article","venue":"Journal of Behavioral Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Department of National Defence; Defence Research and Development Canada","funders":"","keywords":"Calculator; Computation; Coherence (philosophical gambling strategy); Point (geometry); Computer science; Statistics; Probability distribution; Arithmetic; Percentage point; Mathematics; Algorithm","score_opus":0.12452005511506391,"score_gpt":0.42987133092850005,"score_spread":0.30535127581343613,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3124191659","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93258786,0.00019689223,0.06594165,0.0001823094,0.00073746237,0.00010565514,0.000006930043,0.000014672619,0.0002265811],"genre_scores_gemma":[0.8244649,0.00001244922,0.1752975,0.000083009705,0.0000728423,0.000001248858,5.928349e-7,0.000018259401,0.000049184084],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99514574,0.0002543314,0.0018074338,0.000554141,0.0019528903,0.00028547147],"domain_scores_gemma":[0.994292,0.0020563803,0.0012917166,0.00048288162,0.0016445563,0.00023245254],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035932735,0.00024225327,0.00072341796,0.00048261674,0.00021813413,0.0010106497,0.0004986632,0.0001430224,0.00025704937],"category_scores_gemma":[0.0014064017,0.00016546194,0.00024425957,0.0010203499,0.00017148393,0.0009040588,0.00023863536,0.0004582916,0.00003227552],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025175526,0.00024883082,0.04999125,0.0000023613559,0.0000082609595,0.00051240955,0.00040148397,0.001467321,0.00015455118,0.000044011045,0.00045373332,0.946464],"study_design_scores_gemma":[0.0044197724,0.0020839716,0.23372224,0.0015756983,0.00046381567,0.01094361,0.008218624,0.0038807269,0.0004727304,0.7262675,0.006756052,0.0011952176],"about_ca_topic_score_codex":0.000006931796,"about_ca_topic_score_gemma":0.000093810006,"teacher_disagreement_score":0.9452688,"about_ca_system_score_codex":0.0001516274,"about_ca_system_score_gemma":0.0002984204,"threshold_uncertainty_score":0.9745718},"labels":[],"label_agreement":null},{"id":"W3124199816","doi":"","title":"Reverse Bayesianism: A Generalization","year":2018,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Generalization; Decision maker; State space; Null (SQL); Space (punctuation); Mathematical economics; State (computer science); Null hypothesis; Computer science; Artificial intelligence; Mathematics; Econometrics; Epistemology; Operations research; Statistics; Algorithm; Data mining; Philosophy","score_opus":0.15511650417128026,"score_gpt":0.4421341610267307,"score_spread":0.28701765685545044,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3124199816","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8955161,0.00007451258,0.00018157113,0.0006592369,0.0026408264,0.00079589133,0.00013820888,0.00007371512,0.09991992],"genre_scores_gemma":[0.9738311,0.0034821758,0.008593878,0.00051486044,0.0013344688,0.00020798288,0.00011542819,0.00016169282,0.0117584225],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9925565,0.0008586677,0.0020732107,0.0023344425,0.0011731875,0.0010039506],"domain_scores_gemma":[0.99325806,0.0016606885,0.0007115687,0.0032541077,0.000733555,0.00038204412],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.011927589,0.00047193683,0.0010062238,0.0017900917,0.00034138784,0.0013297234,0.0030537702,0.00093046797,0.0017243047],"category_scores_gemma":[0.005128868,0.00044737378,0.00041468753,0.00054733345,0.0006093581,0.00033539458,0.003136527,0.0016044958,0.0008519391],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010192392,0.00017542693,0.0057050413,0.000015489439,0.000027111117,0.00006330318,0.0003882205,0.0074890405,0.00005997252,0.0003560857,0.007940926,0.97767746],"study_design_scores_gemma":[0.0010917736,0.00028762055,0.006119473,0.0003826075,0.000025476229,0.000048013928,0.001257062,0.07748477,0.00026617508,0.44516823,0.46637037,0.0014984261],"about_ca_topic_score_codex":0.0001203155,"about_ca_topic_score_gemma":0.0005045992,"teacher_disagreement_score":0.976179,"about_ca_system_score_codex":0.001178715,"about_ca_system_score_gemma":0.001039493,"threshold_uncertainty_score":0.99992603},"labels":[],"label_agreement":null},{"id":"W3124297494","doi":"","title":"Calibration without Reduction for Non-Expected Utility","year":2015,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Expected utility hypothesis; Calibration; Risk aversion (psychology); Axiom; Econometrics; Reduction (mathematics); Mathematical economics; Decision maker; Economics; Class (philosophy); Prospect theory; Subjective expected utility; Computer science; Mathematics; Microeconomics; Statistics; Artificial intelligence; Management science","score_opus":0.23375136064894944,"score_gpt":0.46792835420559836,"score_spread":0.23417699355664892,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3124297494","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97315216,0.000040646857,0.0003260111,0.00046079842,0.0026416734,0.0017887519,0.00025915404,0.000071154784,0.02125965],"genre_scores_gemma":[0.99184155,0.00030583923,0.0036163377,0.000029478384,0.00058250234,0.00041405312,0.00016756698,0.000072033254,0.0029706582],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99354696,0.0005272588,0.0019836163,0.0021758701,0.000932455,0.000833848],"domain_scores_gemma":[0.9936838,0.0014991331,0.0007428928,0.0024990395,0.0011783981,0.0003967431],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.01431876,0.00042291012,0.0010576656,0.0012621074,0.00029573325,0.0010952567,0.0018947278,0.00087563146,0.00018813465],"category_scores_gemma":[0.006617461,0.00039958593,0.000386533,0.00039632135,0.00042104255,0.00048883737,0.0014283939,0.0014651052,0.000059291804],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047672505,0.00022510368,0.0047678095,0.000021183758,0.00002585488,0.000004698726,0.0005609039,0.007408786,0.00009795366,0.0000493938,0.0031827008,0.9831789],"study_design_scores_gemma":[0.0023127391,0.00042172745,0.007920405,0.0003102398,0.000035587687,0.00003170544,0.0051521626,0.5260058,0.00063267315,0.38259146,0.07317169,0.0014138364],"about_ca_topic_score_codex":0.00012696281,"about_ca_topic_score_gemma":0.0003389504,"teacher_disagreement_score":0.98176503,"about_ca_system_score_codex":0.0013700092,"about_ca_system_score_gemma":0.0018360682,"threshold_uncertainty_score":0.9999417},"labels":[],"label_agreement":null},{"id":"W3124328514","doi":"10.2308/jmar-50726","title":"The Moderating Effect of Prior Sales Changes on Asymmetric Cost Behavior","year":2014,"lang":"en","type":"article","venue":"Journal of Management Accounting Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":322,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Economics; Phenomenon; Microeconomics; Empirical research; Econometrics; Mathematics; Statistics","score_opus":0.1771256799378747,"score_gpt":0.4798260455893569,"score_spread":0.3027003656514822,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3124328514","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99291474,0.00012393743,0.0003370545,0.0008482949,0.0005800493,0.0004373952,0.0000015927974,0.000007562631,0.00474935],"genre_scores_gemma":[0.9984216,0.000095846546,0.00050977967,0.000037464226,0.00027952014,0.000018203591,3.3891465e-7,0.000018342476,0.000618888],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9934759,0.0008956582,0.0010937981,0.00030940407,0.0037574258,0.00046781375],"domain_scores_gemma":[0.9823134,0.014748121,0.0010691105,0.0006731743,0.0011024108,0.00009376798],"candidate_categories":["metaresearch","scholarly_communication"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.05956225,0.00015376971,0.00044396459,0.0017762572,0.0007132132,0.0012798653,0.001943236,0.00007062482,0.00002626804],"category_scores_gemma":[0.011770033,0.000082685074,0.0001987545,0.0013883242,0.00016792535,0.00025232884,0.00052916096,0.00061898894,0.00012452566],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016421499,0.000072891955,0.012441905,0.000013311636,0.000018736919,0.000016137701,0.000043789347,0.00023959125,0.00012828363,0.00031515563,0.0031472323,0.98339874],"study_design_scores_gemma":[0.012189878,0.017988652,0.452348,0.0033342782,0.0007352652,0.00018766992,0.009337525,0.043618258,0.021145603,0.056148406,0.38112324,0.0018432043],"about_ca_topic_score_codex":0.000009782475,"about_ca_topic_score_gemma":0.000028336288,"teacher_disagreement_score":0.9815555,"about_ca_system_score_codex":0.0001206715,"about_ca_system_score_gemma":0.000033078028,"threshold_uncertainty_score":0.9997569},"labels":[],"label_agreement":null},{"id":"W3124348298","doi":"","title":"Social Preference Under Twofold Uncertainty","year":2016,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada; Wissenschaftskolleg zu Berlin; Agence Nationale de la Recherche","keywords":"Preference; Econometrics; Economics; Psychology; Statistics; Mathematics; Microeconomics","score_opus":0.3098558786591238,"score_gpt":0.4708694550469446,"score_spread":0.16101357638782082,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3124348298","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.85189253,0.000052459738,0.000045898632,0.0021738894,0.0014392885,0.00065759534,0.00024046021,0.00007124968,0.14342661],"genre_scores_gemma":[0.9903645,0.00078833324,0.00025769026,0.00018899607,0.0006484972,0.00016333346,0.00002518059,0.000078469384,0.0074850204],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9916463,0.00090364326,0.0020813593,0.0025738499,0.0014033845,0.0013914482],"domain_scores_gemma":[0.9911604,0.0045762346,0.0007446287,0.0025325208,0.00060885726,0.00037736096],"candidate_categories":["metaepi_narrow","scholarly_communication","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.010484237,0.00056765496,0.0012546586,0.0013517364,0.00047165,0.0012284792,0.0041895555,0.0010867789,0.0009987855],"category_scores_gemma":[0.0027966,0.00044812792,0.00055863586,0.00037202451,0.00086185226,0.00032154817,0.004441736,0.002328864,0.0005854164],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014590767,0.00015215261,0.002857883,0.000011026944,0.000035245925,0.000020566731,0.0003176225,0.004126462,0.00005028559,0.0021050477,0.0017960139,0.9883818],"study_design_scores_gemma":[0.00097114424,0.0001136307,0.01066201,0.00025559415,0.000013768045,0.000011067827,0.0014568875,0.004521562,0.00006158112,0.88614535,0.09473744,0.0010499647],"about_ca_topic_score_codex":0.00012131725,"about_ca_topic_score_gemma":0.0008711251,"teacher_disagreement_score":0.9873318,"about_ca_system_score_codex":0.0019336694,"about_ca_system_score_gemma":0.0015511373,"threshold_uncertainty_score":0.9999728},"labels":[],"label_agreement":null},{"id":"W3124621708","doi":"10.3390/risks4030029","title":"Optimal Insurance with Heterogeneous Beliefs and Disagreement about Zero-Probability Events","year":2016,"lang":"en","type":"article","venue":"Risks","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; HEC Montréal; Social Sciences and Humanities Research Council of Canada; Università Bocconi; Université de Montréal; Imperial College London; Georgia State University; Society of Actuaries","keywords":"Indemnity; Arrow; Actuarial science; Deductible; Mathematical economics; Probabilistic logic; Expected utility hypothesis; Monotone polygon; Incentive compatibility; Mathematics; Schedule; Econometrics; Economics; Statistics; Computer science; Microeconomics; Incentive","score_opus":0.1468276934601342,"score_gpt":0.38609035373552975,"score_spread":0.23926266027539556,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3124621708","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9946604,0.00013866929,0.0041430327,0.00031244828,0.00021607228,0.00019310565,0.000080841324,0.000032206328,0.00022323617],"genre_scores_gemma":[0.99683654,0.000050873423,0.0025817186,0.000071682916,0.000040312712,0.000015096257,7.110408e-7,0.000012111322,0.0003909702],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9977932,0.00009123307,0.00051046925,0.000685797,0.00063319626,0.00028612],"domain_scores_gemma":[0.9982505,0.0004714557,0.00021761935,0.0007540292,0.00013398132,0.00017241492],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010996322,0.00017806023,0.00029534183,0.00007512127,0.00015742161,0.0001341877,0.00047224874,0.000074422605,0.00019586257],"category_scores_gemma":[0.00035079257,0.00008977769,0.00007426929,0.00014941783,0.00018523075,0.00026701041,0.00019784577,0.0000768107,0.00034941317],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008838949,0.00008059662,0.3657962,0.0000011851324,0.00000759098,0.000008983994,0.00008765286,0.00030476277,0.00008622223,0.000030067025,0.00019675096,0.63331157],"study_design_scores_gemma":[0.0014747927,0.00053389254,0.9273017,0.0001284419,0.000017912462,0.000065728374,0.00004066467,0.00015834779,0.00084814895,0.058457308,0.010526768,0.00044626827],"about_ca_topic_score_codex":0.000054430016,"about_ca_topic_score_gemma":0.00008627358,"teacher_disagreement_score":0.6328653,"about_ca_system_score_codex":0.00006501313,"about_ca_system_score_gemma":0.000037082653,"threshold_uncertainty_score":0.44911158},"labels":[],"label_agreement":null},{"id":"W3124661297","doi":"","title":"Risk aversion and framing effects","year":2012,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Center for Interuniversity Research and Analysis on Organizations","funders":"","keywords":"Lottery; Framing effect; Framing (construction); Normative; Stochastic game; Risk aversion (psychology); Psychology; Social psychology; Economics; Loss aversion; Incentive; Econometrics; Salient; Microeconomics; Expected utility hypothesis; Mathematical economics; Computer science; Political science; Artificial intelligence","score_opus":0.09101802287557806,"score_gpt":0.4149614283830361,"score_spread":0.32394340550745804,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3124661297","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9738143,0.0004443719,0.00002756049,0.000114315684,0.0017383214,0.0006079146,0.000064047796,0.00003922001,0.023149932],"genre_scores_gemma":[0.99092954,0.005802569,0.001712212,0.000055766628,0.00033107033,0.00006179432,0.000013271119,0.000059803995,0.0010339835],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9941743,0.00095450185,0.001264422,0.0017258376,0.0008464419,0.0010344755],"domain_scores_gemma":[0.9881085,0.0085416855,0.0006224499,0.0020258008,0.00021532527,0.00048622623],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.01359669,0.00042820154,0.0009687679,0.001331306,0.00040816976,0.0009481076,0.0016463256,0.00084898423,0.00020055815],"category_scores_gemma":[0.0076841065,0.00038529694,0.00028083165,0.00026146995,0.00046573626,0.00036416756,0.0042247637,0.0027841534,0.0002660617],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000055297187,0.00009274895,0.052514356,0.000026045751,0.000019292927,0.000023983748,0.0004168935,0.0011156698,0.00003079476,0.000051427454,0.0001647987,0.9454887],"study_design_scores_gemma":[0.0035035273,0.0005593719,0.31602636,0.001467053,0.00013523037,0.00009960317,0.0048498446,0.06559139,0.00071608636,0.37474918,0.22874756,0.0035548036],"about_ca_topic_score_codex":0.00015057295,"about_ca_topic_score_gemma":0.00016473497,"teacher_disagreement_score":0.9419339,"about_ca_system_score_codex":0.0006999518,"about_ca_system_score_gemma":0.00031894696,"threshold_uncertainty_score":0.99985987},"labels":[],"label_agreement":null},{"id":"W3124673016","doi":"10.20955/wp.2011.030","title":"Markov-Perfect Risk Sharing, Moral Hazard and Limited Commitment","year":2011,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Moral hazard; Hazard; Markov chain; Computer science; Psychology; Economics; Microeconomics; Chemistry","score_opus":0.22614275304126036,"score_gpt":0.38612912106509434,"score_spread":0.15998636802383398,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3124673016","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9368418,0.00036168538,0.0007399123,0.00013754527,0.0020514166,0.0004274036,0.00013253478,0.0001916524,0.059116077],"genre_scores_gemma":[0.98585147,0.0004736185,0.009162789,0.00021250139,0.0001211803,0.000042462147,0.000020833493,0.00004541718,0.004069751],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9957606,0.00018936196,0.0012503796,0.0015886009,0.0007829175,0.0004281197],"domain_scores_gemma":[0.99585235,0.0006649429,0.00060013286,0.0023238843,0.00023475131,0.00032395462],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0034408057,0.00052059937,0.00094230357,0.0005435744,0.00021972129,0.0013655734,0.0019829872,0.00051306485,0.002363222],"category_scores_gemma":[0.0006552777,0.00037508973,0.0003646178,0.00020457683,0.00020456137,0.0002070035,0.0038973673,0.0009294532,0.0009235797],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000059634243,0.00013952742,0.17543878,0.000008430091,0.000060218314,0.000027833743,0.00030568006,0.00020102167,0.000004925704,0.0005378352,0.03985695,0.78335917],"study_design_scores_gemma":[0.0006707759,0.00023605458,0.111197926,0.00012410422,0.00018963181,0.000030879237,0.00029458496,0.019527802,0.00016430057,0.84952325,0.016865505,0.00117518],"about_ca_topic_score_codex":0.00053404534,"about_ca_topic_score_gemma":0.00035869813,"teacher_disagreement_score":0.84898543,"about_ca_system_score_codex":0.00011288516,"about_ca_system_score_gemma":0.00008438088,"threshold_uncertainty_score":0.9998701},"labels":[],"label_agreement":null},{"id":"W3124717382","doi":"","title":"Possibility and permissibility","year":2009,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Rationality; Preference; Mathematical economics; Epistemology; Economics; Mathematics; Philosophy; Microeconomics","score_opus":0.18607404405926312,"score_gpt":0.47086700489660793,"score_spread":0.28479296083734484,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3124717382","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.941219,0.00019435327,0.0000061187507,0.0006550917,0.00058984896,0.0007033087,0.00010960571,0.00004899661,0.056473702],"genre_scores_gemma":[0.9946649,0.0015937176,0.0016706255,0.00013441793,0.00018900566,0.00004546344,0.00001666846,0.00003863311,0.0016465762],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99158394,0.0010697948,0.0022191128,0.003129172,0.0010012373,0.0009967627],"domain_scores_gemma":[0.99090886,0.0037288645,0.0005201804,0.0038286236,0.00046131547,0.00055216154],"candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.022261668,0.00049369974,0.0012660614,0.0010559218,0.00032070238,0.0014398326,0.0023831744,0.0008768004,0.00038928638],"category_scores_gemma":[0.009502501,0.00043780002,0.00037270275,0.00033101306,0.00084813114,0.0003112534,0.0032120757,0.0026681225,0.00008047688],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010355927,0.00021384012,0.037776463,0.000015260266,0.000009339123,0.000031387823,0.0002534544,0.00074548397,0.00001649488,0.000088049484,0.00013898753,0.9606077],"study_design_scores_gemma":[0.00063348055,0.00019917864,0.2668283,0.00015956101,0.000010806832,0.000030286896,0.0009993642,0.014372747,0.000046167333,0.6983729,0.017548703,0.0007985049],"about_ca_topic_score_codex":0.00014299373,"about_ca_topic_score_gemma":0.00069049315,"teacher_disagreement_score":0.9598092,"about_ca_system_score_codex":0.0010722693,"about_ca_system_score_gemma":0.0010195079,"threshold_uncertainty_score":0.99980736},"labels":[],"label_agreement":null},{"id":"W3124809987","doi":"","title":"Internal and External Validity of Experimental Risk and Time Preferences","year":2016,"lang":"en","type":"preprint","venue":"DukeSpace (Duke University)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Hyperbolic discounting; Time preference; Preference; Payment; Discounting; Econometrics; Predictive power; Economics; Actuarial science; Cash; Risk aversion (psychology); Expected utility hypothesis; Microeconomics; Financial economics; Finance","score_opus":0.09968940756380147,"score_gpt":0.33251167640901713,"score_spread":0.23282226884521567,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3124809987","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9848112,0.00025855008,0.002560233,0.00009560508,0.0004550072,0.00015947921,0.00028436483,0.000030941497,0.011344623],"genre_scores_gemma":[0.9899019,0.00025240643,0.0010372518,0.000007264374,0.000065932625,4.5199135e-7,0.000002015029,0.000012160927,0.008720593],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99756694,0.000339189,0.000405262,0.0009100049,0.00055645144,0.0002221666],"domain_scores_gemma":[0.9972374,0.0009176998,0.00081229943,0.0006276793,0.00018704591,0.00021788385],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009779314,0.0002970926,0.000612615,0.0006788543,0.00014465758,0.0002514085,0.0010052167,0.00027868123,0.00058062945],"category_scores_gemma":[0.00034340873,0.00023302968,0.00017821499,0.00015181299,0.00047838895,0.0003449477,0.0024552166,0.00035745272,0.00010477046],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017406902,0.00068715535,0.40087184,0.00005534916,0.00024862814,0.00039378085,0.005103675,0.00013439149,0.020868534,0.0056146747,0.008292927,0.5559884],"study_design_scores_gemma":[0.011823848,0.0037844796,0.16847093,0.00467671,0.0012899229,0.0003143036,0.015982332,0.009262992,0.07650254,0.43880916,0.26261377,0.0064690034],"about_ca_topic_score_codex":0.0001998891,"about_ca_topic_score_gemma":0.000026098132,"teacher_disagreement_score":0.54951936,"about_ca_system_score_codex":0.00010526283,"about_ca_system_score_gemma":0.0001229634,"threshold_uncertainty_score":0.9502675},"labels":[],"label_agreement":null},{"id":"W3124888832","doi":"10.1037/a0030174","title":"Risk preferences and aging: The “Certainty Effect” in older adults’ decision making","year":2012,"lang":"en","type":"article","venue":"Europe PMC (PubMed Central)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":203,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"National Institute on Aging; National Institutes of Health","keywords":"Certainty; Psychology; Risk-seeking; Preference; Young adult; Loss aversion; Risk aversion (psychology); Social psychology; Developmental psychology; Expected utility hypothesis; Economics","score_opus":0.04221512767164729,"score_gpt":0.31427425599255343,"score_spread":0.2720591283209061,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3124888832","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9943054,0.0012431806,0.00030175093,0.00024829552,0.0017516011,0.0006225359,0.000014705852,0.000052015275,0.0014605299],"genre_scores_gemma":[0.9986959,0.0002448045,0.0004284924,0.0001904652,0.00025196205,0.000042708027,0.0000014029074,0.000029348335,0.00011490045],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99536544,0.0009311545,0.00087262143,0.0007367926,0.0008747412,0.0012192781],"domain_scores_gemma":[0.993805,0.0044585494,0.0004122976,0.00086352177,0.00010737363,0.00035327807],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00749815,0.00031198625,0.00042461598,0.0002716332,0.00028348248,0.00064660533,0.0010870417,0.00010840696,0.00020900776],"category_scores_gemma":[0.006831789,0.0001735079,0.00011981977,0.0008616141,0.00016875319,0.000661833,0.00045898836,0.0004960977,0.00027489787],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000752484,0.000048061444,0.43985674,0.0000016820946,0.0000033130061,0.0000052306195,0.0029154243,0.000030715328,0.0000017703744,0.000024933366,0.0006198855,0.556417],"study_design_scores_gemma":[0.000693702,0.000042930624,0.9811179,0.00013321696,0.000024935503,0.000016294867,0.0005580569,0.00035347548,0.000055967852,0.0051388037,0.011611105,0.00025359972],"about_ca_topic_score_codex":0.00007901663,"about_ca_topic_score_gemma":0.0001443717,"teacher_disagreement_score":0.5561634,"about_ca_system_score_codex":0.00008923888,"about_ca_system_score_gemma":0.000037147824,"threshold_uncertainty_score":0.81787825},"labels":[],"label_agreement":null},{"id":"W3124949042","doi":"10.2139/ssrn.1883787","title":"Eliciting Risk Preferences: When is Simple Better?","year":2008,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":36,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Center for Interuniversity Research and Analysis on Organizations; University of Alberta","funders":"","keywords":"Simple (philosophy); Computer science; Econometrics; Mathematics; Epistemology","score_opus":0.1024320880113661,"score_gpt":0.3553509570677484,"score_spread":0.2529188690563823,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3124949042","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98887527,0.00048883795,0.008207016,0.0005808972,0.00031081503,0.00008406308,0.00001691656,0.00004046018,0.0013957211],"genre_scores_gemma":[0.9968665,0.001312688,0.0006162144,0.00047074124,0.00042125199,0.0000031313489,0.0000017585211,0.000023624403,0.0002840704],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99507815,0.0002391162,0.0010389562,0.0005319774,0.0010943175,0.002017484],"domain_scores_gemma":[0.99751824,0.0006646138,0.00078154093,0.00055373827,0.00029521598,0.00018664345],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.005451411,0.00023314955,0.0004089743,0.00033037475,0.0009383161,0.00037072008,0.0013559299,0.00012916824,0.0008126721],"category_scores_gemma":[0.0010885833,0.00016946244,0.0003084549,0.00036076648,0.00010964339,0.0006169215,0.00014591705,0.0020081294,0.0009450743],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021123056,0.000036429272,0.029439481,2.2063784e-7,0.00002599774,0.000009398122,0.0007617275,0.00003094404,0.000025335132,0.00014400341,0.003625888,0.96587944],"study_design_scores_gemma":[0.000369642,0.00021846606,0.00074607355,0.000008481232,0.000021532314,0.00076941104,0.0015994208,0.00037382988,0.00006395255,0.9844488,0.011159186,0.00022121781],"about_ca_topic_score_codex":0.00024339958,"about_ca_topic_score_gemma":0.0006768757,"teacher_disagreement_score":0.9843048,"about_ca_system_score_codex":0.0004696037,"about_ca_system_score_gemma":0.001336053,"threshold_uncertainty_score":0.9998328},"labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"theoretical_or_conceptual","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"medium"},{"model":"gpt","categories":[],"domain":null,"study_design":"design_other","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low"}],"label_agreement":"split"},{"id":"W3124972983","doi":"","title":"2011: “External norms and rationality of choice","year":2008,"lang":"en","type":"preprint","venue":"Institutional Repositories DataBase (IRDB)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Social Sciences and Humanities Research Council of Canada; Ministry of Education, Culture, Sports, Science and Technology","keywords":"Rationalizability; Axiom; Rationality; Mathematical economics; Norm (philosophy); Preference theory; Mathematics; Preference; Economics; Microeconomics; Nash equilibrium; Epistemology; Philosophy","score_opus":0.14862552806644339,"score_gpt":0.39877225829112006,"score_spread":0.2501467302246767,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3124972983","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97338957,0.0011249006,0.010276204,0.00026515996,0.0075488887,0.00032176924,0.0035862767,0.000054854845,0.0034324068],"genre_scores_gemma":[0.98550296,0.00047281326,0.0109980395,0.000111627975,0.001525072,0.000040630497,0.0005599951,0.000020847481,0.00076803094],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9939692,0.00016659667,0.0019200406,0.0013018339,0.0023545208,0.00028778464],"domain_scores_gemma":[0.9939439,0.00153762,0.0012495331,0.0017156723,0.0012895595,0.0002636738],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0017032621,0.00042540365,0.0007960291,0.0003612415,0.00058828574,0.0005155129,0.001294161,0.0003476359,0.00021334311],"category_scores_gemma":[0.003983766,0.00034661248,0.00028172904,0.0002332128,0.0011615788,0.0010972689,0.0022154509,0.00069449353,0.00014859911],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013034662,0.0023084246,0.5819978,0.00042596334,0.00047739726,0.0014029104,0.0010929045,0.01930326,0.0060202125,0.12719171,0.07489505,0.18358088],"study_design_scores_gemma":[0.0019732798,0.0002217811,0.34162918,0.0014728579,0.00025799638,0.0019188785,0.00015298658,0.0039237617,0.005783165,0.21483256,0.42555654,0.0022770108],"about_ca_topic_score_codex":0.0017727813,"about_ca_topic_score_gemma":0.00014784645,"teacher_disagreement_score":0.3506615,"about_ca_system_score_codex":0.00022317548,"about_ca_system_score_gemma":0.0015054443,"threshold_uncertainty_score":0.9998986},"labels":[],"label_agreement":null},{"id":"W3125257997","doi":"10.2139/ssrn.2556153","title":"Optimal Insurance for a Minimal Expected Retention: The Case of an Ambiguity-Seeking Insurer","year":2015,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; Université de Montréal; Université du Québec à Montréal","funders":"","keywords":"Ambiguity; Actuarial science; Business; Econometrics; Economics; Computer science","score_opus":0.13289612018130015,"score_gpt":0.39216338868589024,"score_spread":0.2592672685045901,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3125257997","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9838896,0.0005842124,0.014233109,0.00033988882,0.0005744211,0.00018141921,0.000020775378,0.000018252118,0.00015834089],"genre_scores_gemma":[0.9974363,0.000032697353,0.0018747953,0.00004731519,0.00031346845,0.000010268317,0.0000019980298,0.000020106932,0.000263084],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9965868,0.00030131766,0.0009829418,0.00038044777,0.0005999249,0.0011485551],"domain_scores_gemma":[0.9971458,0.0004832608,0.0007395298,0.0005533118,0.0009064454,0.00017169164],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012394456,0.0001732016,0.000357278,0.00022538398,0.00038757964,0.00034791074,0.0009912495,0.00009054152,0.000024388266],"category_scores_gemma":[0.0019950294,0.00010934154,0.00026483988,0.00048044414,0.00013608775,0.0006525178,0.00009174538,0.00086626573,0.000018466826],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012206318,0.0003701396,0.0051774215,0.0000024132557,0.00009601587,0.00020231828,0.002333315,0.0019753152,0.0005548749,0.008555463,0.00094370457,0.9785684],"study_design_scores_gemma":[0.0034178726,0.0027349486,0.0028389555,0.00003762834,0.000084209176,0.022982085,0.039419837,0.011280885,0.0002521839,0.91162413,0.0048492383,0.00047803315],"about_ca_topic_score_codex":0.000101198326,"about_ca_topic_score_gemma":0.001504344,"teacher_disagreement_score":0.97809035,"about_ca_system_score_codex":0.0003440318,"about_ca_system_score_gemma":0.0015932665,"threshold_uncertainty_score":0.44588187},"labels":[],"label_agreement":null},{"id":"W3125265655","doi":"10.1506/2ukm-aw62-bna6-0ap6","title":"Evidence of Choice Avoidance in Capital‐Investment Judgements*","year":2005,"lang":"en","type":"article","venue":"Contemporary Accounting Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":48,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Affect (linguistics); Control (management); Investment (military); Capital investment; Investment decisions; Decision process; Capital (architecture); Psychology; Function (biology); Decision-making; Cognition; Capital budgeting; Process (computing); Decision fatigue; Actuarial science; Business; Social psychology; Economics; Business decision mapping; Marketing; Microeconomics; Decision analysis; Finance; R-CAST; Behavioral economics; Management science; Political science; Management; Computer science","score_opus":0.4343637681212236,"score_gpt":0.5058215024596886,"score_spread":0.07145773433846497,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3125265655","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9788723,0.0038768153,0.00003566123,0.002465991,0.0002523929,0.0004350636,0.000007875874,0.00002551222,0.0140284],"genre_scores_gemma":[0.99631196,0.00006170482,0.0007208106,0.0003343489,0.00018159735,0.00003397429,0.0000018537476,0.000019566063,0.0023341607],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9938238,0.00056648516,0.0015503321,0.00088217226,0.0025869505,0.0005902054],"domain_scores_gemma":[0.99077487,0.006378413,0.00043854097,0.0012578851,0.0010075322,0.00014276587],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.022124015,0.00018526106,0.00047926966,0.0011693946,0.00021731558,0.00047015582,0.0021313208,0.000121945544,0.00043663784],"category_scores_gemma":[0.014874444,0.00015586853,0.00012542095,0.0017893347,0.00035370563,0.0022948212,0.0007656687,0.00061408884,0.0011520686],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019433015,0.00048161965,0.58375037,0.000035125155,0.00001225525,0.0000326831,0.0014995522,0.00037292572,0.004988107,0.00088103197,0.049681485,0.3580705],"study_design_scores_gemma":[0.0034623637,0.0007990315,0.42958063,0.0039073955,0.000010169074,0.000015607744,0.006711249,0.009271469,0.010490914,0.094417125,0.44000348,0.00133054],"about_ca_topic_score_codex":0.000561559,"about_ca_topic_score_gemma":0.00037508045,"teacher_disagreement_score":0.390322,"about_ca_system_score_codex":0.00023180361,"about_ca_system_score_gemma":0.00050457416,"threshold_uncertainty_score":0.9996256},"labels":[],"label_agreement":null},{"id":"W3125350215","doi":"10.1007/s11579-009-0021-2","title":"Static portfolio choice under cumulative prospect theory","year":2010,"lang":"en","type":"article","venue":"VUBIR (Vrije Universiteit Brussel)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":162,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Chinese Academy of Sciences","keywords":"Cumulative prospect theory; Portfolio; Expected utility hypothesis; Economics; Econometrics; Asset (computer security); Skewness; Modern portfolio theory; Capital asset pricing model; Prospect theory; Mathematical finance; Mathematical economics; Financial economics; Microeconomics; Computer science","score_opus":0.07211863151762005,"score_gpt":0.37371363962320003,"score_spread":0.30159500810558,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3125350215","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94691247,0.000023093955,0.0018040278,0.0006843868,0.0014534872,0.0003064117,0.000059065893,0.00017412343,0.048582952],"genre_scores_gemma":[0.97562337,0.000006550375,0.0019763757,0.00060968834,0.0001903892,0.0000019406793,0.000011377702,0.000039339317,0.021540992],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99656755,0.0001972349,0.00067967846,0.0009835283,0.0010275933,0.00054441206],"domain_scores_gemma":[0.99474233,0.0026683104,0.0004943734,0.0012770566,0.00046805813,0.00034983896],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0021213773,0.00035102566,0.0005042733,0.0007852581,0.0004547338,0.0004720224,0.0014986114,0.00022873966,0.007568583],"category_scores_gemma":[0.0013717314,0.00028764847,0.00028272477,0.0012113812,0.00035818567,0.0011718632,0.0003762964,0.0006282151,0.0027916494],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00057932676,0.0007995331,0.035370227,0.000011788581,0.00020736089,0.00043344908,0.0044364976,0.0025990389,0.006180212,0.20269594,0.06299911,0.6836875],"study_design_scores_gemma":[0.0018637016,0.00031634825,0.05399022,0.000038326845,0.00015801965,0.000065125205,0.006417791,0.0027568445,0.0008543896,0.5840976,0.34833542,0.001106188],"about_ca_topic_score_codex":0.00015697094,"about_ca_topic_score_gemma":0.00030410904,"teacher_disagreement_score":0.68258137,"about_ca_system_score_codex":0.00014115708,"about_ca_system_score_gemma":0.0002443739,"threshold_uncertainty_score":0.99995756},"labels":[],"label_agreement":null},{"id":"W3125771274","doi":"","title":"Lottery Decisions and Probability Weighting Function","year":2001,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal; Université de Montréal","funders":"","keywords":"Lottery; Weighting; Argument (complex analysis); Function (biology); Mathematical economics; Preference; Econometrics; Computer science; Mathematics; Economics; Statistics","score_opus":0.08285315703391606,"score_gpt":0.34571459376499214,"score_spread":0.2628614367310761,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3125771274","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96170455,0.0007450701,0.034571443,0.0009891225,0.000565291,0.00009650786,0.0000014286423,0.000032707052,0.00129386],"genre_scores_gemma":[0.99700797,0.0010108025,0.00052248186,0.00016047499,0.00027721553,0.00000284037,7.520718e-7,0.000014955382,0.0010025259],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9962671,0.00018717557,0.00085370365,0.0005057445,0.00072520145,0.001461116],"domain_scores_gemma":[0.9977234,0.0010270294,0.0003624591,0.00043791873,0.00027098568,0.00017818817],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010269046,0.00017478724,0.0002916939,0.00031202054,0.00058870675,0.0005645412,0.0005243576,0.000109838045,0.00020678971],"category_scores_gemma":[0.0022906428,0.00012316398,0.00016249518,0.00049973885,0.00009092623,0.000683445,0.00013411662,0.00127858,0.00027100134],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000092501155,0.000059473718,0.02761898,1.8382038e-7,0.000013707492,0.000005976082,0.000047532874,0.0000474314,0.00008574092,0.0067757103,0.00028278946,0.96497],"study_design_scores_gemma":[0.00034939536,0.00025191827,0.008911937,0.000013980733,0.000021767668,0.0012782647,0.00088327157,0.00035367435,0.00000591302,0.9722585,0.015518848,0.00015251356],"about_ca_topic_score_codex":0.000020164307,"about_ca_topic_score_gemma":0.0006090535,"teacher_disagreement_score":0.96548283,"about_ca_system_score_codex":0.00046907476,"about_ca_system_score_gemma":0.0007495185,"threshold_uncertainty_score":0.55548656},"labels":[],"label_agreement":null},{"id":"W3125871527","doi":"10.1093/rof/rfu021","title":"Improving Investment Decisions with Simulated Experience","year":2014,"lang":"en","type":"article","venue":"European Finance Review","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":107,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Universität Zürich; Westfälische Wilhelms-Universität Münster; Universität Innsbruck; California Institute of Technology; Simon Fraser University; Stony Brook University; University of Central Florida; University of Sussex; Florida State University","keywords":"Investment decisions; Return on investment; Investment (military); Financial risk; Financial services; Experience sampling method; Finance; Actuarial science; Business; Psychology; Economics; Microeconomics; Behavioral economics; Social psychology","score_opus":0.13179014471000466,"score_gpt":0.37705753846547485,"score_spread":0.2452673937554702,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3125871527","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92175585,0.020379012,0.016715981,0.00058339664,0.00052413094,0.000659881,0.000009227302,0.00015693912,0.039215554],"genre_scores_gemma":[0.9750701,0.008235184,0.0090217125,0.006104719,0.00009086479,0.000011093366,0.0000038036535,0.0000533046,0.0014092261],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9964934,0.000519315,0.0010689276,0.00085030997,0.0007260079,0.00034204687],"domain_scores_gemma":[0.99648476,0.00088251394,0.00059409864,0.0016358409,0.0002498458,0.0001529378],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0039879307,0.00025462388,0.00057705963,0.000109318804,0.00036947444,0.00020405583,0.0013052085,0.000027553284,0.0002016829],"category_scores_gemma":[0.005473962,0.00015718226,0.00015268252,0.000830781,0.00013565994,0.00037000747,0.00043976147,0.00018233286,0.0031497178],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006462926,0.00003639358,0.0002845587,0.000011717344,0.0000016183036,0.000027389817,0.000112156704,0.00025344788,0.00002707957,0.00038206318,0.0027658918,0.99609125],"study_design_scores_gemma":[0.0002687855,0.00017307444,0.0027288995,0.0024945852,0.000022041893,0.00003541974,0.000025774685,0.0016232677,0.000027517794,0.0016219994,0.9906458,0.00033279954],"about_ca_topic_score_codex":0.0000073761166,"about_ca_topic_score_gemma":0.0000047201725,"teacher_disagreement_score":0.9957584,"about_ca_system_score_codex":0.000042004503,"about_ca_system_score_gemma":0.000051892108,"threshold_uncertainty_score":0.9976264},"labels":[],"label_agreement":null},{"id":"W3125966813","doi":"","title":"Human Economic Choice as Costly Information Processing","year":2013,"lang":"en","type":"article","venue":"Chapman University Digital Commons (Chapman University)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Stylized fact; Ambiguity; Computer science; Certainty; Task (project management); Artificial neural network; Value (mathematics); Process (computing); Cognitive psychology; Economics; Artificial intelligence; Psychology; Machine learning; Mathematics","score_opus":0.06033713521119109,"score_gpt":0.29221732337412176,"score_spread":0.23188018816293066,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3125966813","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.76264066,0.0000058464807,0.00035271922,0.00035233624,0.0001730272,0.00030958795,0.00011387018,0.00020454376,0.23584743],"genre_scores_gemma":[0.9805539,0.000004297501,0.00008997568,0.00012755799,0.000053189902,1.2036082e-7,0.00006871153,0.000019759134,0.019082475],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9975605,0.00009596658,0.0005444154,0.0006879655,0.0005581066,0.0005530333],"domain_scores_gemma":[0.9971397,0.0003420218,0.00061614835,0.00093121844,0.00046848794,0.00050244917],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002826709,0.00038384448,0.00050677377,0.001493789,0.0012002102,0.0017914105,0.0024067662,0.00024061456,0.000946585],"category_scores_gemma":[0.00017641348,0.00043005208,0.00032415843,0.000984211,0.00044478668,0.012638324,0.0010425978,0.00038401413,0.009259221],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002143773,0.000594588,0.04585606,0.000033932964,0.00013911776,0.00026527862,0.0028214762,0.0014127634,0.00014693527,0.065921105,0.045639485,0.8369549],"study_design_scores_gemma":[0.0021347774,0.0003588496,0.022862747,0.000076946635,0.00007318866,0.000044022516,0.019368626,0.0021248276,0.00004502904,0.018357685,0.9333516,0.0012017044],"about_ca_topic_score_codex":0.0008346013,"about_ca_topic_score_gemma":0.00048171,"teacher_disagreement_score":0.8877121,"about_ca_system_score_codex":0.0008153041,"about_ca_system_score_gemma":0.0002232433,"threshold_uncertainty_score":0.9999667},"labels":[],"label_agreement":null},{"id":"W3129992849","doi":"10.1177/1745691620974773","title":"Promises and Perils of Experimentation: The Mutual-Internal-Validity Problem","year":2021,"lang":"en","type":"article","venue":"Perspectives on Psychological Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":74,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"External validity; Internal validity; Triangulation; Epistemology; Psychology; Test (biology); Cognitive psychology; Social psychology; Management science; Computer science; Mathematics","score_opus":0.25257985042198583,"score_gpt":0.5149616096208628,"score_spread":0.26238175919887696,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3129992849","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97379047,0.0002438093,0.00031653602,0.0019618291,0.0003316558,0.00014930329,0.0000070605893,0.000018746314,0.023180591],"genre_scores_gemma":[0.99647474,0.00007308037,0.0026584496,0.00024917995,0.00004221825,0.000013330089,1.6011624e-7,0.0000032548621,0.00048560728],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99712795,0.00019208052,0.00041894498,0.0010587376,0.0009756661,0.00022660244],"domain_scores_gemma":[0.9976515,0.0008998274,0.00021588535,0.00066569995,0.00044699287,0.00012007108],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002734917,0.00012370534,0.00022875273,0.00010078287,0.00034952923,0.00047289507,0.0009934393,0.00004493604,0.00085192395],"category_scores_gemma":[0.0028185148,0.000063888445,0.0000937535,0.0009500654,0.0019024899,0.0003230388,0.00024538417,0.0001529209,0.00007666337],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00052696455,0.0029059018,0.030500332,0.000003873531,0.000018537716,0.00008172179,0.036014926,0.0000854044,0.093370736,0.05530268,0.0043423027,0.77684665],"study_design_scores_gemma":[0.0012311152,0.002300624,0.49604127,0.000081838116,0.000020604546,0.00029833257,0.12147016,0.0004546294,0.03846105,0.33086514,0.00815026,0.00062497903],"about_ca_topic_score_codex":0.0000058322858,"about_ca_topic_score_gemma":0.000003319593,"teacher_disagreement_score":0.77622163,"about_ca_system_score_codex":0.000058842987,"about_ca_system_score_gemma":0.000057412017,"threshold_uncertainty_score":0.932797},"labels":[],"label_agreement":null},{"id":"W3130506980","doi":"","title":"Prevalence-Induced Concept Change in Older Adults.","year":2020,"lang":"en","type":"article","venue":"Spectrum Research Repository (Concordia University)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Phenomenon; Psychology; Perception; Cognition; Young adult; Exploratory research; Cognitive psychology; Developmental psychology; Sociology; Psychiatry","score_opus":0.17693135462829593,"score_gpt":0.3813084710477123,"score_spread":0.2043771164194164,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3130506980","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97666144,0.00010711397,0.000032791744,0.0033378315,0.000536578,0.000648417,0.000016162368,0.00008321906,0.018576432],"genre_scores_gemma":[0.9973094,0.000040691742,0.000024097248,0.00011990851,0.00040106583,0.000004914955,0.0000017744317,0.00002239744,0.0020757334],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99478525,0.0009433468,0.00058071397,0.0012989893,0.0015760196,0.00081565307],"domain_scores_gemma":[0.9968565,0.001074007,0.00021041375,0.000872905,0.000353155,0.0006329986],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016010682,0.00023443307,0.00045931537,0.0011448374,0.0004036899,0.0003825014,0.0022194423,0.00021873032,0.0005758841],"category_scores_gemma":[0.00095897506,0.00022537424,0.00021903394,0.0030432758,0.00034539108,0.0010421114,0.0007806628,0.000931867,0.0005837096],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011614931,0.00039248084,0.7942182,0.000040874205,0.00002868611,0.0043746843,0.010449835,0.000030274194,0.0017237001,0.0014241647,0.0041827327,0.1819729],"study_design_scores_gemma":[0.0034137226,0.0013629856,0.9389076,0.0002641949,0.000023701688,0.00004055783,0.011536484,0.0032276318,0.008468952,0.0025235945,0.02938357,0.00084695785],"about_ca_topic_score_codex":0.0057198005,"about_ca_topic_score_gemma":0.0020402744,"teacher_disagreement_score":0.18112594,"about_ca_system_score_codex":0.00044776287,"about_ca_system_score_gemma":0.00041158713,"threshold_uncertainty_score":0.91904944},"labels":[],"label_agreement":null},{"id":"W3131101190","doi":"10.1002/wcs.1556","title":"Resource‐rational approach to meta‐control problems across the lifespan","year":2021,"lang":"en","type":"review","venue":"Wiley Interdisciplinary Reviews Cognitive Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada; Deutsche Forschungsgemeinschaft","keywords":"Psychology; Cognition; Control (management); Affect (linguistics); Resource (disambiguation); Adaptation (eye); Cognitive aging; Meta-analysis; Cognitive psychology; Computer science; Medicine; Artificial intelligence","score_opus":0.37619018900321216,"score_gpt":0.5136070250188354,"score_spread":0.1374168360156232,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3131101190","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00003761603,0.97596765,0.0069788783,0.0005535469,0.0010841929,0.0048840903,0.00083476695,0.00005498627,0.00960425],"genre_scores_gemma":[0.00058839726,0.9894513,0.0012326154,0.0013756776,0.0007293023,0.0034459902,0.0001312153,0.00009797878,0.002947544],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9841558,0.002792213,0.0044793054,0.0039768713,0.0032334493,0.001362414],"domain_scores_gemma":[0.9862237,0.0056879353,0.0026476404,0.0029517193,0.0017182947,0.0007707084],"candidate_categories":["metaresearch","metaepi_narrow","sts","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["metaresearch","metaepi_narrow"],"category_scores_codex":[0.0345606,0.0012785356,0.0061643254,0.0008132368,0.0027361668,0.00373106,0.008142988,0.00032930519,0.00044804226],"category_scores_gemma":[0.010951134,0.00063131715,0.0036913336,0.0073695183,0.0023062264,0.0011488609,0.007242307,0.0013687635,0.0043751183],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000854982,0.00019102529,0.0000022272206,0.0002717764,0.00016618625,0.000012145477,0.0013331312,0.000022255554,3.7045848e-7,0.00011063399,0.010744928,0.9871368],"study_design_scores_gemma":[0.00015205651,0.00015070204,0.0000064411292,0.011962125,0.0021333557,0.0003185036,0.001633342,0.00013295776,4.2737832e-7,0.0014581683,0.98122644,0.00082545774],"about_ca_topic_score_codex":0.0000032920877,"about_ca_topic_score_gemma":0.000021423903,"teacher_disagreement_score":0.9863113,"about_ca_system_score_codex":0.00035793363,"about_ca_system_score_gemma":0.001307201,"threshold_uncertainty_score":0.99999666},"labels":[],"label_agreement":null},{"id":"W3133134432","doi":"10.2308/jmar-2019-505","title":"Needs Versus Wants: The Mental Accounting and Effort Effects of Tangible Rewards","year":2021,"lang":"en","type":"article","venue":"Journal of Management Accounting Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Mental accounting; Earnings; Psychology; Marketing; Business; Accounting; Finance","score_opus":0.13582815606805385,"score_gpt":0.45550477442668597,"score_spread":0.31967661835863215,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3133134432","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9913644,0.00081278296,0.00009828806,0.0011625857,0.0014186823,0.00018831056,0.0000018749029,0.000006160949,0.004946915],"genre_scores_gemma":[0.997462,0.00035330077,0.00094633445,0.000062947845,0.00023728874,0.0000031211318,5.96892e-7,0.000016637574,0.00091781333],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99461204,0.00025865613,0.0010939378,0.0002897954,0.003301004,0.00044456002],"domain_scores_gemma":[0.9934726,0.0036882046,0.00071455544,0.00059019856,0.0014469376,0.00008751528],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.019615,0.00014244187,0.00041023764,0.0011023111,0.0004440701,0.001110868,0.0012774976,0.000072811985,0.00012498458],"category_scores_gemma":[0.0041474453,0.00009003892,0.00020160638,0.0019014385,0.00020988025,0.0007915418,0.0012523786,0.0005492167,0.000040746363],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004555668,0.00023767632,0.046138093,0.000105218394,0.00023232243,0.0003761062,0.0011153036,0.00007338552,0.0018724124,0.000744707,0.034085706,0.9145635],"study_design_scores_gemma":[0.018848978,0.0024967315,0.31635362,0.004065294,0.0008445458,0.00064669386,0.13349819,0.005002411,0.033223912,0.078613736,0.40488532,0.0015205569],"about_ca_topic_score_codex":0.000018182354,"about_ca_topic_score_gemma":0.000010873924,"teacher_disagreement_score":0.91304296,"about_ca_system_score_codex":0.00012363518,"about_ca_system_score_gemma":0.00011965984,"threshold_uncertainty_score":0.9999261},"labels":[],"label_agreement":null},{"id":"W3133539121","doi":"10.2139/ssrn.3765027","title":"Proximity Bias: Motivated Effects of Spatial Distance on Probability Judgments","year":2021,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Quest University Canada","funders":"","keywords":"Econometrics; Statistics; Statistical physics; Computer science; Psychology; Mathematics; Physics","score_opus":0.06695565864701353,"score_gpt":0.3383551975670852,"score_spread":0.2713995389200717,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3133539121","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9836493,0.00028672212,0.014418326,0.0003165369,0.00069305906,0.0001988995,0.000007984983,0.000018339626,0.00041082042],"genre_scores_gemma":[0.9988656,0.0001366629,0.00024018457,0.000062444786,0.00009573025,0.0000049003543,0.0000022035201,0.000014559053,0.0005777082],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9956918,0.0004727195,0.0009518716,0.0005492035,0.0011119705,0.0012224814],"domain_scores_gemma":[0.9969756,0.0010629136,0.0006552125,0.00065300224,0.0005270539,0.00012622346],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005045527,0.0001983876,0.00047028172,0.00014849503,0.00019599896,0.000181769,0.0006905708,0.0001089183,0.00008567452],"category_scores_gemma":[0.0060997508,0.00014388036,0.00026966826,0.0005270642,0.00009700065,0.00031101308,0.0001164838,0.001220107,0.00007742568],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027977035,0.0010026838,0.036587887,0.000011690578,0.00006810953,0.000035824713,0.0001229041,0.00025337015,0.0016830191,0.009699365,0.00014550964,0.95010984],"study_design_scores_gemma":[0.0009094197,0.00062588864,0.01278243,0.00009273264,0.000026338263,0.00008989051,0.00021178286,0.00021174419,0.011488131,0.97266054,0.000714764,0.0001863072],"about_ca_topic_score_codex":0.000036346217,"about_ca_topic_score_gemma":0.0006703177,"teacher_disagreement_score":0.9629612,"about_ca_system_score_codex":0.0007921619,"about_ca_system_score_gemma":0.0019713587,"threshold_uncertainty_score":0.7302412},"labels":[],"label_agreement":null},{"id":"W3135620714","doi":"10.3390/g12010020","title":"A Generalization of Quantal Response Equilibrium via Perturbed Utility","year":2021,"lang":"en","type":"article","venue":"Games","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Mathematical economics; Generalization; Best response; Expected utility hypothesis; Preference; Logit; Separable space; Outcome (game theory); Complementarity (molecular biology); Isoelastic utility; Economics; Quadratic equation; Mathematical optimization; Mathematics; Game theory; Econometrics; Microeconomics","score_opus":0.13973826344195597,"score_gpt":0.403918342080461,"score_spread":0.264180078638505,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3135620714","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9943603,0.00021383772,0.003527801,0.00058969297,0.00057128427,0.00005218846,0.000034502067,0.00002652135,0.00062382675],"genre_scores_gemma":[0.99640083,0.000005780686,0.0017989222,0.00014957189,0.000042776865,0.0000022155045,0.000007886224,0.00000825178,0.0015837899],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99784106,0.000387195,0.00064530806,0.00042404849,0.00054176437,0.00016060614],"domain_scores_gemma":[0.9975982,0.0010156761,0.00021331053,0.0007093816,0.00038703208,0.000076435026],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0019634594,0.00010211983,0.00029199544,0.00013341752,0.00004474225,0.00013050844,0.00035579575,0.000083724546,0.0012999722],"category_scores_gemma":[0.003971148,0.0000811144,0.00016477551,0.00048360543,0.00009615477,0.00022130879,0.00018145473,0.00007394838,0.00016896786],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011650136,0.00034483333,0.035344932,0.000006006896,0.00001745058,0.00007319232,0.0013324562,0.00030721846,0.17502002,0.0003275019,0.012413424,0.77364796],"study_design_scores_gemma":[0.0018158199,0.00044459963,0.3913422,0.00008875338,0.000072481525,0.00023002164,0.0030173473,0.07651006,0.19589478,0.19450165,0.1351709,0.00091139716],"about_ca_topic_score_codex":0.000023658356,"about_ca_topic_score_gemma":0.000029618448,"teacher_disagreement_score":0.77273655,"about_ca_system_score_codex":0.000026491125,"about_ca_system_score_gemma":0.00017861449,"threshold_uncertainty_score":0.999613},"labels":[],"label_agreement":null},{"id":"W3135764196","doi":"10.1257/mic.20210361","title":"Decreasing Impatience","year":2023,"lang":"en","type":"preprint","venue":"American Economic Journal Microeconomics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Canada Research Chairs; National Science Foundation","keywords":"Economics; Convexity; Normative; Axiom; Hyperbolic discounting; Econometrics; Mathematical economics; Property (philosophy); Outcome (game theory); Microeconomics; Mathematics; Discounting; Financial economics; Finance","score_opus":0.21415231905560014,"score_gpt":0.45124194714897864,"score_spread":0.2370896280933785,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3135764196","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9817562,0.00020280702,0.0018980706,0.002102962,0.0116728125,0.0003339836,0.0004690636,0.00016717071,0.0013969003],"genre_scores_gemma":[0.9787197,0.0016747317,0.014682974,0.0011983814,0.002210735,0.000030310135,0.000041808267,0.000290628,0.0011507256],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99142325,0.00038418043,0.0044291145,0.002126518,0.00041347215,0.0012234623],"domain_scores_gemma":[0.9871341,0.002512733,0.006686498,0.0024627757,0.0003099277,0.0008939525],"candidate_categories":["metaepi_narrow","scholarly_communication","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0063973637,0.000930052,0.0023569039,0.0018025342,0.00059004873,0.0047361883,0.0053077983,0.00039069314,0.000704845],"category_scores_gemma":[0.001420529,0.0009005224,0.0013809412,0.0002934403,0.0009738045,0.0008151259,0.0030164171,0.0023269006,0.013292546],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011205815,0.00007177627,0.022950903,0.000005301977,0.00017881171,0.00009078881,0.0005499301,0.03127884,0.000047147292,0.00017227302,0.037090216,0.9074519],"study_design_scores_gemma":[0.00122755,0.0005032737,0.015886957,0.0002997335,0.00024213822,0.0019669086,0.00683835,0.023157012,0.00022502635,0.80890816,0.13727677,0.0034681207],"about_ca_topic_score_codex":0.00093676563,"about_ca_topic_score_gemma":0.0005935679,"teacher_disagreement_score":0.90398383,"about_ca_system_score_codex":0.0026224696,"about_ca_system_score_gemma":0.002209586,"threshold_uncertainty_score":0.9999748},"labels":[],"label_agreement":null},{"id":"W314086708","doi":"10.1093/oxfordhb/9780199734689.013.0017","title":"Judgmental Heuristics: A Historical Overview","year":2012,"lang":"en","type":"book-chapter","venue":"Oxford University Press eBooks","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; University of British Columbia","funders":"","keywords":"Heuristics; Normative; Computer science; Psychology; Social heuristics; Management science; Epistemology; Political science; Law; Economics","score_opus":0.22967725201946565,"score_gpt":0.3235526811290206,"score_spread":0.09387542910955493,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W314086708","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005029642,0.00085849897,0.0003047367,0.00003537428,0.001435967,0.0002468173,0.0002387925,0.000093719,0.9962831],"genre_scores_gemma":[0.0017769147,0.0005044044,0.0005662786,0.00009697521,0.00026509957,5.0664323e-7,0.000015982967,0.000048892605,0.99672496],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9969823,0.000065976004,0.0006379623,0.0008313862,0.0010758204,0.00040657152],"domain_scores_gemma":[0.99702245,0.0005001768,0.0006783456,0.0011858623,0.00022492361,0.00038822513],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006612283,0.00045452162,0.0008213361,0.00039312695,0.00027841213,0.00018713008,0.001632372,0.00054790697,0.0008667606],"category_scores_gemma":[0.000083322,0.00043761745,0.00057925197,0.000019185809,0.00016623343,0.00022711433,0.0010408558,0.0005751818,0.00011983092],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011954208,0.00005229908,0.00003511401,0.000012940494,0.000055052205,0.00021399865,0.00012780508,0.0000033785118,0.0000030607464,0.28631958,0.083973445,0.6290838],"study_design_scores_gemma":[0.00030066134,0.00007699622,0.000011209592,0.00007633171,0.00018002809,0.000022840357,0.000023546925,0.000019819941,0.0000045062543,0.017842803,0.9809612,0.0004800769],"about_ca_topic_score_codex":0.000055906574,"about_ca_topic_score_gemma":0.000025731335,"teacher_disagreement_score":0.89698774,"about_ca_system_score_codex":0.0012489164,"about_ca_system_score_gemma":0.00011541635,"threshold_uncertainty_score":0.99980754},"labels":[],"label_agreement":null},{"id":"W3147116413","doi":"10.3390/jrfm14040158","title":"The Standard Model of Rational Risky Decision-Making","year":2021,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Expected utility hypothesis; Mathematical economics; Axiom; Von Neumann–Morgenstern utility theorem; Subjective expected utility; Von Neumann architecture; Certainty; Prospect theory; Random variable; Valuation (finance); Variable (mathematics); Mathematics; Economics; Microeconomics","score_opus":0.04077975711709097,"score_gpt":0.340680903056284,"score_spread":0.29990114593919304,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3147116413","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6692564,0.0007548384,0.3285117,0.00015041302,0.0006328368,0.000047495887,0.00003064657,0.0000019906918,0.0006137101],"genre_scores_gemma":[0.9687639,0.002207246,0.028746659,0.00006493755,0.000099701545,8.984154e-7,2.0134817e-7,0.0000055459664,0.000110918445],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99736315,0.00008557132,0.0011497097,0.0001954919,0.0010621959,0.00014387794],"domain_scores_gemma":[0.9963731,0.001614254,0.000924784,0.00030543038,0.0007205118,0.000061899605],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003764235,0.00010084708,0.0003309677,0.00019406497,0.00034227196,0.00028011104,0.00044465065,0.00004922891,0.000037876252],"category_scores_gemma":[0.0030539178,0.00006075065,0.00020668653,0.0003352698,0.00009072587,0.00022988979,0.000249555,0.00018804656,0.0000065971217],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025445275,0.000037430684,0.002849447,0.0000014614267,0.000008556655,0.000037263046,0.00014850624,0.008742747,0.0000058300247,0.007297217,0.0035541237,0.97706294],"study_design_scores_gemma":[0.0006342917,0.00010940142,0.017128985,0.00011349994,0.00007087331,0.000028918694,0.0008601092,0.005498639,0.00004847717,0.8893876,0.08600775,0.00011146052],"about_ca_topic_score_codex":0.0000012777626,"about_ca_topic_score_gemma":0.000031261596,"teacher_disagreement_score":0.9769515,"about_ca_system_score_codex":0.000039534585,"about_ca_system_score_gemma":0.00015648376,"threshold_uncertainty_score":0.36560455},"labels":[],"label_agreement":null},{"id":"W3152131359","doi":"10.31235/osf.io/u62cx","title":"The Social Determinants of Cognitive Bias: The Effects of Low Capability on Decision Making in a Framing Experiment","year":2017,"lang":"en","type":"article","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Framing (construction); Framing effect; Loss aversion; Prospect theory; Cognitive bias; Social psychology; Psychology; Behavioral economics; Cognition; Economics; Positive economics; Microeconomics; Geography","score_opus":0.13064716839919457,"score_gpt":0.46763397908753984,"score_spread":0.33698681068834524,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3152131359","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9978887,0.000041701398,0.00019385084,0.000058745503,0.00060429185,0.00036310186,0.000006168436,0.0000050649455,0.0008384084],"genre_scores_gemma":[0.9997233,0.000006848179,0.0001294522,0.00004406256,0.00003097769,0.000019428984,8.508477e-8,0.0000075990356,0.00003820253],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99732375,0.0002669686,0.00093884603,0.00039519966,0.0008452632,0.00022997257],"domain_scores_gemma":[0.97466093,0.023218933,0.000934496,0.00093388057,0.00022182908,0.000029908335],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.004515498,0.00014612444,0.00041534196,0.00011127521,0.0008098116,0.0003194549,0.0014312,0.00009811277,0.000036505066],"category_scores_gemma":[0.025488012,0.00006782905,0.00019371588,0.00013646006,0.00054871204,0.00018987487,0.00043622978,0.00015924193,0.000026213564],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023784937,0.00015732614,0.041714717,0.000004113619,0.0000036351273,0.0000059106274,0.0025510944,0.000007850093,0.00017466662,0.000078775054,0.000061839084,0.95500225],"study_design_scores_gemma":[0.0014479632,0.0004920493,0.8865085,0.0014474504,0.00002049632,0.0000030290596,0.0113833705,0.0035923964,0.036963116,0.057806034,0.00007612907,0.00025945134],"about_ca_topic_score_codex":0.00012071014,"about_ca_topic_score_gemma":0.0006744963,"teacher_disagreement_score":0.9547428,"about_ca_system_score_codex":0.000053972137,"about_ca_system_score_gemma":0.0000665311,"threshold_uncertainty_score":0.98272073},"labels":[],"label_agreement":null},{"id":"W3152805028","doi":"10.1080/20954816.2020.1827500","title":"Willingness to pay to reduce future risk: a fundamental issue to invest in prevention behaviour","year":2020,"lang":"en","type":"article","venue":"Economic and Political Studies","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; McGill University; Center for Interuniversity Research and Analysis on Organizations","funders":"","keywords":"Lottery; Endowment effect; Willingness to pay; Actuarial science; Economics; Control (management); Cash; Willingness to accept; Endowment; Microeconomics; Finance","score_opus":0.16369699794284187,"score_gpt":0.446054803544856,"score_spread":0.2823578056020141,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3152805028","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9571511,0.00010948908,0.00008139987,0.040924117,0.00080133695,0.00033759544,0.00012438367,0.000022108445,0.000448446],"genre_scores_gemma":[0.9926537,0.000026877184,0.00096973666,0.0049292324,0.0007914437,0.000041470506,0.0000017706199,0.000013199869,0.0005725279],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9978416,0.000095994044,0.0007213072,0.000731706,0.0001619089,0.00044748615],"domain_scores_gemma":[0.99849045,0.000371828,0.00008363078,0.00023555348,0.00005088011,0.0007676808],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00075142755,0.00020037047,0.0005272673,0.00013594248,0.00016579618,0.000230073,0.00033687774,0.00007226668,0.00018999593],"category_scores_gemma":[0.0008688988,0.00014776338,0.00008331899,0.0002105695,0.00007662335,0.00017399962,0.00047694883,0.00016258097,0.0018120599],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000344366,0.00017478803,0.5610137,0.000012388658,0.000051469804,0.000023761213,0.013321135,0.00042294347,0.00004977591,0.009015808,0.06294189,0.352628],"study_design_scores_gemma":[0.0010920656,0.0015295558,0.5217036,0.00011179682,0.00006709152,0.00001246466,0.04705845,0.0002057316,0.00041528873,0.057090066,0.36973593,0.0009779595],"about_ca_topic_score_codex":0.000252981,"about_ca_topic_score_gemma":0.0005627685,"teacher_disagreement_score":0.35165003,"about_ca_system_score_codex":0.00022171781,"about_ca_system_score_gemma":0.000051518506,"threshold_uncertainty_score":0.99896514},"labels":[],"label_agreement":null},{"id":"W3154981307","doi":"10.1162/jocn_a_01721","title":"Does Ventromedial Prefrontal Cortex Damage Really Increase Impulsiveness? Delay and Probability Discounting in Patients with Focal Lesions","year":2021,"lang":"en","type":"article","venue":"Journal of Cognitive Neuroscience","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; York University","funders":"Natural Sciences and Engineering Research Council of Canada; National Institute on Aging; National Institutes of Health; York University","keywords":"Ventromedial prefrontal cortex; Psychology; Discounting; Temporal discounting; Probabilistic logic; Prefrontal cortex; Delay discounting; Impulsivity; Developmental psychology; Social psychology; Cognition; Neuroscience; Statistics; Economics","score_opus":0.03323203935288998,"score_gpt":0.3291510226263755,"score_spread":0.29591898327348554,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3154981307","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99804175,0.000010557709,0.00088342483,0.00012409965,0.0006391624,0.00015967415,0.0000630717,0.0000038666726,0.000074402895],"genre_scores_gemma":[0.9993404,0.000009437135,0.00038950736,0.00017458959,0.000050594303,0.0000021777025,0.000001783925,0.000008007839,0.000023472698],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99680936,0.00032996509,0.00085713726,0.0005328997,0.0011964279,0.00027420575],"domain_scores_gemma":[0.9961481,0.001538361,0.0007503331,0.00020583073,0.0011215115,0.00023587435],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0017143119,0.00015712735,0.00039539664,0.00023790081,0.00019292861,0.00042188834,0.0004168912,0.000049816204,0.000028660499],"category_scores_gemma":[0.010807028,0.000084349376,0.000083262705,0.0006139823,0.00050134136,0.0012894,0.00027249957,0.00034301876,0.0000027514566],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006228078,0.0006814069,0.91379946,0.0000031626598,0.0000025988552,0.0005274035,0.00028684473,0.000057139354,0.002968381,0.00001066984,0.0000084329085,0.08103172],"study_design_scores_gemma":[0.0013133761,0.0005793156,0.9928752,0.00016867006,0.000021857755,0.000075852375,0.00043692076,0.00019812009,0.00015744832,0.0040012314,0.000045160326,0.00012682112],"about_ca_topic_score_codex":0.000016650138,"about_ca_topic_score_gemma":0.0002038363,"teacher_disagreement_score":0.08090489,"about_ca_system_score_codex":0.00006324206,"about_ca_system_score_gemma":0.00047346632,"threshold_uncertainty_score":0.9975254},"labels":[],"label_agreement":null},{"id":"W3155792879","doi":"10.1017/s1930297500005404","title":"Cultivating credibility with probability words and numbers","year":2019,"lang":"en","type":"article","venue":"Judgment and Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"Ministère de la Défense Nationale","keywords":"Credibility; Probability distribution; Psychology; Probability model; Econometrics; Computer science; Statistics; Social psychology; Mathematics","score_opus":0.0810091612559306,"score_gpt":0.36920782972218935,"score_spread":0.28819866846625875,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3155792879","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9889158,0.0000904716,0.0055976035,0.00013036498,0.00032545842,0.00043911804,0.000006775152,0.000051125444,0.0044432785],"genre_scores_gemma":[0.94697887,0.0000076390725,0.052549347,0.00019151905,0.000041106174,0.0000087645485,7.5128787e-7,0.000015246971,0.0002067313],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.996419,0.00008995808,0.00087167736,0.0011576213,0.0011266796,0.0003350389],"domain_scores_gemma":[0.9951638,0.00327288,0.00036560497,0.00084512215,0.00019100023,0.0001616104],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0038765445,0.00025722847,0.0005009784,0.00021370812,0.00026406243,0.00081951526,0.0003768414,0.000121879384,0.0005460397],"category_scores_gemma":[0.0014134485,0.0001640073,0.000083044324,0.00048163056,0.00015668717,0.0006184333,0.0004706483,0.00022965489,0.0001442457],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020607076,0.000042064472,0.34460244,0.000004721346,0.00000448448,0.0000039674937,0.0003195002,0.00013411393,0.00005879185,0.00021299836,0.00031181905,0.65409905],"study_design_scores_gemma":[0.0022716005,0.0004929829,0.23420161,0.0005869805,0.000038051498,0.00007894778,0.0038992125,0.013043474,0.0000879282,0.7347111,0.009732649,0.0008554679],"about_ca_topic_score_codex":0.000017586652,"about_ca_topic_score_gemma":0.000057285088,"teacher_disagreement_score":0.7344981,"about_ca_system_score_codex":0.000077157165,"about_ca_system_score_gemma":0.000049244925,"threshold_uncertainty_score":0.79026043},"labels":[],"label_agreement":null},{"id":"W3157959619","doi":"10.1017/s0140525x20000953","title":"Pleas for patience from the cumulative future self","year":2021,"lang":"en","type":"letter","venue":"Behavioral and Brain Sciences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canada Auto Workers; The Scarborough Hospital; University of Toronto","funders":"","keywords":"Patience; Set (abstract data type); Power (physics); Intertemporal choice; Psychology; Social psychology; Term (time); Economics; Microeconomics; Computer science","score_opus":0.2442724312796611,"score_gpt":0.42748739271484537,"score_spread":0.18321496143518426,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3157959619","genre_codex":"empirical","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5043911,0.0007025318,0.00009206467,0.49045587,0.0026005025,0.00050115376,0.0010320791,0.000053297026,0.0001714012],"genre_scores_gemma":[0.06782403,0.00012333096,0.012064695,0.9019279,0.012049091,0.00024759304,0.00044105822,0.00008183155,0.0052404674],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9941485,0.00039009852,0.0009911151,0.0018577274,0.001970344,0.0006422196],"domain_scores_gemma":[0.99087095,0.006918098,0.000723699,0.0008958658,0.00046494365,0.000126413],"candidate_categories":["metaepi_narrow","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.002868883,0.00048814394,0.0007511072,0.00018821844,0.0014187251,0.0026470164,0.0026699184,0.0006298762,0.0004047934],"category_scores_gemma":[0.0008783821,0.00026180837,0.00039422364,0.0009365338,0.0010803945,0.00064461067,0.00055343466,0.0008909724,0.00006424194],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000068984587,0.0000430337,0.002848996,0.0000018034359,0.000005409487,0.000037370417,0.0010768042,0.0000029596004,0.000012165367,0.000039925744,0.81526756,0.18065704],"study_design_scores_gemma":[0.00022667756,0.00027001352,0.003436609,0.000060640967,0.00007240724,0.000017954133,0.0026298175,0.0002634726,0.000018146362,0.03214281,0.9603683,0.0004931757],"about_ca_topic_score_codex":0.0004531817,"about_ca_topic_score_gemma":0.00031861744,"teacher_disagreement_score":0.43656707,"about_ca_system_score_codex":0.00005473557,"about_ca_system_score_gemma":0.00041146914,"threshold_uncertainty_score":0.99998343},"labels":[],"label_agreement":null},{"id":"W3158170300","doi":"10.7202/1091798ar","title":"La dictature des 3P :Prévention, Prudence, Précaution","year":2013,"lang":"fr","type":"article","venue":"Assurances et gestion des risques","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Prudence; Humanities; Political science; Philosophy; Epistemology","score_opus":0.09123075887161222,"score_gpt":0.3840317167062193,"score_spread":0.292800957834607,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3158170300","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9342702,0.014146458,0.0078011854,0.0088461125,0.003068692,0.0005541849,0.000093696915,0.00025539735,0.030964077],"genre_scores_gemma":[0.9594936,0.0060731517,0.01350148,0.0002209943,0.00024986223,0.000104659084,0.000029004033,0.000043475397,0.020283785],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9944908,0.0015148796,0.0012676877,0.0009876214,0.0010548716,0.0006841495],"domain_scores_gemma":[0.9945543,0.0025542602,0.00061855407,0.0007019961,0.0012328164,0.00033809672],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.003734065,0.0004875415,0.0006015881,0.00043529947,0.00069400255,0.0023073906,0.0008838818,0.0007164004,0.003564825],"category_scores_gemma":[0.002993734,0.00041638906,0.00037163013,0.0011858015,0.0018472071,0.004997058,0.00017002712,0.00074024836,0.004137846],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029802743,0.00028267797,0.017042037,0.00005201804,0.000030803996,0.000020428011,0.0011346474,0.0026477443,0.00015455211,0.0022109582,0.046676695,0.92971766],"study_design_scores_gemma":[0.00047089095,0.00030813253,0.28960705,0.0016352598,0.000106026535,0.00019071643,0.0015078615,0.008945609,0.0003883158,0.514985,0.18118918,0.0006659203],"about_ca_topic_score_codex":0.0011245179,"about_ca_topic_score_gemma":0.001024909,"teacher_disagreement_score":0.9290517,"about_ca_system_score_codex":0.00032644646,"about_ca_system_score_gemma":0.0002058609,"threshold_uncertainty_score":0.9998288},"labels":[],"label_agreement":null},{"id":"W3159193802","doi":"","title":"Graphical Depiction of Statistical Information Improves Gambling-Related Judgments","year":2019,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Preference; Presentation (obstetrics); Psychology; Scratch; Domain (mathematical analysis); Computer science; Information retrieval; Statistics; Mathematics; Medicine","score_opus":0.02798652188078146,"score_gpt":0.3424345583327339,"score_spread":0.31444803645195246,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3159193802","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9696661,0.00006646605,0.02840336,0.00015092705,0.000804006,0.00011550542,0.00000828849,0.000016183147,0.00076913316],"genre_scores_gemma":[0.99923146,0.00016339771,0.00029294295,0.000045538076,0.000033461656,0.0000011923754,0.0000068209565,0.0000076933065,0.0002174994],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99671143,0.00011281244,0.0011993363,0.00019694636,0.000885194,0.0008942826],"domain_scores_gemma":[0.9982745,0.00037212926,0.00066358125,0.00027844077,0.00031521704,0.0000961041],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0051018614,0.00012571832,0.0002922451,0.00048095838,0.00010884535,0.00020331045,0.00047053682,0.00011910539,0.00019821998],"category_scores_gemma":[0.0007935914,0.00009338765,0.00015282677,0.00044814634,0.0000587072,0.0010573259,0.00006060889,0.0010909103,0.0006268099],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011401046,0.00007482216,0.012016245,0.0000016983466,0.00004153264,5.9797253e-7,0.00010330415,0.00018647766,0.0007044729,0.046289373,0.0001689799,0.9402985],"study_design_scores_gemma":[0.00082358456,0.000609996,0.015469679,0.000014942459,0.000024698718,0.00016038113,0.000840971,0.0030834991,0.00008872893,0.9775967,0.0011489461,0.0001378667],"about_ca_topic_score_codex":0.00002302622,"about_ca_topic_score_gemma":0.000044356264,"teacher_disagreement_score":0.94016063,"about_ca_system_score_codex":0.0002832458,"about_ca_system_score_gemma":0.00075387716,"threshold_uncertainty_score":0.8056582},"labels":[],"label_agreement":null},{"id":"W3160244203","doi":"10.1016/j.neurobiolaging.2021.05.001","title":"Associations between phasic arousal and decisions under risk in younger and older adults","year":2021,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Arousal; Pupillary response; Psychology; Pupillometry; Developmental psychology; Low arousal theory; Audiology; Young adult; Pupil; Medicine; Social psychology; Neuroscience","score_opus":0.08219081522370424,"score_gpt":0.37096814494627334,"score_spread":0.2887773297225691,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3160244203","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99831843,0.00020638008,0.00019932244,0.00072771736,0.00024341908,0.000066650166,0.000106699576,0.00001235003,0.000119017146],"genre_scores_gemma":[0.9988955,0.0000982434,0.0006915122,0.00021727156,0.000032527474,0.0000015103534,0.000010766816,0.0000081377175,0.000044478846],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99820167,0.00028179822,0.0006256059,0.00053763,0.0001513846,0.00020190992],"domain_scores_gemma":[0.99466634,0.004550267,0.00028442751,0.00029600214,0.00013629315,0.00006665949],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009094813,0.00011364248,0.00040776152,0.00025238222,0.00012648162,0.0000751474,0.00019029409,0.00012312029,0.000041380543],"category_scores_gemma":[0.0016082779,0.00009595212,0.000056824607,0.00034754307,0.00014908648,0.0001911334,0.0002265806,0.0002418587,0.000015536874],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009944722,0.000058158734,0.86193395,6.5350287e-7,0.000010467481,0.000012992532,0.0003675374,0.000057011912,0.0002661427,0.00008643845,0.0001949521,0.13700172],"study_design_scores_gemma":[0.0005826112,0.000035731286,0.97566986,0.000035212124,0.000021632351,0.000017125785,0.00048568784,0.00006656731,0.00021455345,0.022677178,0.00009769956,0.000096156895],"about_ca_topic_score_codex":0.000080640595,"about_ca_topic_score_gemma":0.00018609327,"teacher_disagreement_score":0.13690557,"about_ca_system_score_codex":0.000017806826,"about_ca_system_score_gemma":0.00004951069,"threshold_uncertainty_score":0.3912814},"labels":[],"label_agreement":null},{"id":"W3160674630","doi":"10.31234/osf.io/qsnea","title":"A Tutorial on Cognitive Modeling for Cognitive Aging Research","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital","funders":"","keywords":"Cognition; Cognitive aging; Cognitive model; Computer science; Cognitive psychology; Structural equation modeling; Psychology; Artificial intelligence; Machine learning","score_opus":0.8028651390569861,"score_gpt":0.6151710269779309,"score_spread":0.18769411207905518,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3160674630","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7711293,0.00012715002,0.16163573,0.001727755,0.008639587,0.0030450718,0.0010563025,0.00021421464,0.052424874],"genre_scores_gemma":[0.99213624,0.000020925056,0.0026327504,0.0007506245,0.0024161977,0.00034034988,0.00009206904,0.00006352282,0.0015473351],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9928152,0.00048934884,0.0012924479,0.0023576939,0.0024016984,0.0006435963],"domain_scores_gemma":[0.9798059,0.014600673,0.00036472324,0.000678049,0.004193669,0.00035700283],"candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.008071112,0.00042997644,0.00091769267,0.0009794806,0.00048961,0.0019957812,0.0015272096,0.0005386749,0.00038338854],"category_scores_gemma":[0.027891608,0.00034293073,0.0005710045,0.00054720085,0.00017319513,0.00020579225,0.002353488,0.0018538298,0.0015712326],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014630432,0.00027094985,0.000059381924,0.000025880987,0.000060341543,0.000028856373,0.0011472411,0.0025636202,0.000018967083,0.0022408224,0.011934016,0.9801869],"study_design_scores_gemma":[0.0010550409,0.0004020475,0.000009057235,0.0011911972,0.000070074,0.0000026870657,0.0073465393,0.20625046,0.00023879537,0.779522,0.0033409202,0.00057120004],"about_ca_topic_score_codex":0.00017631051,"about_ca_topic_score_gemma":0.00005145499,"teacher_disagreement_score":0.9796157,"about_ca_system_score_codex":0.0001976663,"about_ca_system_score_gemma":0.0014373498,"threshold_uncertainty_score":0.99990225},"labels":[],"label_agreement":null},{"id":"W3161513602","doi":"10.31234/osf.io/yt9cm","title":"Using Icon Arrays to Communicate Gambling Information Reduces the Appeal of Scratch Card Games","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Icon; Appeal; Salience (neuroscience); Scratch; Computer science; Psychology; Perception; Feeling; Information seeking; Advertising; Internet privacy; Social psychology; Cognitive psychology; Information retrieval; Business; Political science","score_opus":0.47784076430262523,"score_gpt":0.4782812633588952,"score_spread":0.00044049905626997177,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3161513602","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96212393,0.00006153014,0.022729073,0.0051103407,0.0011339019,0.00048906915,0.0000762047,0.00006224453,0.008213727],"genre_scores_gemma":[0.97787637,0.00003925028,0.020952392,0.0009273056,0.00009910815,0.000011305765,0.000017453614,0.000014613388,0.00006219844],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99604505,0.00026570982,0.0018775366,0.0004735273,0.0010817313,0.0002564391],"domain_scores_gemma":[0.99518645,0.00092098914,0.0011873144,0.0019351173,0.0006156089,0.0001545014],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.003754759,0.00028905488,0.0007593903,0.0004107796,0.00023264394,0.0012683003,0.003358667,0.00023949357,0.000107031294],"category_scores_gemma":[0.0017538342,0.00018110126,0.00034047346,0.0005940123,0.00015514069,0.00054126,0.0034627109,0.0006681025,0.00032308896],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014057933,0.00005803799,0.0007504333,0.000029014522,0.0000612836,0.0000020809716,0.010145251,0.09207448,0.0031176032,0.0008338483,0.015019783,0.8777676],"study_design_scores_gemma":[0.0010870657,0.00039379552,0.00246717,0.0016362919,0.00037835186,0.000027476985,0.06602784,0.3088796,0.039113656,0.48823446,0.08911872,0.0026355556],"about_ca_topic_score_codex":0.0006244966,"about_ca_topic_score_gemma":0.00005217884,"teacher_disagreement_score":0.875132,"about_ca_system_score_codex":0.000091082045,"about_ca_system_score_gemma":0.00031118435,"threshold_uncertainty_score":0.9997685},"labels":[],"label_agreement":null},{"id":"W3163279460","doi":"10.2139/ssrn.4771721","title":"Rational vs. Irrational Beliefs in a Complex World","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bank of Canada; Government of Canada","funders":"","keywords":"Irrational number; Psychology; Positive economics; Epistemology; Economics; Philosophy; Mathematics","score_opus":0.12356299317244869,"score_gpt":0.4096547294732133,"score_spread":0.2860917363007646,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3163279460","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9490823,0.0046611642,0.005521275,0.021382429,0.005513352,0.0005879988,0.00018059522,0.00010931772,0.012961564],"genre_scores_gemma":[0.9872745,0.00040026268,0.00086170045,0.00040808832,0.0012824055,0.000024246934,0.000073583775,0.0000476099,0.0096276],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99285275,0.0003036498,0.0019973267,0.0010321859,0.0019022562,0.0019118135],"domain_scores_gemma":[0.9973581,0.0007068741,0.000720971,0.0006368578,0.00041160427,0.00016558317],"candidate_categories":["metaepi_narrow","scholarly_communication","research_integrity","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.011588441,0.00042445006,0.00072947296,0.0019807518,0.00025203073,0.001738775,0.00183556,0.0002917885,0.0014068529],"category_scores_gemma":[0.0007628101,0.0003459249,0.00053274096,0.00090334524,0.00011748029,0.00025064018,0.0011372654,0.008155282,0.0016039499],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026434072,0.00038000217,0.0051617725,0.000013785263,0.0001883487,0.000107535794,0.0005413249,0.016553292,0.00007633031,0.35085616,0.043887667,0.58196944],"study_design_scores_gemma":[0.00035153097,0.00008284009,0.0034588287,0.00010317311,0.00002304867,0.0003104356,0.0003111562,0.0043915054,0.0000026631294,0.96866786,0.021940833,0.00035614285],"about_ca_topic_score_codex":0.000083801206,"about_ca_topic_score_gemma":0.014551911,"teacher_disagreement_score":0.6178117,"about_ca_system_score_codex":0.002777706,"about_ca_system_score_gemma":0.010410346,"threshold_uncertainty_score":0.99989927},"labels":[],"label_agreement":null},{"id":"W3163772508","doi":"10.1111/cogs.13041","title":"Plans or Outcomes: How Do We Attribute Intelligence to Others?","year":2021,"lang":"en","type":"article","venue":"Cognitive Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Attribution; Outcome (game theory); Planner; Psychology; Task (project management); Human intelligence; Cognitive psychology; Quality (philosophy); Artificial intelligence; Key (lock); Social psychology; Computer science; Developmental psychology","score_opus":0.33029010703308453,"score_gpt":0.4760305961946483,"score_spread":0.1457404891615638,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3163772508","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89271694,0.00010050258,0.0948744,0.0073596514,0.001567224,0.00025893917,0.00028376648,0.00006226588,0.0027763264],"genre_scores_gemma":[0.9904407,0.000036692,0.0028570276,0.0016214775,0.000051652914,0.000015367194,0.0000014833392,0.000012166049,0.0049634045],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99560386,0.00011651902,0.0005266285,0.0014262664,0.0017170884,0.0006096131],"domain_scores_gemma":[0.9934986,0.0032058558,0.00020541866,0.0008088825,0.0018034561,0.00047777616],"candidate_categories":["metaresearch","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.003465399,0.00023231143,0.00042223308,0.00049493706,0.00050980295,0.0020392805,0.0019031836,0.000071723705,0.0015191247],"category_scores_gemma":[0.025725754,0.00015297999,0.00014493336,0.004087197,0.00077663036,0.00094663055,0.00077031535,0.00019785759,0.003868526],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000035965168,0.00008645635,0.014292511,0.0000010976429,0.000004764978,0.00015802305,0.0010791405,0.000032376007,0.00062371953,0.00042037104,0.0011721854,0.9820934],"study_design_scores_gemma":[0.0015073615,0.0016061842,0.14135104,0.0014826847,0.0001430333,0.00064938917,0.19284877,0.002197654,0.16570334,0.2849885,0.20358555,0.0039364947],"about_ca_topic_score_codex":0.00000594592,"about_ca_topic_score_gemma":0.00012506873,"teacher_disagreement_score":0.9781569,"about_ca_system_score_codex":0.000111257075,"about_ca_system_score_gemma":0.00075785624,"threshold_uncertainty_score":0.99939364},"labels":[],"label_agreement":null},{"id":"W3164126022","doi":"10.1177/09567976211024254","title":"Noise Increases Anchoring Effects","year":2021,"lang":"en","type":"article","venue":"Psychological Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Quest University Canada","funders":"","keywords":"Anchoring; Stimulus (psychology); Psychology; Psychophysics; Perception; Cognitive psychology; Social psychology; Neuroscience","score_opus":0.17018581827456375,"score_gpt":0.48360973784537664,"score_spread":0.3134239195708129,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3164126022","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97347915,0.00012357329,0.0012367987,0.00045433582,0.0012145647,0.00007100186,0.0000030682593,0.00006842357,0.02334906],"genre_scores_gemma":[0.9939557,0.000016836091,0.0045030294,0.0010142213,0.00012942255,0.000007665238,4.3127451e-7,0.0000042531537,0.0003684448],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9963961,0.00014227914,0.00046317367,0.0012418332,0.0012800762,0.00047652365],"domain_scores_gemma":[0.99653363,0.0016313269,0.000135462,0.0009932318,0.00034696492,0.00035940052],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0035757406,0.00013874823,0.00027358814,0.00017233338,0.0004171014,0.0008404713,0.0016412473,0.00007708348,0.0009430345],"category_scores_gemma":[0.014226408,0.000089213085,0.00012408535,0.002527623,0.00065563334,0.00054218416,0.00047581157,0.0001842582,0.0018271656],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013648984,0.00033787536,0.022841392,6.82229e-7,9.0116407e-7,0.0001845176,0.00003509842,0.000031925294,0.022716664,0.0011612216,0.0022436033,0.9504325],"study_design_scores_gemma":[0.00052911777,0.00027185868,0.6835597,0.000041826977,0.00000954693,0.00019248729,0.00019407696,0.00047537993,0.010308768,0.28164852,0.022300934,0.00046775644],"about_ca_topic_score_codex":0.000010600354,"about_ca_topic_score_gemma":0.0000058981896,"teacher_disagreement_score":0.9499647,"about_ca_system_score_codex":0.000057050012,"about_ca_system_score_gemma":0.000073354946,"threshold_uncertainty_score":0.99997026},"labels":[],"label_agreement":null},{"id":"W3166550623","doi":"10.20944/preprints202106.0177.v1","title":"Choice Under Uncertainty and Ambiguity: An Empirical Inquiry of a Behavioral Economic Experiment Applied to COVID-19.","year":2021,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Ambiguity; Context (archaeology); Odds; Public health; Public economics; Actuarial science; Psychology; Coronavirus disease 2019 (COVID-19); Economics; Management science; Public relations; Political science; Medicine; Computer science","score_opus":0.6070011200828059,"score_gpt":0.5612884243724034,"score_spread":0.045712695710402484,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3166550623","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99495476,0.0000646204,0.000930896,0.0008263744,0.0015560632,0.00088805804,0.00010870849,0.000108816675,0.000561687],"genre_scores_gemma":[0.99679005,0.000022652219,0.0011163336,0.0013338362,0.00022773076,0.00022679579,0.000060985043,0.000055617395,0.00016601659],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9927039,0.00043747787,0.0021155162,0.003196279,0.0009917332,0.0005550571],"domain_scores_gemma":[0.9929886,0.0008527586,0.0009425761,0.0037351637,0.000268945,0.0012119958],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003861209,0.0006370665,0.0015284288,0.0006032312,0.00021151124,0.00042978142,0.0022566752,0.0006680641,0.0028180028],"category_scores_gemma":[0.0009393617,0.0006137676,0.00038564886,0.00029386222,0.00044423755,0.00026027625,0.0072674034,0.0007948783,0.00062805694],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005989239,0.0020215733,0.7483685,0.00007024844,0.00014789897,0.00006157335,0.026386151,0.14512427,0.008457217,0.00031300928,0.0011286481,0.067322],"study_design_scores_gemma":[0.0036209775,0.0005303968,0.8190741,0.00029155586,0.00046308705,0.000084991065,0.04579219,0.0031871856,0.018709628,0.066647016,0.03744064,0.004158259],"about_ca_topic_score_codex":0.0029511058,"about_ca_topic_score_gemma":0.0012452861,"teacher_disagreement_score":0.14193709,"about_ca_system_score_codex":0.0010164909,"about_ca_system_score_gemma":0.0014484654,"threshold_uncertainty_score":0.99963135},"labels":[],"label_agreement":null},{"id":"W3168391240","doi":"10.1093/ej/ueaf030","title":"The Dynamics of Inattention in the (Baseball) Field","year":2021,"lang":"en","type":"article","venue":"The Economic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canada Research Chairs","keywords":"Exploit; League; Scarcity; Download; Affect (linguistics); Work (physics); Economics; Computer science; Microeconomics; Psychology; Computer security; Engineering","score_opus":0.0817865970839414,"score_gpt":0.39000589164508775,"score_spread":0.3082192945611464,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3168391240","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9756465,0.00019185762,0.0005027715,0.017121408,0.0012795842,0.000052900636,0.000006526646,0.0000022207266,0.0051962105],"genre_scores_gemma":[0.99829304,0.00015038499,0.00006385706,0.00051006686,0.00013708805,0.0000017972637,7.492877e-7,0.000004839629,0.00083819794],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9982018,0.00037921284,0.00083668885,0.00015455279,0.00024868138,0.00017905374],"domain_scores_gemma":[0.99516785,0.0036218034,0.00047005079,0.00061569305,0.00009319516,0.00003137758],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0077126105,0.00007975307,0.0001774385,0.000072248265,0.00036646545,0.00061237597,0.0014381019,0.000048809394,0.00058255735],"category_scores_gemma":[0.000920473,0.000034571854,0.00019237367,0.00015098021,0.000097170036,0.00019129677,0.00013661882,0.00040135244,0.00012410323],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000464163,0.000041399086,0.0073818006,4.5587976e-7,0.000015487136,0.00002440161,0.0005369692,0.0019742742,0.000027170236,0.019463064,0.014627898,0.9558607],"study_design_scores_gemma":[0.0005999476,0.000110998546,0.032667927,0.000034498396,0.000028565993,0.0009396179,0.017116923,0.02648749,0.00020315363,0.8945579,0.027084803,0.00016816398],"about_ca_topic_score_codex":0.00004246185,"about_ca_topic_score_gemma":0.00168553,"teacher_disagreement_score":0.95569247,"about_ca_system_score_codex":0.00015062942,"about_ca_system_score_gemma":0.00020205072,"threshold_uncertainty_score":0.6378594},"labels":[],"label_agreement":null},{"id":"W3169178731","doi":"10.3386/w30910","title":"Dynamic Inconsistency in Risky Choice: Evidence from the Lab and Field","year":2023,"lang":"en","type":"report","venue":"National Bureau of Economic Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Field (mathematics); Data science; Econometrics; Psychology; Computer science; Economics; Mathematics","score_opus":0.7522762698277524,"score_gpt":0.6515421769172369,"score_spread":0.1007340929105155,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3169178731","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91670966,0.0037300412,0.000005963169,0.009418236,0.0023153054,0.00082004524,0.0005200005,0.00002686251,0.06645387],"genre_scores_gemma":[0.9882199,0.004629239,0.00017427518,0.00006147514,0.00036949787,0.000070301074,0.00006537271,0.00003499485,0.0063749338],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9930917,0.0005441088,0.0017567417,0.0011002443,0.0031184412,0.0003887815],"domain_scores_gemma":[0.9204147,0.0760737,0.0006693144,0.0009462385,0.0017853619,0.000110698704],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.02823741,0.0002291373,0.0007167968,0.0012414888,0.00020536334,0.00047483458,0.0020631377,0.00049399154,0.0008024749],"category_scores_gemma":[0.07072579,0.0001653508,0.00020058097,0.0006663326,0.00039533846,0.000386766,0.0010064616,0.0012509883,0.0008412533],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016724234,0.00011948529,0.17052795,0.000036701498,0.00011752571,0.000039816623,0.00049610564,0.0008403653,0.00005780406,0.0029220523,0.39092025,0.4337547],"study_design_scores_gemma":[0.00026693707,0.00009021136,0.08224504,0.00054090016,0.00001256152,0.000010022105,0.00036567074,0.0032475884,0.000011968907,0.89705396,0.015921896,0.0002332443],"about_ca_topic_score_codex":0.027259786,"about_ca_topic_score_gemma":0.033619944,"teacher_disagreement_score":0.8941319,"about_ca_system_score_codex":0.0011675687,"about_ca_system_score_gemma":0.0038973368,"threshold_uncertainty_score":0.9999367},"labels":[],"label_agreement":null},{"id":"W3170229078","doi":"10.1017/s1930297500007385","title":"Preferences for rank in competition: Is first-place seeking stronger than last-place aversion?","year":2020,"lang":"en","type":"article","venue":"Judgment and Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Competition (biology); Rank (graph theory); Risk aversion (psychology); Social psychology; Psychology; Expected utility hypothesis; Economics; Mathematical economics; Mathematics","score_opus":0.11650631349044685,"score_gpt":0.35977218640903547,"score_spread":0.24326587291858862,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3170229078","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9689533,0.0002570083,0.02561121,0.0026032845,0.0007933915,0.00056655717,0.00006361797,0.000056677483,0.0010949565],"genre_scores_gemma":[0.98479146,0.00006612486,0.0132287145,0.0015019714,0.00017727714,0.000030182327,0.0000058100272,0.00002352433,0.00017494355],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99610466,0.000090154346,0.0011270423,0.0011093122,0.0011276299,0.00044121037],"domain_scores_gemma":[0.99353486,0.005169482,0.00042139646,0.0004542316,0.00019928814,0.00022074598],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0019939668,0.0003209148,0.0006204277,0.00038969904,0.00041604982,0.00085657684,0.00074821844,0.0001800691,0.00079520524],"category_scores_gemma":[0.0012865141,0.00025554487,0.00020981499,0.00062988873,0.00008103267,0.0006362294,0.00045198487,0.0002498141,0.00025610946],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002057948,0.00018514764,0.06837499,0.00003495573,0.000025714031,0.000028411967,0.0036074652,0.0064862138,0.00009131799,0.00075906864,0.068574056,0.8497747],"study_design_scores_gemma":[0.009674354,0.0012440806,0.034961026,0.0017760587,0.00011469109,0.00003508826,0.011213867,0.3145009,0.00025538733,0.2627376,0.36154357,0.0019433787],"about_ca_topic_score_codex":0.000009741977,"about_ca_topic_score_gemma":0.0002186134,"teacher_disagreement_score":0.8478313,"about_ca_system_score_codex":0.000089216635,"about_ca_system_score_gemma":0.00006588648,"threshold_uncertainty_score":0.9999897},"labels":[],"label_agreement":null},{"id":"W3171185325","doi":"10.1111/phc3.12763","title":"Risky‐choice framing and rational decision‐making","year":2021,"lang":"en","type":"article","venue":"Philosophy Compass","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Framing (construction); Framing effect; Narrative; Epistemology; Psychology; Empirical research; Prospect theory; Management science; Social psychology; Computer science; Economics; Microeconomics; Philosophy","score_opus":0.14862799612947,"score_gpt":0.40913365641103544,"score_spread":0.2605056602815654,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3171185325","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9625116,0.0005769089,0.018179275,0.0029928247,0.0013084308,0.00010186036,0.000040383627,0.00006773497,0.014220991],"genre_scores_gemma":[0.9834956,0.000017562656,0.014954995,0.00092869886,0.00048145044,0.000006936247,0.000005904083,0.000018311433,0.00009054453],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99680436,0.00015384953,0.0008517788,0.00083897315,0.0010741822,0.00027684556],"domain_scores_gemma":[0.9926539,0.0056359814,0.00028060866,0.00076263904,0.0004979599,0.00016891648],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001194042,0.00021365467,0.0004419026,0.00025990882,0.00044220043,0.0008800631,0.00060298556,0.000111027046,0.0006895152],"category_scores_gemma":[0.0037611092,0.000183862,0.00016221874,0.00062242476,0.00012318212,0.00052912446,0.00046630553,0.00027474356,0.0005727403],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000051382714,0.00018120353,0.029481132,0.0000043175523,0.00002363915,0.000109031236,0.00024060592,0.0007269447,0.00025820395,0.022823203,0.007832078,0.93826824],"study_design_scores_gemma":[0.000407212,0.000027502012,0.031307984,0.0000829427,0.000016560003,0.000071294206,0.000100672405,0.006402342,0.00009946662,0.91330343,0.047907945,0.0002726166],"about_ca_topic_score_codex":0.00000688863,"about_ca_topic_score_gemma":0.000034358276,"teacher_disagreement_score":0.9379956,"about_ca_system_score_codex":0.00005493119,"about_ca_system_score_gemma":0.00012035557,"threshold_uncertainty_score":0.8486469},"labels":[],"label_agreement":null},{"id":"W3171315464","doi":"10.2139/ssrn.3369078","title":"An Ordinal Theory of Worst- and Best-Case Expected Utility","year":2019,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Ordinal data; Econometrics; Ordinal optimization; Statistics; Ordinal regression; Mathematical economics; Mathematics; Psychology; Computer science","score_opus":0.06428426999270867,"score_gpt":0.3724670102434361,"score_spread":0.30818274025072745,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3171315464","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.995077,0.00067160814,0.0029887913,0.00006354397,0.00028666755,0.00009558165,0.000006292535,0.000013061425,0.0007974465],"genre_scores_gemma":[0.9988971,0.00014016572,0.00022229072,0.000023723587,0.00007366577,9.26766e-7,6.45922e-7,0.000012792437,0.0006287253],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9969615,0.00037234055,0.0007283402,0.0004112528,0.000519475,0.001007093],"domain_scores_gemma":[0.9979501,0.0006170365,0.0004238266,0.0005755783,0.00027425718,0.00015924098],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00951249,0.00015618041,0.00037254798,0.00028010673,0.00017094899,0.00020692147,0.00059553795,0.000100607685,0.00066965574],"category_scores_gemma":[0.0005397802,0.00011164369,0.0001359434,0.000330585,0.000121146666,0.0005552281,0.0000823318,0.00095739093,0.00012333623],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028175133,0.00020576025,0.031028802,0.0000010017382,0.000026025806,0.00004360124,0.00029588904,0.000018976707,0.00043547378,0.015735205,0.000030486124,0.951897],"study_design_scores_gemma":[0.0005950863,0.0010091399,0.0023374818,0.000014129638,0.00002915457,0.005470658,0.014114588,0.0005075911,0.0000935655,0.9752339,0.00042768195,0.00016702308],"about_ca_topic_score_codex":0.000043894073,"about_ca_topic_score_gemma":0.0003160322,"teacher_disagreement_score":0.9594987,"about_ca_system_score_codex":0.00015702663,"about_ca_system_score_gemma":0.00083772204,"threshold_uncertainty_score":0.73322606},"labels":[],"label_agreement":null},{"id":"W3171846995","doi":"10.5430/ijfr.v12n4p259","title":"The Impact of Corporate Performance on Mental Accounting and Loss Aversion in Financial Decisions","year":2021,"lang":"en","type":"article","venue":"International Journal of Financial Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Mental accounting; Loss aversion; Accounting; Business; Real estate; Affect (linguistics); Financial accounting; Finance; Actuarial science; Accounting information system; Economics; Psychology","score_opus":0.275625826064391,"score_gpt":0.5087273663348035,"score_spread":0.23310154027041252,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3171846995","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9978992,0.00011941015,0.000037720893,0.0006265813,0.0008862168,0.000054508975,0.000029209743,9.428544e-7,0.0003462401],"genre_scores_gemma":[0.9988591,0.0006569356,0.00012505362,0.000025328658,0.00019185289,9.1231516e-7,0.000001311175,0.0000051992447,0.000134328],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9960958,0.00021272313,0.0009413899,0.00020884746,0.0023010706,0.00024017326],"domain_scores_gemma":[0.9927532,0.0034209331,0.00062963576,0.00020512522,0.0029040105,0.00008709182],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0077555487,0.000090671274,0.00024235234,0.00066260755,0.00023399745,0.00033892287,0.0010283857,0.00007802693,0.00008399848],"category_scores_gemma":[0.020440185,0.00005567997,0.00017464832,0.0006671049,0.00022679391,0.00043201225,0.0003696332,0.00057683635,0.000032732103],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009945483,0.00014800743,0.12942222,4.998e-7,0.000006968179,0.0002359462,0.00021743098,0.00054025516,0.00082911935,0.0004637649,0.0029262877,0.86421496],"study_design_scores_gemma":[0.00093804084,0.00049602985,0.95996344,0.0002936588,0.0000018910075,0.0001792689,0.00013986426,0.001448874,0.0014901403,0.03102877,0.0039366228,0.00008337969],"about_ca_topic_score_codex":0.00005158939,"about_ca_topic_score_gemma":0.000105454936,"teacher_disagreement_score":0.86413157,"about_ca_system_score_codex":0.00029092145,"about_ca_system_score_gemma":0.0013196676,"threshold_uncertainty_score":0.9878111},"labels":[],"label_agreement":null},{"id":"W3171916869","doi":"10.1016/j.jet.2023.105645","title":"A central limit theorem, loss aversion and multi-armed bandits","year":2023,"lang":"en","type":"article","venue":"Journal of Economic Theory","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"National Key Research and Development Program of China; Natural Science Foundation of Shandong Province","keywords":"Limit (mathematics); Central limit theorem; Risk aversion (psychology); Mathematical economics; Domain (mathematical analysis); Mathematics; Focus (optics); Decision maker; Loss aversion; Interval (graph theory); Economics; Set (abstract data type); Econometrics; Mathematical optimization; Applied mathematics; Computer science; Expected utility hypothesis; Mathematical analysis; Combinatorics; Statistics; Microeconomics","score_opus":0.12073289912750154,"score_gpt":0.3876364178873946,"score_spread":0.26690351875989304,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3171916869","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9955804,0.00012991359,0.0007650423,0.00048571517,0.0022245073,0.00007029304,0.000023604553,0.000020244517,0.0007002886],"genre_scores_gemma":[0.9976978,0.00021586541,0.0004444366,0.00014163276,0.00028243707,6.3968906e-7,0.0000010220195,0.000017295575,0.0011988998],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9978392,0.00024051411,0.001054059,0.00030040854,0.00024041565,0.00032536255],"domain_scores_gemma":[0.99605227,0.0024369473,0.00081844634,0.0003347066,0.00009673515,0.00026089558],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.006480761,0.00015976178,0.00046706293,0.00056055264,0.0001451437,0.00028735754,0.0006936189,0.00010967795,0.0008121],"category_scores_gemma":[0.0011828087,0.000114238734,0.0002637748,0.0001564782,0.0001899152,0.00056825695,0.00019869398,0.00024026058,0.0008569017],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009413908,0.00016446353,0.037726328,0.00000597032,0.000109848435,0.00036205596,0.0029041597,0.004712169,0.0004982035,0.015849832,0.024334975,0.9123906],"study_design_scores_gemma":[0.0032257664,0.00031488886,0.0557832,0.00009990153,0.00007656351,0.0005991227,0.0054314705,0.008103873,0.0005145329,0.8951409,0.030257637,0.00045218674],"about_ca_topic_score_codex":0.0000031691463,"about_ca_topic_score_gemma":0.000009720698,"teacher_disagreement_score":0.9119384,"about_ca_system_score_codex":0.00013913572,"about_ca_system_score_gemma":0.00013780314,"threshold_uncertainty_score":0.999921},"labels":[],"label_agreement":null},{"id":"W3173220302","doi":"10.5642/cguetd/222","title":"Essays in Behavioral, Health and Financial Economics","year":2021,"lang":"en","type":"dissertation","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Respondent; Behavioral Risk Factor Surveillance System; Feeling; Life satisfaction; Psychology; Stock (firearms); Behavioral economics; Social psychology; Unemployment; Matching (statistics); Stock market; Health and Retirement Study; Gerontology; Actuarial science; Economics; Public health; Medicine; Finance; Political science; Geography","score_opus":0.12109112276881964,"score_gpt":0.43674413513822313,"score_spread":0.31565301236940346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3173220302","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.985687,0.00084199716,0.000013610029,0.00021812897,0.0019565276,0.0001936171,0.000054109034,0.000021554395,0.011013445],"genre_scores_gemma":[0.95210814,0.0022364147,0.0028516317,0.0014130126,0.00025186196,0.00008491717,0.00093652133,0.00008904761,0.040028438],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99663734,0.000111376474,0.0015088125,0.0010559603,0.00033938725,0.0003471358],"domain_scores_gemma":[0.99799657,0.00035895774,0.0005910289,0.0006428168,0.00016450988,0.00024613197],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0015503779,0.00030676293,0.0009449445,0.00063935696,0.00013805753,0.0006752367,0.0005489685,0.00042389077,0.00088854274],"category_scores_gemma":[0.00049265136,0.00027562573,0.00016625102,0.00038976473,0.000039163806,0.0002897605,0.000106029016,0.0004185852,0.00015166725],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004278536,0.00014353123,0.0022847003,0.000007985347,0.0000014654175,0.000022219603,0.0014595567,0.000015544825,0.0000024806168,0.0012518552,0.008593751,0.9861741],"study_design_scores_gemma":[0.0031031945,0.0011541707,0.047060095,0.0009238895,0.000069387206,0.00009426457,0.084746726,0.0010458562,0.00022757785,0.48192734,0.37615967,0.0034878245],"about_ca_topic_score_codex":0.00079434743,"about_ca_topic_score_gemma":0.03603836,"teacher_disagreement_score":0.9826863,"about_ca_system_score_codex":0.00016809182,"about_ca_system_score_gemma":0.0013416274,"threshold_uncertainty_score":0.9999696},"labels":[],"label_agreement":null},{"id":"W3174533914","doi":"10.1093/jcr/ucac024","title":"The Influence of Budgets on Consumer Spending","year":2022,"lang":"en","type":"article","venue":"Journal of Consumer Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Psychographic; Compliance (psychology); Economics; Consumer behaviour; Consumer spending; Consumer expenditure; Behavioral economics; Marketing; Public economics; Business; Finance; Psychology; Aggregate expenditure; Social psychology; Macroeconomics","score_opus":0.3370500657519823,"score_gpt":0.524397804116713,"score_spread":0.18734773836473068,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3174533914","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9958765,0.0007500919,0.0000071495942,0.0010736276,0.00054659427,0.00012041934,0.0000139873,0.0000028497439,0.0016088069],"genre_scores_gemma":[0.99883485,0.00020301592,0.00009771315,0.000056462024,0.00003806429,0.000004451103,1.3350771e-7,0.000010558283,0.0007547269],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99259156,0.0012260742,0.0013458207,0.0002353598,0.004215302,0.00038591103],"domain_scores_gemma":[0.9836744,0.013171932,0.0008575304,0.0006881189,0.001436342,0.00017169806],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.027355,0.00010004965,0.00035819542,0.0008771997,0.00095261936,0.00032906802,0.0022989076,0.000038903203,0.00075988524],"category_scores_gemma":[0.009456407,0.000058964237,0.00020728528,0.0009939156,0.0005475231,0.00024812698,0.000626137,0.001261185,0.00024457675],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010824483,0.00033381165,0.08204628,0.0000037707134,0.00007983513,0.00027504357,0.00063441193,0.004256989,0.0036705027,0.0022708266,0.05199158,0.8533545],"study_design_scores_gemma":[0.0011770161,0.0013150746,0.06496675,0.000093129536,0.000024125959,0.00048397324,0.004485101,0.00021737348,0.0016895841,0.09280616,0.83251876,0.00022295085],"about_ca_topic_score_codex":0.00002577778,"about_ca_topic_score_gemma":0.0000116271285,"teacher_disagreement_score":0.85313153,"about_ca_system_score_codex":0.00015285493,"about_ca_system_score_gemma":0.00046023622,"threshold_uncertainty_score":0.99888736},"labels":[],"label_agreement":null},{"id":"W3178845484","doi":"10.31234/osf.io/yn5r2","title":"Risky Choice and Memory for Effort: Hard Work Stands Out","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Preference; Actuarial science; Action (physics); Work (physics); Computer science; Psychology; Economics; Microeconomics; Engineering","score_opus":0.22471795304849454,"score_gpt":0.42998179886202775,"score_spread":0.2052638458135332,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3178845484","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96789354,0.0007033553,0.018422667,0.0006671462,0.00403381,0.00058407924,0.00014557921,0.00009228269,0.007457522],"genre_scores_gemma":[0.9148957,0.00015931299,0.03773395,0.00067834737,0.0006381684,0.00013610248,0.000054952816,0.00006840943,0.045635026],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99586165,0.000075404874,0.0012130165,0.0016065958,0.00085467333,0.00038866006],"domain_scores_gemma":[0.9945843,0.0027410495,0.0005487374,0.0013708608,0.00049601664,0.00025899723],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003407791,0.00039434264,0.0009871521,0.00030426815,0.00021452522,0.0023759787,0.0011874589,0.000517349,0.0011678473],"category_scores_gemma":[0.0027901293,0.00029575545,0.00046018878,0.00021888725,0.00012366415,0.0002342281,0.0018013365,0.0005211788,0.00016081781],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000588607,0.000080096586,0.01905306,0.000020627198,0.000041959054,0.000011310806,0.00051162235,0.00043830086,0.000014505119,0.000056002118,0.055102475,0.92461115],"study_design_scores_gemma":[0.0032460608,0.00033328647,0.13026775,0.0009250642,0.00049595896,0.000028030914,0.0056905835,0.0050964477,0.00097393105,0.25204203,0.5975689,0.003331918],"about_ca_topic_score_codex":0.00006542047,"about_ca_topic_score_gemma":0.00036540793,"teacher_disagreement_score":0.92127925,"about_ca_system_score_codex":0.00009500677,"about_ca_system_score_gemma":0.00023438962,"threshold_uncertainty_score":0.99994946},"labels":[],"label_agreement":null},{"id":"W3183017283","doi":"10.2139/ssrn.3873427","title":"Simultaneous Learning of Perceptual Ambiguity and Expected Value Estimates Alter Preferences, Discrimination Performance, and Choice","year":2021,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Ambiguity; Perception; Cognitive psychology; Value (mathematics); Psychology; Statistics; Econometrics; Artificial intelligence; Mathematics; Computer science; Neuroscience","score_opus":0.04533264389809971,"score_gpt":0.3439252199320242,"score_spread":0.2985925760339245,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3183017283","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99622124,0.00091865007,0.0022678166,0.000096079726,0.00012259147,0.000045600224,0.0000023776602,0.000013417364,0.00031220962],"genre_scores_gemma":[0.99714226,0.001607482,0.00059908064,0.000016052063,0.00006183007,0.0000011887513,0.0000035537646,0.000010349974,0.00055821665],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9977625,0.00016027922,0.0005473866,0.0003476967,0.0004973848,0.00068475],"domain_scores_gemma":[0.99801165,0.0010554173,0.0003191995,0.0001653179,0.00035767935,0.00009074837],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019523383,0.00014383812,0.00029892923,0.00016615543,0.0003104879,0.00028996298,0.00023495476,0.000079597805,0.000080071324],"category_scores_gemma":[0.0027888762,0.000108872984,0.00005815016,0.00023372118,0.00012646074,0.00043821585,0.00012658135,0.00087162113,0.000008512923],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040531097,0.00006073008,0.052602172,0.000004874857,0.000022393564,0.0000052493187,0.00091403973,0.0013889949,0.0015516029,0.00087176356,0.000015914095,0.94252175],"study_design_scores_gemma":[0.0025485165,0.0024913426,0.18458496,0.000272557,0.00025768141,0.003638114,0.039608873,0.17444599,0.0025548085,0.58686256,0.0017700704,0.0009645051],"about_ca_topic_score_codex":0.000046396206,"about_ca_topic_score_gemma":0.00029915816,"teacher_disagreement_score":0.9415572,"about_ca_system_score_codex":0.00014315445,"about_ca_system_score_gemma":0.00055172265,"threshold_uncertainty_score":0.44397116},"labels":[],"label_agreement":null},{"id":"W3186286161","doi":"","title":"Making Progress on the Effort Paradox: Progress Information Moderates Cognitive Demand Avoidance","year":2021,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Army Research Office; Natural Sciences and Engineering Research Council of Canada","keywords":"Cognition; Psychology; Cognitive psychology; Stimulus (psychology); Task (project management); Information processing; Social psychology; Economics; Neuroscience","score_opus":0.07587271996073992,"score_gpt":0.32921525826423753,"score_spread":0.2533425383034976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3186286161","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.982752,0.00035632902,0.00051381794,0.0026968548,0.00029901238,0.0004993817,0.0014755337,0.00020948352,0.011197562],"genre_scores_gemma":[0.99660826,0.000008779448,0.000549846,0.0019776865,0.00010942722,0.00008871464,0.00027367615,0.00004127431,0.0003423522],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99607366,0.0002134409,0.001149853,0.00069029815,0.001320722,0.0005520417],"domain_scores_gemma":[0.9963936,0.0017214069,0.0005449468,0.00076825015,0.00035753415,0.00021423404],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001135985,0.00039140665,0.0004378319,0.00023938334,0.000572572,0.01262168,0.0010865829,0.00019206836,0.00056418404],"category_scores_gemma":[0.0025481347,0.00025043142,0.00027711358,0.0010487485,0.00033317544,0.009422024,0.00054088945,0.0006156359,0.0065537393],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004102303,0.0003375625,0.279375,0.000014634987,0.00004620321,0.00012155534,0.00018820538,0.000100738,0.0000030871631,0.0041374853,0.004612132,0.7106532],"study_design_scores_gemma":[0.0022053695,0.0005044943,0.06618211,0.0016190188,0.000089911206,0.00022663029,0.002212137,0.008576721,0.009924763,0.5540805,0.35226876,0.0021095797],"about_ca_topic_score_codex":1.9339703e-7,"about_ca_topic_score_gemma":8.0285696e-7,"teacher_disagreement_score":0.7085436,"about_ca_system_score_codex":0.000039518793,"about_ca_system_score_gemma":0.00022796413,"threshold_uncertainty_score":0.9999948},"labels":[],"label_agreement":null},{"id":"W3186295407","doi":"10.1016/j.jesp.2021.104154","title":"Retrospective and prospective hindsight bias: Replications and extensions of Fischhoff (1975) and Slovic and Fischhoff (1977)","year":2021,"lang":"en","type":"article","venue":"Journal of Experimental Social Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Hindsight bias; Psychology; Replication (statistics); Debiasing; Social psychology; Cognitive psychology; Statistics; Mathematics","score_opus":0.14643696357332456,"score_gpt":0.4601383078492517,"score_spread":0.3137013442759271,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3186295407","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9916225,0.0035026635,0.000070753435,0.0026265257,0.00037087625,0.00011739066,0.000026629674,0.0000055619107,0.0016570713],"genre_scores_gemma":[0.9974149,0.0003016428,0.0016391056,0.0003273872,0.00013169833,0.000004096581,9.061725e-7,0.000012082218,0.00016818153],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99794376,0.00018658311,0.0008437014,0.00051782216,0.00033595337,0.00017219257],"domain_scores_gemma":[0.99806374,0.0003766252,0.0007469482,0.00023828025,0.00041103864,0.00016335442],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009178608,0.00016152274,0.0006057155,0.00021690244,0.000308418,0.00014005108,0.0001596437,0.00016548535,0.00011813401],"category_scores_gemma":[0.0007687169,0.00012976878,0.0000981965,0.00029468,0.0006190771,0.000336407,0.00021183383,0.0002835046,0.0000028388981],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001052555,0.0018651125,0.4523046,0.000010357808,0.00030331354,0.00026697505,0.021473218,0.0000011678602,0.35494632,0.008682917,0.027415147,0.13167833],"study_design_scores_gemma":[0.0020490566,0.0008714893,0.9078916,0.0000383647,0.00006050507,0.0013111167,0.0081103025,0.000019271394,0.004857184,0.070709504,0.003848779,0.00023282287],"about_ca_topic_score_codex":0.000011367294,"about_ca_topic_score_gemma":0.000015575055,"teacher_disagreement_score":0.455587,"about_ca_system_score_codex":0.000045876026,"about_ca_system_score_gemma":0.000058107253,"threshold_uncertainty_score":0.5291818},"labels":[],"label_agreement":null},{"id":"W3186408120","doi":"","title":"A Unified, Resource-Rational Account of the Allais and Ellsberg Paradoxes","year":2021,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Rationality; Mathematical economics; Expected utility hypothesis; Economics; Decision theory; Microeconomics; Epistemology; Philosophy","score_opus":0.05044557053754595,"score_gpt":0.2872208121346794,"score_spread":0.23677524159713348,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3186408120","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97901225,0.0002711927,0.00003253086,0.0024152563,0.00017331935,0.00011212655,0.0013673154,0.000042408592,0.016573614],"genre_scores_gemma":[0.99620163,0.00001089317,0.00039143735,0.0006724997,0.00007779309,0.0000044658996,0.00006682072,0.000027044181,0.0025474154],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9971451,0.0001821981,0.000861519,0.0005868098,0.00096628873,0.00025809143],"domain_scores_gemma":[0.9971012,0.0014281352,0.0003227188,0.0008374795,0.00013083147,0.00017962992],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00073334156,0.00021779962,0.00036010504,0.00013614062,0.00020503694,0.0025987448,0.000945081,0.00012071068,0.00084451836],"category_scores_gemma":[0.0023924387,0.00013748513,0.00024451083,0.00080793386,0.0002359239,0.002245328,0.0008076522,0.00030533897,0.00072404084],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018302946,0.00021042603,0.74478996,0.000010861435,0.000033778484,0.000043770553,0.00008547693,0.000086920576,0.00034224047,0.0048301476,0.019041454,0.23034191],"study_design_scores_gemma":[0.00047833237,0.000051601575,0.03297582,0.00006525726,0.000019301084,0.00006342668,0.00020768674,0.00015925588,0.0047027236,0.20117866,0.75980914,0.0002888189],"about_ca_topic_score_codex":0.0000029109485,"about_ca_topic_score_gemma":0.000006638818,"teacher_disagreement_score":0.74076766,"about_ca_system_score_codex":0.000017230002,"about_ca_system_score_gemma":0.0002264029,"threshold_uncertainty_score":0.9984366},"labels":[],"label_agreement":null},{"id":"W3186539350","doi":"10.18559/ebr.2021.2.2","title":"Escalation of commitment is independent of numeracy and cognitive reflection. Failed replication and extension of Staw (1976)","year":2021,"lang":"en","type":"article","venue":"Economics and Business Review/˜The œPoznań University of Economics Review","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Escalation of commitment; Psychology; Cognition; Numeracy; Social psychology; Test (biology); Replicate; Reflection (computer programming); Pedagogy","score_opus":0.10819323199258794,"score_gpt":0.34520719616570056,"score_spread":0.2370139641731126,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3186539350","genre_codex":"empirical","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.88178635,0.11465423,0.00025182538,0.002098901,0.00009184946,0.00059855264,0.00014210126,0.0000029479288,0.0003732285],"genre_scores_gemma":[0.35049328,0.64857596,0.00055221515,0.00027824152,0.0000072928856,0.0000010448579,0.00002045405,0.0000070911096,0.000064412336],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99774456,0.00016065317,0.0013010782,0.00059700175,0.00009129267,0.000105440515],"domain_scores_gemma":[0.99543,0.00057379634,0.0022066003,0.00076076307,0.00095949945,0.00006935913],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022343313,0.00017624506,0.0011986524,0.00013791119,0.000113935464,0.000031177053,0.00026572315,0.00008488606,0.00013191487],"category_scores_gemma":[0.0004287396,0.00015435476,0.00016474533,0.00029137806,0.00029675904,0.00038578114,0.00034126773,0.000091747155,0.0000044050416],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007365934,0.0001435958,0.0049542487,0.0021257156,0.0000994324,0.0000010574606,0.00021595124,0.00005897376,0.00006825013,0.0012825159,0.00065781706,0.9903188],"study_design_scores_gemma":[0.00650253,0.00075426465,0.25760192,0.050450306,0.0044547096,0.0002898031,0.004556277,0.012246031,0.0022697544,0.064956255,0.59379447,0.0021236883],"about_ca_topic_score_codex":0.000112813555,"about_ca_topic_score_gemma":0.00013776789,"teacher_disagreement_score":0.9881951,"about_ca_system_score_codex":0.000044722907,"about_ca_system_score_gemma":0.00013793538,"threshold_uncertainty_score":0.6294404},"labels":[],"label_agreement":null},{"id":"W3187466351","doi":"10.7554/elife.67387.sa2","title":"Author response: The role of ventromedial prefrontal cortex in reward valuation and future thinking during intertemporal choice","year":2021,"lang":"en","type":"peer-review","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; York University","funders":"","keywords":"Ventromedial prefrontal cortex; Prefrontal cortex; Neuroscience; Valuation (finance); Consumer neuroscience; Psychology; Cognitive psychology; Cognition; Economics","score_opus":0.10142801138577899,"score_gpt":0.41507450618347214,"score_spread":0.31364649479769313,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3187466351","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9257644,0.025407607,0.000021273028,0.04153627,0.0053921905,0.00089168013,0.00013880742,0.000029357261,0.00081845606],"genre_scores_gemma":[0.852274,0.0024588443,0.0021623345,0.0016849877,0.003425963,0.00021236949,0.0004058896,0.0001378051,0.1372378],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99445176,0.00096980337,0.0017098108,0.00086347637,0.0017236146,0.00028155645],"domain_scores_gemma":[0.9953425,0.0021083003,0.0010101894,0.00096982054,0.00047012515,0.00009905126],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0077778213,0.00032295694,0.0010234752,0.00040265458,0.00014311059,0.00040706404,0.0011678466,0.00036812847,0.0013674323],"category_scores_gemma":[0.00392104,0.00020139896,0.00028833587,0.0005726928,0.00011833881,0.00031972193,0.0006658986,0.0007168744,0.00004364884],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041332582,0.00015364509,0.0039335727,0.00017778174,0.000048764163,0.000040531988,0.0023483306,0.000008637213,0.00087369635,0.000042795273,0.124049954,0.86790895],"study_design_scores_gemma":[0.0005015905,0.000111072986,0.27502012,0.0023088984,0.0001038333,0.000056994384,0.0026832416,0.00029273191,0.000038018323,0.017047068,0.70145607,0.00038036003],"about_ca_topic_score_codex":0.00036575316,"about_ca_topic_score_gemma":0.001533951,"teacher_disagreement_score":0.8675286,"about_ca_system_score_codex":0.00017301229,"about_ca_system_score_gemma":0.0004090283,"threshold_uncertainty_score":0.99954545},"labels":[],"label_agreement":null},{"id":"W3187642658","doi":"","title":"Unclaimed Prize Information Biases Perceptions of Winning in Scratch Card Gambling","year":2018,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Scratch; Context (archaeology); Psychology; Perception; Advertising; Equating; Social psychology; Computer science; Business; Developmental psychology","score_opus":0.09505840821841158,"score_gpt":0.40094134935706,"score_spread":0.30588294113864845,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3187642658","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9844385,0.00009883231,0.013629096,0.00031502955,0.0003641176,0.000080404,0.0000038201742,0.000014384268,0.001055811],"genre_scores_gemma":[0.99871534,0.00015275275,0.00073434145,0.000090210684,0.00017241987,0.0000019257093,0.000002231728,0.000008007107,0.0001227695],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99687433,0.00012900638,0.0011157502,0.00018375173,0.00069177,0.0010053645],"domain_scores_gemma":[0.99815845,0.00039865565,0.00053540384,0.00029542626,0.00053578627,0.00007629444],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006991524,0.00012535519,0.00029317933,0.0008141007,0.00024131722,0.00031982362,0.0005894165,0.000094071285,0.0001607312],"category_scores_gemma":[0.001880754,0.0000987368,0.00014396838,0.00085529743,0.00012456752,0.001673444,0.00008116294,0.0008430071,0.0002744294],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009438924,0.000062248546,0.030605515,0.000001056588,0.000017432147,0.000001426675,0.0019960885,0.0010360221,0.0010062997,0.0025308095,0.0004480324,0.9622007],"study_design_scores_gemma":[0.0012048124,0.00074230105,0.0169442,0.00014724856,0.000030789506,0.00020906974,0.04258116,0.0039789304,0.0003633612,0.9305075,0.002962448,0.00032819103],"about_ca_topic_score_codex":0.00012263175,"about_ca_topic_score_gemma":0.0013131209,"teacher_disagreement_score":0.96187246,"about_ca_system_score_codex":0.00053740543,"about_ca_system_score_gemma":0.0018327908,"threshold_uncertainty_score":0.40263698},"labels":[],"label_agreement":null},{"id":"W3193439024","doi":"10.31234/osf.io/h8prg","title":"Efficient Coding and Risky Choice","year":2020,"lang":"en","type":"article","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Semtech (Canada)","funders":"","keywords":"Stochastic game; Lottery; Coding (social sciences); Perception; Mathematical economics; Decision maker; Economics; Regular polygon; Computer science; Econometrics; Microeconomics; Mathematics; Psychology; Operations research; Statistics","score_opus":0.22266381831301854,"score_gpt":0.4113413905840159,"score_spread":0.18867757227099738,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3193439024","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98067015,0.000035651516,0.004209586,0.0030458139,0.00018793921,0.00005640641,0.0000045198453,0.00004879232,0.011741108],"genre_scores_gemma":[0.99672085,0.0000030604383,0.0014284973,0.001349477,0.00006870436,9.807441e-7,2.2228214e-7,0.000005019234,0.00042316617],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99873334,0.000032296197,0.00033920314,0.0003934074,0.00036706484,0.00013468965],"domain_scores_gemma":[0.99850863,0.0009390754,0.000085381944,0.00021303094,0.00006609446,0.00018776364],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006885697,0.000078598336,0.0001727431,0.00006219706,0.00010922869,0.00033248702,0.00031703644,0.00003804598,0.0007873655],"category_scores_gemma":[0.0020119522,0.000053010222,0.000049147297,0.00027778457,0.000048220998,0.00006243364,0.00019107472,0.00008153929,0.0011229992],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001910677,0.000035929843,0.020449676,0.0000013103505,0.0000033102403,0.000010027728,0.000563577,0.0017135325,0.00065172656,0.0013728242,0.020153686,0.9550253],"study_design_scores_gemma":[0.0012992611,0.00029274388,0.05438554,0.000023085648,0.000031414787,0.00002399989,0.0027757308,0.5120782,0.0010866928,0.020550244,0.40674615,0.000706914],"about_ca_topic_score_codex":0.000021424921,"about_ca_topic_score_gemma":0.000008964807,"teacher_disagreement_score":0.9543184,"about_ca_system_score_codex":0.000010086787,"about_ca_system_score_gemma":0.00001599371,"threshold_uncertainty_score":0.99965477},"labels":[],"label_agreement":null},{"id":"W3195157048","doi":"10.1016/j.insmatheco.2021.08.004","title":"Optimal reinsurance under the α-maxmin mean-variance criterion","year":2021,"lang":"en","type":"article","venue":"Insurance Mathematics and Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"China Scholarship Council; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Ambiguity; Reinsurance; Minimax; Variance (accounting); Preference; Ambiguity aversion; Expected utility hypothesis; Mathematical economics; Economics; Econometrics; Range (aeronautics); Mathematics; Microeconomics; Actuarial science; Computer science","score_opus":0.09917736626442714,"score_gpt":0.34546154272203133,"score_spread":0.2462841764576042,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3195157048","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98707944,0.00054954673,0.0067653335,0.0019461785,0.0007854502,0.00012920026,0.00007222956,0.000029265708,0.0026433598],"genre_scores_gemma":[0.9788387,0.0005869442,0.01875724,0.00074521895,0.00012630146,0.000015533426,0.0000033523568,0.000028838276,0.00089787046],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9976628,0.00006353729,0.0010457708,0.0006475645,0.00025164822,0.0003287122],"domain_scores_gemma":[0.996736,0.001323188,0.00043754882,0.0011438451,0.00024189301,0.00011756245],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001863928,0.0002437292,0.00053879194,0.00007593403,0.00036980596,0.0011009801,0.00069768546,0.00012415119,0.00018500262],"category_scores_gemma":[0.00051334884,0.00017307153,0.00016241349,0.0002532354,0.00021122838,0.00044150683,0.00027013768,0.00021783388,0.00030811512],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015963516,0.000738178,0.0067137214,0.0000834287,0.00014480771,0.0001091558,0.0075737294,0.04974636,0.0016496463,0.13044374,0.0050231707,0.79761446],"study_design_scores_gemma":[0.0012877098,0.000096914286,0.021452831,0.0001927022,0.000047914873,0.00065164734,0.00838924,0.09686266,0.002218928,0.80854446,0.059151143,0.0011038797],"about_ca_topic_score_codex":0.000010968147,"about_ca_topic_score_gemma":0.00008895043,"teacher_disagreement_score":0.7965106,"about_ca_system_score_codex":0.00005392228,"about_ca_system_score_gemma":0.00010198341,"threshold_uncertainty_score":0.999936},"labels":[],"label_agreement":null},{"id":"W3195225210","doi":"10.22215/etd/2014-10349","title":"Individual Differences Influence the Degree of Source Expertise Bias in Syllogistic Reasoning","year":2014,"lang":"en","type":"dissertation","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Syllogism; Psychology; Debiasing; Reflection (computer programming); Cognitive psychology; Social psychology; Computer science; Epistemology","score_opus":0.3110407190417193,"score_gpt":0.4111068290434165,"score_spread":0.10006611000169718,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3195225210","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9921328,0.0002313936,0.00036226297,0.000045103516,0.0005895383,0.00020661643,0.000014867756,0.00002744247,0.0063900095],"genre_scores_gemma":[0.9951009,0.000026404106,0.00038586644,0.000096302836,0.00004610113,0.00002986382,0.000028185905,0.000021145719,0.0042652246],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9954563,0.00035500366,0.0016525267,0.000736701,0.001475272,0.0003242116],"domain_scores_gemma":[0.9926807,0.0046436465,0.0012465676,0.0010095708,0.00033098026,0.00008850755],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.00362838,0.00033855764,0.00082209636,0.0005847639,0.000155654,0.00050272344,0.0025609755,0.00036586446,0.00035535215],"category_scores_gemma":[0.012776245,0.00018539894,0.00021088026,0.00066577544,0.0002029845,0.00020748838,0.00017244135,0.0004597903,0.00017080235],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007212662,0.00006837324,0.094908446,0.000009369009,0.00001203374,0.0000050832464,0.0037208928,0.0005141468,0.000043515058,0.000488321,0.00072082644,0.8994369],"study_design_scores_gemma":[0.0003824883,0.00017113154,0.9502688,0.00067749555,0.00006967281,0.000007845454,0.015202598,0.0023932776,0.00026370992,0.028504292,0.0014554431,0.00060325937],"about_ca_topic_score_codex":0.0012845543,"about_ca_topic_score_gemma":0.006033089,"teacher_disagreement_score":0.89883363,"about_ca_system_score_codex":0.00004522832,"about_ca_system_score_gemma":0.0001890911,"threshold_uncertainty_score":0.99553955},"labels":[],"label_agreement":null},{"id":"W3195747619","doi":"10.1016/j.cognition.2021.104866","title":"Reasoning strategy vs cognitive capacity as predictors of individual differences in reasoning performance","year":2021,"lang":"en","type":"article","venue":"Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":28,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal; University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Psychology; Cognition; Cognitive psychology; Probabilistic logic; Cognitive strategy; Verbal reasoning; Inference; Task (project management); Bayesian inference; Neglect; Bayesian probability; Artificial intelligence; Computer science","score_opus":0.14444953941990485,"score_gpt":0.35540569572792713,"score_spread":0.21095615630802228,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3195747619","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98964494,0.0000725997,0.00014451378,0.000022543196,0.00028629642,0.00011620622,0.00010920339,0.000025289513,0.009578429],"genre_scores_gemma":[0.99938744,0.000046394805,0.00027161927,0.0000591082,0.000055446028,0.000013635098,0.000055940356,0.000009755764,0.00010063121],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9973783,0.0002385965,0.0007402624,0.0005204752,0.00086677924,0.00025560101],"domain_scores_gemma":[0.99761844,0.0010581263,0.00039414744,0.00022086616,0.00061419717,0.000094209005],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016079185,0.00016174634,0.00039610275,0.000286412,0.00013273447,0.00025815083,0.0003154733,0.00014360802,0.00049175957],"category_scores_gemma":[0.0042459304,0.00014296774,0.00009084117,0.00074794417,0.00017231815,0.0006216886,0.0001351296,0.00027448853,0.00012799219],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016357722,0.0002484459,0.56954175,0.0000120234345,0.000026547394,0.000043847587,0.0016377186,0.00004795659,0.00039047934,0.0001834525,0.00009032678,0.42761388],"study_design_scores_gemma":[0.000889048,0.0003281671,0.95806164,0.00085604686,0.00006903438,0.00005548238,0.006903213,0.0012833407,0.0145797925,0.016652742,0.000046198595,0.0002753146],"about_ca_topic_score_codex":0.00002347877,"about_ca_topic_score_gemma":0.00009704149,"teacher_disagreement_score":0.42733857,"about_ca_system_score_codex":0.000035415553,"about_ca_system_score_gemma":0.00021156718,"threshold_uncertainty_score":0.58300555},"labels":[],"label_agreement":null},{"id":"W3196651021","doi":"10.5167/uzh-205562","title":"Evaluating deliberative competence: a simple method with an application to financial choice","year":2021,"lang":"en","type":"article","venue":"Zurich Open Repository and Archive (University of Zurich)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of Toronto; Alfred P. Sloan Foundation","keywords":"Statistic; Competence (human resources); Scope (computer science); Quality (philosophy); Psychological intervention; Actuarial science; Computer science; Simple (philosophy); Risk analysis (engineering); Management science; Psychology; Economics; Business; Mathematics; Social psychology; Statistics","score_opus":0.10856754775166595,"score_gpt":0.41931267990820664,"score_spread":0.3107451321565407,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3196651021","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7722153,0.000016359088,0.22430578,0.00020064387,0.000050172246,0.00029863114,0.000035798264,0.000014361608,0.0028629545],"genre_scores_gemma":[0.59154236,0.0000034895188,0.40731,0.00020794562,0.000045547276,0.000002425106,0.00001942296,0.000009460125,0.00085932406],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99713147,0.001046075,0.00030731678,0.00082773564,0.0004947621,0.00019262942],"domain_scores_gemma":[0.9961033,0.002175576,0.00034462436,0.0006079588,0.0005348464,0.0002337254],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022706178,0.00015055828,0.00040636933,0.00015593476,0.0008525178,0.00031183707,0.0009757377,0.000057307156,0.000065920445],"category_scores_gemma":[0.00045539162,0.00014092244,0.000064053864,0.0006297804,0.0001219953,0.000792583,0.00082851795,0.00015942272,0.00002257526],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012428602,0.00058179506,0.019587027,0.000015105799,0.00005842704,0.0002254259,0.011762507,0.0054206946,0.035265435,0.0027088067,0.004532407,0.9185995],"study_design_scores_gemma":[0.0059056506,0.0069761444,0.48153427,0.0003192115,0.000495426,0.0006104751,0.04889057,0.118482105,0.008604483,0.21752082,0.10837194,0.0022888859],"about_ca_topic_score_codex":0.00068849715,"about_ca_topic_score_gemma":0.0011676255,"teacher_disagreement_score":0.9163106,"about_ca_system_score_codex":0.00003479475,"about_ca_system_score_gemma":0.0003087049,"threshold_uncertainty_score":0.6556964},"labels":[],"label_agreement":null},{"id":"W3197565229","doi":"10.1167/jov.21.9.2920","title":"Decreases loom larger than increases: A perceptual account for loss aversion","year":2021,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Numerosity adaptation effect; Perception; Psychology; Asymmetry; Loss aversion; Audiology; Contrast (vision); Mathematics; Cognitive psychology; Computer science; Medicine; Physics; Economics; Artificial intelligence; Microeconomics; Neuroscience","score_opus":0.08370552187857169,"score_gpt":0.4099889928868475,"score_spread":0.3262834710082758,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3197565229","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99398255,0.00039716627,0.0035612425,0.00068857934,0.0010353897,0.000090011774,0.00004160396,0.000009983878,0.00019348852],"genre_scores_gemma":[0.9923921,0.00013660736,0.006143098,0.00041439864,0.0004309654,0.0000012770406,0.000006589513,0.000018892626,0.00045605723],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9966102,0.00019069327,0.0012353451,0.00038223443,0.0013101269,0.00027135244],"domain_scores_gemma":[0.99435234,0.0022864426,0.000868569,0.0004925113,0.0017064208,0.00029370005],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0034288897,0.00018240848,0.00054946763,0.00037831912,0.00024343953,0.00058584183,0.00070735597,0.00014865524,0.001366755],"category_scores_gemma":[0.0060619055,0.00012254142,0.0006334809,0.00040726623,0.00007425982,0.0009484504,0.00022498879,0.00022080967,0.0002236984],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017882693,0.0020678912,0.03125985,0.000013625347,0.00006733361,0.0008871332,0.00080761354,0.0004373041,0.013083253,0.00022871427,0.15219794,0.7971611],"study_design_scores_gemma":[0.0087265605,0.0037275509,0.18571602,0.0012950229,0.0004421995,0.0043672584,0.017420927,0.0050220652,0.006072974,0.12571995,0.64021766,0.0012717899],"about_ca_topic_score_codex":0.000020196243,"about_ca_topic_score_gemma":0.000033052384,"teacher_disagreement_score":0.79588926,"about_ca_system_score_codex":0.0001296115,"about_ca_system_score_gemma":0.00041147336,"threshold_uncertainty_score":0.9995461},"labels":[],"label_agreement":null},{"id":"W3203492635","doi":"10.1037/dev0001226","title":"Hindsight bias and false-belief reasoning from preschool to old age.","year":2021,"lang":"en","type":"article","venue":"Developmental Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kwantlen Polytechnic University","funders":"Social Sciences and Humanities Research Council of Canada; Canada Research Chairs","keywords":"Hindsight bias; Psychology; False belief; Developmental psychology; Theory of mind; Cognitive development; Cognitive psychology; Cognition","score_opus":0.20276103245079985,"score_gpt":0.42923391078912787,"score_spread":0.22647287833832802,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3203492635","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9835971,0.00019242817,0.00064463273,0.0014598252,0.0014425465,0.00012240215,0.00004597121,0.000048811384,0.01244631],"genre_scores_gemma":[0.9385575,0.00003388497,0.049204838,0.007456732,0.0001100235,0.000018599612,0.00003307821,0.000025739786,0.0045595705],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9970339,0.00017877994,0.0007858134,0.0011691798,0.00046734035,0.00036499443],"domain_scores_gemma":[0.99819124,0.0006482643,0.00015791088,0.00057080877,0.00012541385,0.00030634544],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0010046186,0.00022150176,0.00043182116,0.00025430298,0.0001872386,0.00042014613,0.0006072843,0.00018455186,0.0020401988],"category_scores_gemma":[0.0015006075,0.000191369,0.00007606903,0.00054802693,0.00008338792,0.00022913732,0.00048461542,0.00023098859,0.0029948014],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007951792,0.00014373958,0.08129253,6.8433565e-7,0.000028346001,0.00052678137,0.001232899,0.000005394549,0.006083385,0.00024519366,0.048226796,0.86213475],"study_design_scores_gemma":[0.0009111777,0.000078157405,0.55540353,0.000050865536,0.000011750548,0.00024392665,0.0010096482,0.000016602224,0.001826741,0.038767718,0.40120536,0.0004745493],"about_ca_topic_score_codex":0.000056504017,"about_ca_topic_score_gemma":0.00023136135,"teacher_disagreement_score":0.8616602,"about_ca_system_score_codex":0.0000687715,"about_ca_system_score_gemma":0.00009489243,"threshold_uncertainty_score":0.9988721},"labels":[],"label_agreement":null},{"id":"W3205897733","doi":"10.3390/jrfm14100490","title":"Behavioral Decision Making in Normative and Descriptive Views: A Critical Review of Literature","year":2021,"lang":"en","type":"review","venue":"Journal of risk and financial management","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Normative; Ambiguity; Underpinning; Management science; Psychology; Decision theory; Decision analysis; Behavioral economics; Loss aversion; Normative model of decision-making; Computer science; Epistemology; Economics; Microeconomics","score_opus":0.1475315296025813,"score_gpt":0.4533514488544466,"score_spread":0.3058199192518653,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3205897733","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010026877,0.9943277,0.0034012084,0.000018390034,0.000688337,0.00035209113,0.000095734664,0.0000019803067,0.00011181967],"genre_scores_gemma":[0.0005658702,0.9898678,0.009365605,0.000071128794,0.000089379166,0.0000087168655,0.0000025920967,0.000014945937,0.000013930923],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99470323,0.00057094195,0.0031691645,0.00046574796,0.00086031517,0.00023060896],"domain_scores_gemma":[0.99507713,0.0017041354,0.0021097704,0.00038240768,0.0006090981,0.00011747097],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0053216927,0.00036308804,0.0030816954,0.0010864439,0.00009129763,0.00031099527,0.00055380136,0.00023891976,0.0000458956],"category_scores_gemma":[0.0038219308,0.00023916626,0.00065830123,0.001208299,0.00013500977,0.00046642384,0.00051757833,0.00081641617,0.00000559264],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025098527,0.00012309547,0.000051874402,0.004127479,0.000009591653,0.000499136,0.0004722314,3.5822873e-7,6.337224e-9,0.00036352678,0.0012435657,0.993084],"study_design_scores_gemma":[0.00020489172,0.00016467572,0.00025512034,0.29160482,0.0006557837,0.00022154946,0.0002962486,0.000002219047,2.9492693e-8,0.011078519,0.6953159,0.00020028559],"about_ca_topic_score_codex":0.0000032442424,"about_ca_topic_score_gemma":0.000016192394,"teacher_disagreement_score":0.99288374,"about_ca_system_score_codex":0.00011580748,"about_ca_system_score_gemma":0.00014001908,"threshold_uncertainty_score":0.9752917},"labels":[],"label_agreement":null},{"id":"W3207220179","doi":"10.1016/j.cognition.2021.104934","title":"The effects of cueing episodic future thinking on delay discounting in children, adolescents, and adults","year":2021,"lang":"en","type":"article","venue":"Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"Economic and Social Research Council","keywords":"Psychology; Delay of gratification; Delay discounting; Gratification; Discounting; Intertemporal choice; Temporal discounting; Developmental psychology; Affect (linguistics); Trait; Value (mathematics); Cognitive psychology; Cognition; Social psychology; Impulsivity","score_opus":0.016490195087892796,"score_gpt":0.3043624066559573,"score_spread":0.28787221156806453,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3207220179","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99816173,0.0006899204,0.00011436185,0.00015431845,0.0004390597,0.00017658836,0.0000053297654,0.0000106662155,0.00024803725],"genre_scores_gemma":[0.9994269,0.00018065571,0.00008465384,0.00016871029,0.00010446098,0.0000066689895,0.000007529189,0.000007453355,0.000012993479],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99858725,0.00013630041,0.0003959272,0.00032727284,0.00040270813,0.0001505166],"domain_scores_gemma":[0.9984363,0.0009537024,0.00020938263,0.00023078936,0.00013627349,0.000033573946],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00092184945,0.0000957803,0.0001657182,0.000108406435,0.00022475897,0.000246852,0.00019004002,0.000068869274,0.0000076151305],"category_scores_gemma":[0.0013623482,0.00006372066,0.000057327314,0.0003065981,0.000055564862,0.00019942506,0.00010502035,0.00018296743,0.000023044191],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000039323542,0.000055535595,0.05648926,0.000009976426,0.0000032424955,0.000012949558,0.0003205593,0.000006874965,0.00021411013,0.00013361001,0.00004975236,0.9426648],"study_design_scores_gemma":[0.0018098659,0.00013883329,0.89483213,0.003025772,0.000041928473,0.00005917445,0.002625705,0.0006416204,0.0066167847,0.0894844,0.0004435014,0.00028027335],"about_ca_topic_score_codex":0.0000060972384,"about_ca_topic_score_gemma":0.00008507494,"teacher_disagreement_score":0.94238454,"about_ca_system_score_codex":0.000018493418,"about_ca_system_score_gemma":0.000021973576,"threshold_uncertainty_score":0.25984532},"labels":[],"label_agreement":null},{"id":"W3208397276","doi":"10.21203/rs.3.rs-1048207/v1","title":"The globalizability of temporal discounting","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University; McGill University","funders":"Economic and Social Research Council","keywords":"Discounting; Economics; Econometrics; Finance","score_opus":0.34270716156599124,"score_gpt":0.5597152017425966,"score_spread":0.21700804017660535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3208397276","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9905032,0.0011998547,0.00030314422,0.0013116845,0.0010346968,0.00049751735,0.00014937548,0.000023663071,0.004976898],"genre_scores_gemma":[0.9984343,0.00012994821,0.0005377232,0.00000988129,0.00016583601,0.000037638576,0.000025507925,0.00001886078,0.0006402835],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9899982,0.0018547965,0.0015467451,0.0011959445,0.00474306,0.0006612476],"domain_scores_gemma":[0.98416054,0.007997769,0.0005716392,0.0035079976,0.0035774813,0.00018455155],"candidate_categories":["metaresearch","scholarly_communication"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.032990877,0.00022833276,0.0006522491,0.00029359516,0.00067674636,0.0026818935,0.0034807501,0.0003301971,0.00042574707],"category_scores_gemma":[0.026170377,0.00013473176,0.00054682663,0.001159844,0.00087754836,0.00020453596,0.0063247634,0.0014734174,0.00013637119],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001090656,0.0003427896,0.19723356,0.00013721031,0.00003951684,0.00005659231,0.00089319085,0.0009903188,0.000065776425,0.0013251866,0.013894898,0.78491193],"study_design_scores_gemma":[0.00039167822,0.00022139738,0.109007016,0.0013514359,0.000024541756,0.000012646387,0.027143253,0.0064455373,0.0005155962,0.7640097,0.09019909,0.0006780976],"about_ca_topic_score_codex":0.0012511606,"about_ca_topic_score_gemma":0.0011912704,"teacher_disagreement_score":0.7842338,"about_ca_system_score_codex":0.00028229842,"about_ca_system_score_gemma":0.0013453695,"threshold_uncertainty_score":0.9983534},"labels":[],"label_agreement":null},{"id":"W3209539600","doi":"10.5281/zenodo.4007866","title":"Replication package for: Stochastic Revealed Preferences with Measurement Error","year":2020,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Replication (statistics); Computer science; Statistics; Mathematics","score_opus":0.34519049537582386,"score_gpt":0.36199735507997255,"score_spread":0.01680685970414869,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3209539600","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.55076486,0.0001011366,0.40259883,0.010472774,0.00024359816,0.0025973688,0.0007497256,0.0013065222,0.031165157],"genre_scores_gemma":[0.9976713,0.0000041577955,0.0011299229,0.00027758078,0.000104421626,2.5902978e-7,0.00020445338,0.00041787705,0.00019004782],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9969772,0.00025579293,0.0005075501,0.0008780076,0.0010965363,0.00028491937],"domain_scores_gemma":[0.99660724,0.0001243543,0.00030289392,0.0010011878,0.0017040056,0.0002602881],"candidate_categories":["sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0028582262,0.00015050943,0.00023372084,0.00016660076,0.0013011857,0.0013237623,0.0017191487,0.000055997316,0.0031166594],"category_scores_gemma":[0.008134418,0.0001177307,0.00006927788,0.00068212906,0.0001216396,0.0003403782,0.00052247016,0.00016802255,0.00466932],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041252104,0.00012319432,0.000019570563,0.000018272623,0.000026903777,0.0000033460926,0.001472307,0.00060300704,0.0032768873,0.0008671984,0.18770517,0.8054716],"study_design_scores_gemma":[0.0010289139,0.0012738956,0.0011509204,0.000058408852,0.000039832732,0.00003613846,0.0013554947,0.0034410069,0.0005089772,0.0075484174,0.983209,0.00034897454],"about_ca_topic_score_codex":0.0000042147885,"about_ca_topic_score_gemma":0.0000012795468,"teacher_disagreement_score":0.8051227,"about_ca_system_score_codex":0.00013551148,"about_ca_system_score_gemma":0.000014059695,"threshold_uncertainty_score":0.999999},"labels":[],"label_agreement":null},{"id":"W3209547369","doi":"","title":"Endogenous Risk Attitudes","year":2021,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Perception; Decision maker; Risk perception; Anticipation (artificial intelligence); Weighting; Prospect theory; Lottery; Limit (mathematics); Function (biology); Psychology; Economics; Econometrics; Microeconomics; Mathematics; Computer science; Artificial intelligence; Management science","score_opus":0.10336993199991618,"score_gpt":0.3698981964218558,"score_spread":0.2665282644219396,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3209547369","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98324865,0.0039546126,0.006131332,0.00047640133,0.0008318681,0.000041899748,0.0000089819905,0.000028419074,0.0052778483],"genre_scores_gemma":[0.9922814,0.0034085077,0.0004869818,0.00012621855,0.0003237452,0.0000014492393,0.0000013741354,0.000018343444,0.0033520253],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9958835,0.0002953063,0.0007250531,0.0004479914,0.00085889176,0.0017892192],"domain_scores_gemma":[0.99779975,0.0006228337,0.000417494,0.00057079265,0.0004348454,0.00015430634],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.007279264,0.00016215381,0.00032461787,0.00019072172,0.0005094574,0.00063961087,0.00087145914,0.000093463794,0.00065595534],"category_scores_gemma":[0.002232571,0.000121861456,0.00031889183,0.000489214,0.000057432047,0.00033720527,0.00014572857,0.0017740054,0.0013309544],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022743947,0.00012480098,0.01938815,2.8675962e-7,0.00005309345,0.00009230675,0.00009056153,0.00017675736,0.0005056364,0.010292357,0.00050238374,0.9687509],"study_design_scores_gemma":[0.0003895414,0.00014702194,0.0017378227,0.0000074478694,0.00003331119,0.004135334,0.0015692805,0.00005335075,0.00035736003,0.9648577,0.02652836,0.00018347643],"about_ca_topic_score_codex":0.000038213988,"about_ca_topic_score_gemma":0.0012896458,"teacher_disagreement_score":0.96856743,"about_ca_system_score_codex":0.00057688815,"about_ca_system_score_gemma":0.0031262427,"threshold_uncertainty_score":0.99944663},"labels":[],"label_agreement":null},{"id":"W3210758287","doi":"10.1016/b978-0-12-816636-9.00011-6","title":"Development of the ability to detect and override miserly information processing","year":2021,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Information processing; Psychology; Information processing theory; Cognition; Cognitive psychology; Heuristic; Social psychology; Computer science; Artificial intelligence","score_opus":0.06707639137507482,"score_gpt":0.32918162999994055,"score_spread":0.26210523862486573,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3210758287","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20953943,0.00021402116,0.00013465945,0.000091864655,0.00049019227,0.0005748429,0.000034850942,0.000020614358,0.78889954],"genre_scores_gemma":[0.13034752,0.000011391256,0.04698986,0.0011067084,0.00012830866,0.00004796543,0.000009428716,0.00006306958,0.82129574],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99726266,0.00003073266,0.0013035866,0.00039203904,0.000854069,0.00015690376],"domain_scores_gemma":[0.9978099,0.0002112349,0.00069965457,0.0007279496,0.00044249638,0.00010876878],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001589178,0.00023903455,0.00047671027,0.00017644683,0.00020361278,0.00033607872,0.00060627365,0.00018664708,0.000110312525],"category_scores_gemma":[0.000544131,0.0001553286,0.00015266065,0.000049098766,0.0001063431,0.00019201038,0.0004916189,0.00023036062,0.00007941183],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001044265,0.0000016510616,0.000019057263,0.000020546673,0.000004486564,6.5169183e-7,0.0010087094,0.000002951502,0.000068856905,0.00006130586,0.000040344272,0.998761],"study_design_scores_gemma":[0.00009695789,0.000016777458,0.0011409253,0.0004130514,0.00002258472,0.000007825145,0.00011375574,0.000010324556,0.00036037748,0.02878555,0.96880776,0.00022409103],"about_ca_topic_score_codex":4.834098e-7,"about_ca_topic_score_gemma":0.00007541667,"teacher_disagreement_score":0.9985369,"about_ca_system_score_codex":0.00011147863,"about_ca_system_score_gemma":0.00057578005,"threshold_uncertainty_score":0.63341165},"labels":[],"label_agreement":null},{"id":"W3211629106","doi":"10.2308/tar-2020-0305","title":"The Beneficial Learning Effects of Combining a Hypothesis-Testing Mindset with a Causal Model","year":2021,"lang":"en","type":"article","venue":"The Accounting Review","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; Western University","funders":"","keywords":"Mindset; Causal model; Control (management); Causal analysis; Psychology; Computer science; Econometrics; Economics; Artificial intelligence","score_opus":0.12877444529769258,"score_gpt":0.36143604372151283,"score_spread":0.23266159842382025,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3211629106","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9806685,0.016595615,0.00037948403,0.00077785796,0.00015805973,0.00026215782,0.000002138612,0.000032196447,0.0011239934],"genre_scores_gemma":[0.9948959,0.0015118937,0.0027347626,0.00052703125,0.00007124738,0.000021877495,8.10504e-7,0.000026642283,0.00020984162],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99719507,0.0003486968,0.0008854107,0.00040061717,0.0008498331,0.00032035218],"domain_scores_gemma":[0.9779635,0.019314952,0.0010607024,0.00095195376,0.0006656259,0.000043273816],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0063502486,0.00018994494,0.00058805523,0.000048826536,0.00072338514,0.00043429894,0.0010251683,0.00004716038,0.000018247423],"category_scores_gemma":[0.030273328,0.00008986924,0.00016322205,0.00095330446,0.00013062442,0.00018998452,0.00033015438,0.00035008535,0.000078774334],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014630241,0.000034898967,0.0028545945,0.00017345244,0.000020518239,0.000017699225,0.00022387442,0.0031264892,0.0003502731,0.000175455,0.00057681603,0.9924313],"study_design_scores_gemma":[0.00463755,0.0014051138,0.028809002,0.10276737,0.0040943827,0.001728158,0.0062138964,0.44099396,0.008237795,0.31024072,0.08639964,0.0044724173],"about_ca_topic_score_codex":0.000028202947,"about_ca_topic_score_gemma":0.000049995022,"teacher_disagreement_score":0.9879589,"about_ca_system_score_codex":0.000025587458,"about_ca_system_score_gemma":0.00022339515,"threshold_uncertainty_score":0.9778951},"labels":[],"label_agreement":null},{"id":"W3216246799","doi":"10.1016/j.cogpsych.2021.101443","title":"Hypothesis testing, attention, and ‘Same’-‘Different’ judgments","year":2021,"lang":"en","type":"article","venue":"Cognitive Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Intuition; Converse; Psychology; Stimulus (psychology); Cognitive psychology; Cognition; Perception; Set (abstract data type); Social psychology; Computer science; Mathematics; Cognitive science","score_opus":0.3584158466734584,"score_gpt":0.4618216681543257,"score_spread":0.1034058214808673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3216246799","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97969186,0.00017546928,0.0015391699,0.00088784314,0.0007369067,0.00009131067,0.00004944866,0.000035235676,0.016792772],"genre_scores_gemma":[0.99382395,0.000036249574,0.0014380194,0.002737712,0.00008016991,0.0000142621075,0.0000057934935,0.000015900476,0.0018479226],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9976842,0.00026314714,0.00054551644,0.0009098157,0.00031849448,0.00027886825],"domain_scores_gemma":[0.99491507,0.00362935,0.00022555687,0.00038662602,0.00069991825,0.00014350505],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00065261597,0.00017426806,0.00035975093,0.00020654013,0.00016967834,0.00022647536,0.0002764484,0.00013007486,0.0012727819],"category_scores_gemma":[0.009392593,0.00014272003,0.000094436844,0.0004364226,0.00023598706,0.00014523031,0.00018876494,0.00016421758,0.0013184698],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025871763,0.00016580429,0.16428651,8.717483e-7,0.000015807587,0.000061775776,0.00005554801,1.0186886e-7,0.0012983417,0.000044759818,0.0034137617,0.83063084],"study_design_scores_gemma":[0.0009233797,0.00012515421,0.80898696,0.000042722277,0.000043097283,0.00019236268,0.00053297397,0.000031074123,0.0003973849,0.18519329,0.0033150623,0.00021655564],"about_ca_topic_score_codex":0.0000050425583,"about_ca_topic_score_gemma":0.000028805876,"teacher_disagreement_score":0.8304143,"about_ca_system_score_codex":0.000015354695,"about_ca_system_score_gemma":0.000031035728,"threshold_uncertainty_score":0.99964017},"labels":[],"label_agreement":null},{"id":"W322901492","doi":"","title":"Mental Simulation and Stability Over Time","year":2005,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Trope (literature); Preference; Time preference; Stability (learning theory); Economics; Mental effort; Intertemporal choice; Task (project management); Psychology; Computer science; Cognitive psychology; Microeconomics","score_opus":0.05762878922459367,"score_gpt":0.38401916621792764,"score_spread":0.32639037699333395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W322901492","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9966681,0.00037055046,0.0015284402,0.00065660797,0.00013249744,0.00006699149,0.0000046726454,0.000015490026,0.00055665785],"genre_scores_gemma":[0.99877393,0.00009272676,0.00016426702,0.000095755786,0.00019049586,5.1663443e-7,9.536615e-7,0.000008569479,0.0006727697],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99772125,0.00010312729,0.00050890876,0.00028373057,0.00053378457,0.00084917946],"domain_scores_gemma":[0.9989788,0.000383152,0.00021270626,0.00022839718,0.00009748259,0.00009947773],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005401536,0.00011012945,0.00018425797,0.00013159566,0.000236162,0.00029959105,0.00029571113,0.0000629765,0.0009042182],"category_scores_gemma":[0.0003966018,0.00008151192,0.00009415187,0.00015325013,0.000056430148,0.00064624974,0.00007111103,0.00061260274,0.00043686942],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000054336,0.000058191425,0.0071702595,1.2833064e-7,0.000009898244,5.528419e-7,0.00015724574,0.0009393042,0.0003032483,0.0007600037,0.00021678477,0.99033004],"study_design_scores_gemma":[0.00088954775,0.00027178097,0.0069201207,0.000006438732,0.000019677607,0.00019714766,0.0006583824,0.06638071,0.000110238754,0.8984312,0.025863132,0.00025163597],"about_ca_topic_score_codex":0.000007526153,"about_ca_topic_score_gemma":0.00019355852,"teacher_disagreement_score":0.9900784,"about_ca_system_score_codex":0.00064275716,"about_ca_system_score_gemma":0.00040735607,"threshold_uncertainty_score":0.9900555},"labels":[],"label_agreement":null},{"id":"W4200056893","doi":"10.1109/iros51168.2021.9636479","title":"A Marginal Log-Likelihood Approach for the Estimation of Discount Factors of Multiple Experts in Inverse Reinforcement Learning","year":2021,"lang":"en","type":"article","venue":"2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Marginal likelihood; Computer science; Latent variable; Machine learning; Probabilistic logic; Hyperparameter; Expectation–maximization algorithm; Markov decision process; Artificial intelligence; Principle of maximum entropy; Reinforcement learning; Latent variable model; Likelihood function; Variable (mathematics); Markov process; Bayesian probability; Mathematical optimization; Mathematics; Maximum likelihood; Estimation theory; Statistics; Algorithm","score_opus":0.21327069326339732,"score_gpt":0.3892692312640018,"score_spread":0.1759985380006045,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200056893","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7081993,0.000111015936,0.28842524,0.00015240481,0.0013620309,0.00045709242,0.000045222256,0.00000603534,0.0012416395],"genre_scores_gemma":[0.99793965,0.00014470812,0.0006227278,0.000019824562,0.00005311175,0.00006329501,0.000058301794,0.00001019818,0.00108816],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99710953,0.00013361424,0.0012186749,0.00047251367,0.00087146886,0.00019418928],"domain_scores_gemma":[0.9972167,0.0010792591,0.00064880075,0.00033735816,0.00064611225,0.00007179028],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013544856,0.00019515448,0.0004477028,0.00027176135,0.00010040063,0.0002742655,0.0004859558,0.000096440875,0.00028466937],"category_scores_gemma":[0.0010883809,0.0001274674,0.00015964615,0.00020504056,0.00011415984,0.0002091252,0.000115609546,0.0001593753,0.0000092116325],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018519319,0.00028227206,0.017101573,0.000040624942,0.00007061606,0.00000515742,0.0028444282,0.89980674,0.00184185,0.010348207,0.00038450482,0.06708881],"study_design_scores_gemma":[0.00040126895,0.00014361675,0.0011474229,0.00024550577,0.000015420346,0.000006965198,0.016372085,0.9771185,0.0024434829,0.0012524525,0.00069824833,0.00015506183],"about_ca_topic_score_codex":0.00042154428,"about_ca_topic_score_gemma":0.0001366349,"teacher_disagreement_score":0.28974035,"about_ca_system_score_codex":0.00010948171,"about_ca_system_score_gemma":0.00014108984,"threshold_uncertainty_score":0.51979697},"labels":[],"label_agreement":null},{"id":"W4200124202","doi":"10.1002/jcpy.1283","title":"The wellbeing implications of maximizing: A conceptual framework and meta‐analysis","year":2021,"lang":"en","type":"article","venue":"Journal of Consumer Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Psychology; Outcome (game theory); Maximization; Process (computing); Focus (optics); Conceptual framework; Meta-analysis; Decision maker; Social psychology; Management science; Economics; Microeconomics; Computer science; Epistemology","score_opus":0.24260888221096222,"score_gpt":0.47723490670550184,"score_spread":0.23462602449453962,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200124202","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91844416,0.021378811,0.032824982,0.025000032,0.00076649006,0.000067445326,0.0000246756,0.000005533816,0.0014878649],"genre_scores_gemma":[0.9883665,0.0006931651,0.009912463,0.0008532965,0.000030262081,0.000001762949,2.939697e-7,0.0000058798955,0.00013637474],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.997601,0.00035992105,0.0012835767,0.00025007362,0.00034464177,0.00016082502],"domain_scores_gemma":[0.9917673,0.005388275,0.0011795062,0.0006626095,0.0008943546,0.00010799165],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024986472,0.00010248618,0.00083007617,0.0002900611,0.000160477,0.00014200548,0.00061395887,0.00011604635,0.0005412228],"category_scores_gemma":[0.0020255623,0.00005919976,0.0006792056,0.0008733033,0.00050644216,0.00012340792,0.00009299506,0.00031182313,0.000016857162],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044493313,0.00073095545,0.12313361,0.0000044012795,0.092581004,0.00019705982,0.0031457508,0.00048611328,0.0032151004,0.06400559,0.025115041,0.68694043],"study_design_scores_gemma":[0.0006450718,0.00016540657,0.06430131,0.0000064338105,0.055313386,0.00092253136,0.0026351656,0.000041887648,0.0002601178,0.6819989,0.19348085,0.00022895857],"about_ca_topic_score_codex":0.0000030398487,"about_ca_topic_score_gemma":0.000027412238,"teacher_disagreement_score":0.6867115,"about_ca_system_score_codex":0.000008646228,"about_ca_system_score_gemma":0.00010614447,"threshold_uncertainty_score":0.592601},"labels":[],"label_agreement":null},{"id":"W4200311074","doi":"10.1111/phc3.12794","title":"Teaching &amp; learning guide for: Risky‐choice framing and rational decision‐making","year":2021,"lang":"en","type":"article","venue":"Philosophy Compass","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Framing effect; Prospect theory; Framing (construction); Expected utility hypothesis; Decision theory; Decision field theory; Evidential decision theory; Empirical research; Rationality; Epistemology; Decision analysis; Psychology; Positive economics; Mathematical economics; Computer science; Social psychology; Economics; Decision engineering; Business decision mapping; Microeconomics; Persuasion","score_opus":0.15259550135196523,"score_gpt":0.43255974557467985,"score_spread":0.2799642442227146,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200311074","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.79256004,0.0004961393,0.18977009,0.0028950975,0.0011253227,0.00019934309,0.00003967696,0.000112764734,0.012801506],"genre_scores_gemma":[0.91786444,0.000010629419,0.080211334,0.0006109458,0.00067775114,0.000017326644,0.000018234727,0.00003062832,0.0005587072],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9963118,0.00028658545,0.0011104767,0.0009779593,0.0009479609,0.00036524175],"domain_scores_gemma":[0.9866361,0.011559252,0.0004346125,0.0006602012,0.00054362917,0.00016618917],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.003137888,0.0002634971,0.00054990756,0.00031344622,0.0011184991,0.0010340472,0.00063170714,0.00013280238,0.00019597323],"category_scores_gemma":[0.012914594,0.00023812076,0.00024147217,0.0003368892,0.00009260902,0.000592288,0.00046915415,0.00054259616,0.00019804636],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006367731,0.00012606183,0.022165418,0.000009479938,0.000031056967,0.000018474448,0.00056672486,0.0042209774,0.0005804046,0.017744219,0.008437512,0.946036],"study_design_scores_gemma":[0.0004770079,0.00003421656,0.0046403194,0.00012049943,0.00002401141,0.00004709695,0.00016820608,0.011577359,0.00002833019,0.6058214,0.37676278,0.00029877847],"about_ca_topic_score_codex":0.00002360802,"about_ca_topic_score_gemma":0.00011001904,"teacher_disagreement_score":0.94573724,"about_ca_system_score_codex":0.00008933603,"about_ca_system_score_gemma":0.00012601874,"threshold_uncertainty_score":0.99713415},"labels":[],"label_agreement":null},{"id":"W4200495547","doi":"10.22230/src.2021v12n1a381","title":"Lecture 10: Rhetoric and Behavioral Economics","year":2021,"lang":"fr","type":"article","venue":"Scholarly and Research Communication","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Persuasion; Rhetoric; Humanities; Gens; Sociology; Positive economics; Welfare economics; Economics; Psychology; Social psychology; Philosophy; Theology","score_opus":0.31860779150733626,"score_gpt":0.49729334940272496,"score_spread":0.1786855578953887,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200495547","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87968516,0.093438484,0.0000711637,0.021429235,0.00054592144,0.00019760539,0.00005827168,0.00001862828,0.004555551],"genre_scores_gemma":[0.9208142,0.052221354,0.003984284,0.00014453384,0.00012745833,0.000018516605,0.00004164595,0.000027572423,0.022620441],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99494773,0.00233215,0.0006974595,0.0007792054,0.0006979138,0.0005455291],"domain_scores_gemma":[0.99286723,0.0024019647,0.0001720101,0.001976465,0.0021707134,0.00041164164],"candidate_categories":["sts","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.010424398,0.00021347549,0.0003802787,0.00041073587,0.0017253355,0.0071055093,0.0011412856,0.00050415087,0.001190724],"category_scores_gemma":[0.0034485902,0.00020580384,0.00009965596,0.00091173616,0.0010588695,0.0035006055,0.002081083,0.0020298047,0.0005025681],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004470757,0.00025922764,0.0021753276,0.00001152821,0.000013626773,0.00001771288,0.0009823487,0.000018210116,0.00020067146,0.005855973,0.0036645797,0.9867561],"study_design_scores_gemma":[0.0006198896,0.00027054988,0.008580774,0.00019900198,0.000034329703,0.00016678488,0.0020952553,0.0012879224,0.00041529085,0.26486135,0.72114027,0.00032857404],"about_ca_topic_score_codex":0.00036774125,"about_ca_topic_score_gemma":0.001017712,"teacher_disagreement_score":0.9864275,"about_ca_system_score_codex":0.0002406497,"about_ca_system_score_gemma":0.0006646106,"threshold_uncertainty_score":0.9997223},"labels":[],"label_agreement":null},{"id":"W4200503215","doi":"10.31234/osf.io/kt5ya","title":"Conjectures on Science and Rationality: Commentary on Fiedler, Salmen, &amp;amp; Prager (2022)","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Rationality; Mathematical economics; Epistemology; Philosophy; Ecological rationality; Laplace transform; Economics; Mathematics","score_opus":0.2083340373998797,"score_gpt":0.44396456939372336,"score_spread":0.23563053199384365,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200503215","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9605247,0.00018986997,0.0012795413,0.014679341,0.0031855807,0.00046872324,0.00014172157,0.00007552443,0.019455047],"genre_scores_gemma":[0.95180964,0.000106626394,0.0062042233,0.03720631,0.0003144595,0.000044033248,0.00013985722,0.000029418092,0.0041453997],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99324834,0.00028335373,0.0010385037,0.002028096,0.0030016697,0.00040000377],"domain_scores_gemma":[0.9930614,0.0030927607,0.00049396936,0.0021522606,0.00091216824,0.0002873997],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0063706003,0.0004383968,0.000687158,0.00069156406,0.0005645665,0.0030652247,0.0016216063,0.00029035707,0.0044952193],"category_scores_gemma":[0.005046723,0.0003182949,0.00018958497,0.00060793135,0.0006584947,0.00032287528,0.0023173625,0.0008780264,0.00061391393],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015128953,0.00058487116,0.002189572,0.00001324092,0.000040509098,0.000032385593,0.0006885536,0.0030574591,0.00046142092,0.005029401,0.60574645,0.38200486],"study_design_scores_gemma":[0.0008298642,0.00020362022,0.010407086,0.00032709265,0.00006147774,0.000039295912,0.0008733791,0.00089994335,0.001398883,0.28174803,0.70181584,0.0013954813],"about_ca_topic_score_codex":0.00024448332,"about_ca_topic_score_gemma":0.0005348152,"teacher_disagreement_score":0.38060936,"about_ca_system_score_codex":0.00030560375,"about_ca_system_score_gemma":0.000711516,"threshold_uncertainty_score":0.9999269},"labels":[],"label_agreement":null},{"id":"W4200611774","doi":"10.1177/00222437211068025","title":"Understanding and Neutralizing the Expense Prediction Bias: The Role of Accessibility, Typicality, and Skewness","year":2021,"lang":"en","type":"article","venue":"Journal of Marketing Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Booth University College","funders":"Social Sciences and Humanities Research Council of Canada; Booth School of Business, University of Chicago","keywords":"Skewness; Skew; Econometrics; Mode (computer interface); Economics; Advertising; Actuarial science; Marketing; Business; Computer science","score_opus":0.6610217989920589,"score_gpt":0.5100268606449933,"score_spread":0.15099493834706568,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200611774","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99469626,0.0009965942,0.00026569818,0.0028147083,0.00016933055,0.00007472672,0.0000040761993,0.0000025598886,0.0009760175],"genre_scores_gemma":[0.999307,0.00035772548,0.00013386829,0.00002490701,0.000104523366,9.0040714e-7,1.13244866e-7,0.00000621156,0.00006479264],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9935312,0.003651312,0.0008751569,0.00024325246,0.0014599423,0.00023911134],"domain_scores_gemma":[0.9694982,0.028525492,0.00046575532,0.00040923903,0.0010012491,0.00010005867],"candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.083890736,0.00007408956,0.00024394106,0.00020392756,0.0005025169,0.00082718884,0.0005912127,0.00006734073,0.00006486012],"category_scores_gemma":[0.029758597,0.000036160145,0.00008799449,0.00058464566,0.0004340816,0.00031446054,0.0006464061,0.000626196,0.0000011629488],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010410901,0.00012835678,0.5575292,0.00002470001,0.000040665276,0.0000395067,0.0024934825,0.00005636543,0.0031517975,0.0018338248,0.0014762406,0.4321848],"study_design_scores_gemma":[0.00043795447,0.00011282656,0.43057278,0.0003247652,0.000026246571,0.00037026042,0.06275679,0.0024512794,0.00094697945,0.4984645,0.0034498412,0.00008580003],"about_ca_topic_score_codex":0.000016142922,"about_ca_topic_score_gemma":0.000038270435,"teacher_disagreement_score":0.49663067,"about_ca_system_score_codex":0.000079925434,"about_ca_system_score_gemma":0.00019365808,"threshold_uncertainty_score":0.9784142},"labels":[],"label_agreement":null},{"id":"W4205204427","doi":"10.18438/eblip30044","title":"Announcing and Advocating: The Missing Step in the EBLIP Model","year":2021,"lang":"en","type":"article","venue":"Evidence Based Library and Information Practice","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Data science; Operations research; Mathematics","score_opus":0.10540163403748827,"score_gpt":0.3691787815054047,"score_spread":0.2637771474679164,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205204427","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5074127,0.0019817755,0.026076283,0.4490667,0.00026631556,0.0003513851,0.000012831611,0.000052755215,0.014779281],"genre_scores_gemma":[0.8870087,0.0004122335,0.013852889,0.098544456,0.000044785593,0.00001066291,0.0000063702923,0.000004755457,0.00011511268],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979875,0.00051182875,0.0006348986,0.00019160562,0.0005384633,0.0001357121],"domain_scores_gemma":[0.9863255,0.012622905,0.00040914599,0.0004675164,0.0001201365,0.000054800566],"candidate_categories":["metaresearch","scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0047341282,0.00009846918,0.00012301926,0.00012695814,0.0003843114,0.0030513415,0.0004075039,0.000053771455,0.00006085857],"category_scores_gemma":[0.014033613,0.000054800585,0.00003136242,0.00070524873,0.000076158205,0.116275795,0.00016247369,0.00027332606,0.000029763041],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014389589,0.000042445492,0.002077749,0.000016441145,0.0000033052966,0.00001366282,0.003172841,0.0065373685,0.000048446556,0.0317191,0.006686252,0.94953847],"study_design_scores_gemma":[0.0003057301,0.000053709467,0.0072876117,0.00025867033,0.000022507264,0.00015271317,0.022009412,0.5936514,0.00018954292,0.013708123,0.36217132,0.00018924433],"about_ca_topic_score_codex":0.000005382476,"about_ca_topic_score_gemma":3.6951155e-7,"teacher_disagreement_score":0.9493492,"about_ca_system_score_codex":0.000007978223,"about_ca_system_score_gemma":0.00035188827,"threshold_uncertainty_score":0.9979836},"labels":[],"label_agreement":null},{"id":"W4205741254","doi":"10.31234/osf.io/kpy8a","title":"Information about task progress modulates cognitive demand avoidance","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Army Research Office; Natural Sciences and Engineering Research Council of Canada","keywords":"Task (project management); Cognition; Psychology; Cognitive psychology; Variety (cybernetics); Action (physics); Social psychology; Computer science; Economics; Artificial intelligence; Neuroscience","score_opus":0.07592392844458976,"score_gpt":0.38732076921248093,"score_spread":0.3113968407678912,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205741254","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9672887,0.00066526094,0.022317246,0.00031064684,0.0018039873,0.00050540606,0.00016437196,0.000119041186,0.006825342],"genre_scores_gemma":[0.9948232,0.00008744718,0.0035059417,0.00041145206,0.000108421125,0.00007807256,0.00019039588,0.000016340651,0.0007786942],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9959334,0.00017994875,0.0015697783,0.00072984,0.0012370391,0.000349999],"domain_scores_gemma":[0.99524957,0.00095854804,0.001012531,0.0009919385,0.0016130528,0.00017433312],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0022463377,0.00038145596,0.00073062436,0.000424133,0.00020389348,0.003874889,0.0011410575,0.00047617836,0.00093398895],"category_scores_gemma":[0.002394906,0.0002900744,0.0003361554,0.0003923127,0.00020356433,0.0014458365,0.0016897073,0.0006381143,0.001392371],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000036805788,0.000084078434,0.00712681,0.000019272162,0.000031689484,0.000014193916,0.0017410419,0.0016344709,0.000005169967,0.00009710797,0.0025619774,0.98664737],"study_design_scores_gemma":[0.0037634636,0.00042893537,0.22723383,0.0049660006,0.0005256216,0.00018872009,0.03380311,0.15543082,0.0044778725,0.49783766,0.06541194,0.005932032],"about_ca_topic_score_codex":0.000054637047,"about_ca_topic_score_gemma":0.00006166474,"teacher_disagreement_score":0.98071533,"about_ca_system_score_codex":0.000085136635,"about_ca_system_score_gemma":0.00033442985,"threshold_uncertainty_score":0.9999793},"labels":[],"label_agreement":null},{"id":"W4206031678","doi":"10.2139/ssrn.3982168","title":"A Characterization of Consideration Functions: When Asymmetric Revealed Preferences Suffice","year":2021,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Characterization (materials science); Mathematical economics; Economics; Econometrics; Mathematics; Microeconomics; Physics","score_opus":0.0728323054005499,"score_gpt":0.33617794020684805,"score_spread":0.26334563480629813,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206031678","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9692652,0.0005586581,0.027763046,0.00067906163,0.00062044914,0.00008289697,0.000012779803,0.000016105834,0.0010017776],"genre_scores_gemma":[0.99572974,0.000785264,0.0003448962,0.00008665965,0.00015241382,0.0000034013176,0.000018775296,0.000010370953,0.0028684938],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9968309,0.0003419092,0.001022711,0.00035056265,0.0007384159,0.0007155236],"domain_scores_gemma":[0.997081,0.0006127258,0.0007837288,0.0003459975,0.0011005343,0.000076060125],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0046790126,0.00013078519,0.0003334522,0.00047945604,0.00024607338,0.00038367748,0.00034841566,0.00010292289,0.00040265598],"category_scores_gemma":[0.0031333412,0.00010442655,0.00016057056,0.0009447342,0.000046773337,0.00065272505,0.00005989559,0.0006983797,0.00015168662],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007088712,0.00019544843,0.010746099,0.000002198377,0.00005679659,0.0000061810456,0.00024121942,0.00004802092,0.012502352,0.00884448,0.0003753873,0.96691096],"study_design_scores_gemma":[0.0005990888,0.0003327249,0.01072085,0.000037904163,0.000062007835,0.00061838765,0.002949888,0.0002860967,0.002055149,0.97754574,0.0045849257,0.00020726288],"about_ca_topic_score_codex":0.00001702196,"about_ca_topic_score_gemma":0.00052933174,"teacher_disagreement_score":0.96870124,"about_ca_system_score_codex":0.00029216136,"about_ca_system_score_gemma":0.0028120906,"threshold_uncertainty_score":0.4988528},"labels":[],"label_agreement":null},{"id":"W4206203128","doi":"10.1007/s00355-020-01285-9","title":"Choice resolutions","year":2020,"lang":"en","type":"article","venue":"Social Choice and Welfare","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Università di Catania","keywords":"Rationalizability; Preorder; Resolution (logic); Independence (probability theory); Path (computing); Order (exchange); Simple (philosophy); Mathematics; Mathematical economics; Computer science; Economics; Discrete mathematics; Artificial intelligence","score_opus":0.2240353870216814,"score_gpt":0.4185354270676562,"score_spread":0.19450004004597476,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206203128","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9190476,0.00016820332,0.0001275353,0.068469405,0.0003116028,0.00009807212,0.00008084693,0.00008520482,0.011611546],"genre_scores_gemma":[0.99664146,0.0000075103903,0.00010360894,0.0021533184,0.0007566864,0.000004980635,0.0000055024743,0.00001101553,0.00031594097],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.998459,0.00007277147,0.0003722809,0.00044338225,0.0004304304,0.000222166],"domain_scores_gemma":[0.9989347,0.00042433647,0.00012857332,0.00018306702,0.00013850973,0.00019083453],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037429723,0.00012095899,0.00024702368,0.000062224826,0.00081972557,0.00034062445,0.00042081837,0.00011846183,0.0006471999],"category_scores_gemma":[0.0019285923,0.0001005355,0.0001219861,0.00047135624,0.00010856014,0.00029021947,0.00018226948,0.0001912274,0.00038682838],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021038008,0.00005788583,0.054116398,0.0000056550557,0.000015073127,0.000008510468,0.0024315675,0.000014383705,0.00011358692,0.005845653,0.101535454,0.8358348],"study_design_scores_gemma":[0.00026799992,0.000044152468,0.11487098,0.0000030784022,0.000015746964,0.0000013448719,0.0015048526,0.00012534541,0.0000056783924,0.010022989,0.8729783,0.00015948236],"about_ca_topic_score_codex":0.00013876212,"about_ca_topic_score_gemma":0.00013971509,"teacher_disagreement_score":0.8356753,"about_ca_system_score_codex":0.000022175787,"about_ca_system_score_gemma":0.00003184392,"threshold_uncertainty_score":0.70863855},"labels":[],"label_agreement":null},{"id":"W4206454672","doi":"10.3390/g13010013","title":"Random Rank-Dependent Expected Utility","year":2022,"lang":"en","type":"article","venue":"Games","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Rank (graph theory); Expected utility hypothesis; Characterization (materials science); Statistical hypothesis testing; Expected value; Mathematics; Computer science; Statistics; Combinatorics; Physics","score_opus":0.1298978114648991,"score_gpt":0.3834981293634477,"score_spread":0.2536003178985486,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206454672","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9886067,0.00022004593,0.00084425893,0.00060675613,0.0016138911,0.00016353794,0.000063946885,0.00009022924,0.0077906377],"genre_scores_gemma":[0.99518514,0.0000048707316,0.00030306165,0.00028638897,0.000062887775,0.00004197995,0.000005041377,0.000010191949,0.0041004643],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9970036,0.0003529274,0.00064033596,0.00057407765,0.0011816698,0.00024739827],"domain_scores_gemma":[0.99771255,0.0010277588,0.00020986423,0.0008427819,0.000105671694,0.00010134414],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0030638878,0.0001272386,0.00034453467,0.00021172935,0.00038016296,0.0002438835,0.001006824,0.0000375927,0.016153658],"category_scores_gemma":[0.0012364958,0.00010001992,0.0002058387,0.000440794,0.000067766225,0.0001628111,0.0005291244,0.00025302463,0.00071510416],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003674106,0.000175235,0.011185961,5.075958e-7,0.000009328425,0.00004292479,0.0007789679,0.0004139461,0.0001892905,0.00009438093,0.040795617,0.94594646],"study_design_scores_gemma":[0.004959962,0.00021482047,0.038187295,0.00000614538,0.000035443583,0.00010119678,0.008672865,0.0036188145,0.00067595474,0.16253448,0.78039515,0.0005978806],"about_ca_topic_score_codex":0.000058879625,"about_ca_topic_score_gemma":0.00002652485,"teacher_disagreement_score":0.94534856,"about_ca_system_score_codex":0.00006903676,"about_ca_system_score_gemma":0.000084354375,"threshold_uncertainty_score":0.9847457},"labels":[],"label_agreement":null},{"id":"W4206516048","doi":"10.31234/osf.io/ynbmr","title":"Push Outcomes Bias Perceptions of Scratch Card Games","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Scratch; Lottery; Feeling; Psychology; Outcome (game theory); Perception; Advertising; Social psychology; Computer science; Business; Economics","score_opus":0.28198388051563716,"score_gpt":0.4537372735496796,"score_spread":0.1717533930340424,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206516048","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9792577,0.000121596604,0.0024464424,0.0013313711,0.0027990884,0.00021307026,0.00016276518,0.000074462616,0.013593488],"genre_scores_gemma":[0.9761758,0.00008589359,0.01084806,0.0003450904,0.00008369971,0.000020174873,0.00003427331,0.000026991143,0.012380009],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99492073,0.0002549501,0.001867928,0.001218131,0.0014338676,0.00030441346],"domain_scores_gemma":[0.9938236,0.0016694221,0.00074955064,0.0025467249,0.0010286398,0.0001821],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002468576,0.00038063855,0.0014161987,0.0005895701,0.0001134494,0.001044728,0.0018636954,0.0004786882,0.0072567924],"category_scores_gemma":[0.0031897665,0.00026775,0.0011520563,0.00044903907,0.0002059485,0.0002286311,0.0023173345,0.00057625916,0.0007422785],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010855041,0.0003090238,0.41785446,0.000015290292,0.000083879444,0.000028389328,0.0012567639,0.002124698,0.00015466032,0.00024115514,0.043702237,0.5342186],"study_design_scores_gemma":[0.000717593,0.00013733664,0.68341535,0.0004024074,0.0003174543,0.000024528343,0.036441043,0.0021046647,0.0006597318,0.25731015,0.016625864,0.0018438912],"about_ca_topic_score_codex":0.00065554737,"about_ca_topic_score_gemma":0.0007604158,"teacher_disagreement_score":0.5323747,"about_ca_system_score_codex":0.000090776775,"about_ca_system_score_gemma":0.0004871011,"threshold_uncertainty_score":0.9999923},"labels":[],"label_agreement":null},{"id":"W4206701330","doi":"10.2196/preprints.32709","title":"Understanding Decision Making in the Adoption of Digital Health Technology: The Role of Behavioural Economics’ Prospect Theory (Preprint)","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Prospect theory; Behavioral economics; Preprint; Irrational number; Nudge theory; Positive economics; Behavioural economics; Health technology; Field (mathematics); Behavioural sciences; Management science; Economics; Psychology; Sociology; Social psychology; Computer science; Health care; Social science; Microeconomics","score_opus":0.23693334573396055,"score_gpt":0.3886242971751964,"score_spread":0.15169095144123587,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206701330","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9744448,0.00047634591,0.020465309,0.00089049444,0.00048934494,0.00085796264,0.00006654957,0.0000346132,0.0022745947],"genre_scores_gemma":[0.99748355,0.00010856057,0.002224715,0.000065515844,0.000025886631,0.000033073557,0.0000122776355,0.000024086565,0.000022323462],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99502933,0.0003544219,0.0024587885,0.0010280961,0.0007583563,0.0003710253],"domain_scores_gemma":[0.99202645,0.0033376517,0.0019984343,0.0023530927,0.00023917182,0.000045223842],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009755944,0.000339541,0.0009627918,0.0008679177,0.00018868146,0.00085251837,0.0029617536,0.0004055848,0.00014635974],"category_scores_gemma":[0.0016928109,0.00019351664,0.00047587443,0.0007937666,0.0004491419,0.00035875442,0.0022978615,0.0009752846,0.000018181423],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001420739,0.00031418676,0.16794033,0.000012728227,0.00002743982,0.0000059981658,0.0032514376,0.006788777,0.000018106663,0.06634369,0.00006149414,0.75509375],"study_design_scores_gemma":[0.00019692584,0.00008563381,0.015519838,0.0004152585,0.000018380804,0.000030215608,0.067453146,0.0019096233,0.000111542926,0.91400045,0.00005958891,0.0001993817],"about_ca_topic_score_codex":0.0000659624,"about_ca_topic_score_gemma":0.0005525004,"teacher_disagreement_score":0.8476568,"about_ca_system_score_codex":0.00054790464,"about_ca_system_score_gemma":0.0005416845,"threshold_uncertainty_score":0.82208544},"labels":[],"label_agreement":null},{"id":"W4206918081","doi":"10.3917/cerpsy.098.0032","title":"L’effet de cadrage","year":2018,"lang":"fr","type":"article","venue":"Cerveau & Psycho","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"World Federation of Science Journalists","funders":"","keywords":"Political science","score_opus":0.1562351327664002,"score_gpt":0.4735114989065195,"score_spread":0.31727636614011934,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206918081","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8464724,0.0028897885,0.0042163185,0.008614375,0.019831933,0.0002267443,0.000111255154,0.00009216159,0.11754506],"genre_scores_gemma":[0.89208657,0.00022847542,0.0051661944,0.0025794446,0.0027235895,0.000011922968,0.000004880166,0.000060663744,0.09713826],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9957964,0.0003274417,0.0010674335,0.0010966182,0.00072460884,0.000987523],"domain_scores_gemma":[0.99619544,0.00080212805,0.00037092037,0.0016727694,0.00039061764,0.0005681473],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0033198835,0.0003802649,0.0005389687,0.00031400388,0.0004472926,0.00087084953,0.0017956637,0.00046952502,0.022489263],"category_scores_gemma":[0.0009179099,0.00034558217,0.00040571528,0.00094633864,0.00089165283,0.0006034723,0.00025690865,0.00044045987,0.039163172],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006435264,0.00022632808,0.004212832,0.000005272559,0.000014263162,0.000048909696,0.0011574791,0.000010502043,0.00013817009,0.0011568908,0.22947237,0.76349264],"study_design_scores_gemma":[0.000587966,0.00040893536,0.011293985,0.00015260444,0.00004361777,0.00011423072,0.0004529671,0.0011254965,0.0003385024,0.15793061,0.82712287,0.00042824555],"about_ca_topic_score_codex":0.0004929928,"about_ca_topic_score_gemma":0.00042510196,"teacher_disagreement_score":0.7630644,"about_ca_system_score_codex":0.00024545958,"about_ca_system_score_gemma":0.00028587974,"threshold_uncertainty_score":0.9998996},"labels":[],"label_agreement":null},{"id":"W4210369397","doi":"10.1109/cdc45484.2021.9683260","title":"Policy-Dependent and Policy-Independent Static Reduction of Stochastic Dynamic Teams and Games and Fragility of Equivalence Properties","year":2021,"lang":"en","type":"article","venue":"2021 60th IEEE Conference on Decision and Control (CDC)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Bijection; Convexity; Reduction (mathematics); Equivalence (formal languages); Computer science; Mathematical optimization; Stochastic control; Control (management); Optimal control; Mathematical economics; Mathematics; Economics; Discrete mathematics; Artificial intelligence","score_opus":0.06531591309574436,"score_gpt":0.3620595027644107,"score_spread":0.2967435896686663,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210369397","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9858656,0.0010290876,0.010824855,0.0013202215,0.00027870742,0.00034493933,0.0001295777,0.000012851968,0.0001941519],"genre_scores_gemma":[0.9979133,0.0010383632,0.00035535387,0.0001203815,0.00004477817,0.000015759266,0.0000017881691,0.000015985914,0.000494283],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9960401,0.00030603787,0.0012289401,0.0010483181,0.0010333849,0.00034323445],"domain_scores_gemma":[0.9964071,0.0012042932,0.0005645964,0.00073674246,0.0007798858,0.00030740644],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0016873614,0.00033522773,0.00096647977,0.0005639775,0.00018152938,0.00041781957,0.00033184994,0.00018523689,0.000105995525],"category_scores_gemma":[0.0034128586,0.00025066664,0.00009283765,0.00040479808,0.0006490142,0.0003571764,0.0002805496,0.0002691371,0.000009296877],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00067097094,0.0001873726,0.00095732807,0.00003577926,0.000035808283,0.000014497615,0.00075519504,0.00023921092,0.02918687,0.0020235504,0.00003183837,0.96586156],"study_design_scores_gemma":[0.013664692,0.003085346,0.09286465,0.0024805556,0.00039706292,0.00080420653,0.021783646,0.12504838,0.011278151,0.72661614,0.00017698538,0.0018001631],"about_ca_topic_score_codex":0.0002715485,"about_ca_topic_score_gemma":0.00018563714,"teacher_disagreement_score":0.96406144,"about_ca_system_score_codex":0.00006837521,"about_ca_system_score_gemma":0.000612653,"threshold_uncertainty_score":0.9999946},"labels":[],"label_agreement":null},{"id":"W4210413809","doi":"10.1080/01462679.2022.2030840","title":"Situating the Problematics of Judgment-Based Deselection: A Heuristics and Biases Approach","year":2022,"lang":"en","type":"article","venue":"Collection Management","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Library of Parliament","funders":"","keywords":"Heuristics; Status quo bias; Endowment effect; Context (archaeology); Endowment; Status quo; Loss aversion; Prospect theory; Computer science; Psychology; Social psychology; Epistemology; Management science; Economics; Political science; Microeconomics; Law","score_opus":0.19657083705203834,"score_gpt":0.3686091870057728,"score_spread":0.17203834995373443,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210413809","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8231535,0.00014562358,0.15433393,0.0010866283,0.00091866025,0.0015885511,0.000021449627,0.00008957647,0.018662106],"genre_scores_gemma":[0.98509294,0.000008130532,0.012324757,0.00015632619,0.000020087042,0.00016713777,0.0000036594538,0.000009475301,0.0022174765],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99800426,0.00021749588,0.00056686107,0.00031318353,0.00076485536,0.00013333595],"domain_scores_gemma":[0.9984118,0.00069915724,0.00036445525,0.000375713,0.00011558608,0.000033335444],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024501004,0.0000981003,0.0001798192,0.00035409498,0.0009653768,0.00019900041,0.00034721795,0.00001813365,0.00018670791],"category_scores_gemma":[0.00040050127,0.00007139411,0.00006772438,0.0015368845,0.00006804461,0.000062688494,0.00031357913,0.00011864442,0.000005966915],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021453634,0.0011107855,0.0068186456,0.000094665156,0.000105735286,0.000010498202,0.0015995423,0.4500359,0.00014154935,0.004376959,0.09929364,0.43619755],"study_design_scores_gemma":[0.001466511,0.00067957136,0.0036138124,0.000042101732,0.00019040678,0.000039481693,0.018054882,0.8726081,0.00024104316,0.058748122,0.043930747,0.00038521644],"about_ca_topic_score_codex":0.000017225426,"about_ca_topic_score_gemma":0.000010731539,"teacher_disagreement_score":0.43581232,"about_ca_system_score_codex":0.000116514966,"about_ca_system_score_gemma":0.000039778555,"threshold_uncertainty_score":0.74249953},"labels":[],"label_agreement":null},{"id":"W4210605159","doi":"10.3389/fpsyt.2021.794014","title":"Changes in Loss Sensitivity During Treatment in Concurrent Disorders Inpatients: A Computational Model Approach to Assessing Risky Decision-Making","year":2022,"lang":"en","type":"article","venue":"Frontiers in Psychiatry","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Provincial Health Services Authority; BC Mental Health & Substance Use Services; University of British Columbia","funders":"Provincial Health Services Authority","keywords":"Context (archaeology); Psychology; Mental health; Clinical psychology; Psychiatry; Medicine","score_opus":0.04142798101269025,"score_gpt":0.3602536963875951,"score_spread":0.31882571537490484,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210605159","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89999664,0.00016296918,0.09316145,0.0003716027,0.0053611416,0.0005473136,0.00008482481,0.000024666631,0.00028941012],"genre_scores_gemma":[0.8732491,0.00001058553,0.12634744,0.00016708982,0.00003218632,0.00014040437,0.000013558557,0.000025097554,0.000014534204],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99590784,0.00042542306,0.0010235974,0.0010961888,0.0010302548,0.00051667745],"domain_scores_gemma":[0.9986001,0.0004434507,0.00032557952,0.0004690595,0.0000480375,0.000113736096],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0020470372,0.0003046724,0.00062664325,0.0020424707,0.0003022809,0.00023085043,0.0005297063,0.00009164923,0.000022396613],"category_scores_gemma":[0.0002910002,0.00029599652,0.00013496472,0.0018181002,0.000068149646,0.0003785423,0.00041940546,0.00041571108,0.000007804105],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008940022,0.00069282664,0.3468475,0.000002328255,0.000003465648,0.000008466409,0.0011492398,0.45781764,5.9967374e-7,0.000037366135,0.00043639392,0.19291477],"study_design_scores_gemma":[0.0017330503,0.000095328825,0.2033036,0.00010674231,0.0000066381212,0.000010756883,0.0074821804,0.69424576,4.901972e-7,0.09241906,0.00022337252,0.00037300668],"about_ca_topic_score_codex":0.00009767851,"about_ca_topic_score_gemma":0.0021638472,"teacher_disagreement_score":0.23642813,"about_ca_system_score_codex":0.0013631429,"about_ca_system_score_gemma":0.0002766984,"threshold_uncertainty_score":0.9999492},"labels":[],"label_agreement":null},{"id":"W4210901269","doi":"10.1037/xge0001179","title":"Logical intuition is not really about logic.","year":2022,"lang":"en","type":"article","venue":"Journal of Experimental Psychology General","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":39,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Macquarie University","keywords":"Intuition; Logical consequence; Indeterminate; Logical conjunction; Psychology; Logical form; Logical reasoning; Probabilistic logic; Epistemology; Inference; Modus ponens; Cognitive psychology; Computer science; Artificial intelligence; Cognitive science; Mathematics; Philosophy","score_opus":0.248374088983785,"score_gpt":0.5042549891909857,"score_spread":0.25588090020720067,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210901269","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9855469,0.0006331507,0.00075192406,0.0026165089,0.0040232567,0.00007749734,0.000028519215,0.00001197512,0.0063102725],"genre_scores_gemma":[0.9814085,0.000028632438,0.003673289,0.01372457,0.00046629863,0.000008156236,0.000003118508,0.000014024395,0.00067341106],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9962718,0.0005051017,0.00140959,0.00045697225,0.0010670808,0.0002894647],"domain_scores_gemma":[0.998009,0.0002115287,0.0009711474,0.00045246637,0.00017590102,0.00017991151],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0029502027,0.00017990715,0.000476841,0.0004118186,0.00037597114,0.000137282,0.001220106,0.00011337822,0.010948862],"category_scores_gemma":[0.00017601936,0.00013545949,0.0003942114,0.00031759046,0.00016699293,0.000274252,0.00033221793,0.0006467775,0.00021356819],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0023280287,0.0023021642,0.0032496306,6.3831055e-7,0.00006300049,0.00071257184,0.001851021,0.00077399664,0.27108073,0.0027197255,0.53293407,0.1819844],"study_design_scores_gemma":[0.008457921,0.016675083,0.026025096,0.000022091352,0.00006810795,0.011996749,0.0067684385,0.00082153594,0.034130763,0.36046034,0.53331894,0.0012549413],"about_ca_topic_score_codex":0.0000056879585,"about_ca_topic_score_gemma":7.721701e-7,"teacher_disagreement_score":0.3577406,"about_ca_system_score_codex":0.0001803299,"about_ca_system_score_gemma":0.000063653846,"threshold_uncertainty_score":0.98995525},"labels":[],"label_agreement":null},{"id":"W4211127273","doi":"10.31219/osf.io/wtupm","title":"Logical Intuition Is Not Really About Logic","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Macquarie University","keywords":"Intuition; Logical consequence; Logical conjunction; Logical analysis; Indeterminate; Non-classical logic; Modus ponens; Logical form; Logical reasoning; Probabilistic logic; Psychology; Inference; Epistemology; Computer science; Cognitive psychology; Mathematics; Artificial intelligence; Cognitive science; Philosophy","score_opus":0.3269425148933434,"score_gpt":0.4567912874123577,"score_spread":0.12984877251901428,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4211127273","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8801618,0.00020510785,0.039415862,0.0040555596,0.0037782763,0.0003233974,0.00013102562,0.00019777114,0.071731165],"genre_scores_gemma":[0.9736923,0.00024206188,0.013450499,0.006259099,0.00030390732,0.000027112595,0.00007392269,0.000024923262,0.0059261834],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9941026,0.00026274583,0.0017126127,0.0019373138,0.0015831029,0.00040160364],"domain_scores_gemma":[0.9949908,0.0011169212,0.00068849954,0.0021278919,0.00083267066,0.00024321812],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0031063608,0.0004243224,0.0009768618,0.00037657758,0.00016318854,0.002524924,0.002026169,0.00091503887,0.021215241],"category_scores_gemma":[0.002411828,0.00029451714,0.0006932613,0.00037718756,0.00016017843,0.00024532247,0.002990473,0.0009826352,0.003533494],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000052563308,0.0002513161,0.0007763948,0.000010505891,0.000021359316,0.00017077598,0.00034580147,0.0006240403,0.000119372504,0.002991615,0.05264315,0.9419931],"study_design_scores_gemma":[0.00029745637,0.00012686441,0.008657737,0.00016157047,0.00005147623,0.000056206958,0.0007282979,0.0030456078,0.00052452146,0.9397267,0.04575775,0.0008658135],"about_ca_topic_score_codex":0.00015348606,"about_ca_topic_score_gemma":0.00012824741,"teacher_disagreement_score":0.9411273,"about_ca_system_score_codex":0.00016388869,"about_ca_system_score_gemma":0.0003439856,"threshold_uncertainty_score":0.9999507},"labels":[],"label_agreement":null},{"id":"W4211165067","doi":"10.1177/1745691612454303","title":"Hindsight Bias","year":2012,"lang":"en","type":"article","venue":"Perspectives on Psychological Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":445,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"National Science Foundation","keywords":"Hindsight bias; Overconfidence effect; Psychology; Debiasing; Cognitive bias; Recall; Cognitive psychology; Intervention (counseling); Sensemaking; Meaning (existential); Neglect; Social psychology; Philosophy of science; Cognition; Epistemology; Computer science","score_opus":0.39829618382886645,"score_gpt":0.5334642844091555,"score_spread":0.13516810058028905,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4211165067","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87779826,0.00012968127,0.0004919556,0.0011614838,0.0017858575,0.00010548076,0.00000496765,0.00007782304,0.11844449],"genre_scores_gemma":[0.99627733,0.000016947282,0.001914447,0.0007582638,0.00023411665,0.000008053677,1.6948036e-7,0.0000064606766,0.0007842279],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9956135,0.00015273975,0.00046999933,0.0012779436,0.0017353921,0.0007503812],"domain_scores_gemma":[0.99671733,0.0011427731,0.0002090886,0.0011410101,0.00027339067,0.0005164043],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00793758,0.00019351502,0.0002762601,0.00044387457,0.0005181455,0.00054845074,0.0022238584,0.000098814555,0.0026765848],"category_scores_gemma":[0.007992332,0.00011043543,0.00016257778,0.0022383989,0.0014320317,0.0010065963,0.00023208016,0.00029858173,0.00649738],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001216793,0.0025624405,0.039746698,2.4321264e-7,0.0000036664326,0.000012092856,0.0054166606,0.000038802245,0.0026647018,0.0672933,0.011585009,0.8705547],"study_design_scores_gemma":[0.0004835907,0.0008859081,0.7531896,0.000013098311,0.0000071965956,0.00007543773,0.012303343,0.0001567683,0.0005981514,0.17459825,0.057045344,0.00064328406],"about_ca_topic_score_codex":0.0000047344624,"about_ca_topic_score_gemma":9.0071086e-7,"teacher_disagreement_score":0.86991143,"about_ca_system_score_codex":0.0001810297,"about_ca_system_score_gemma":0.000029272578,"threshold_uncertainty_score":0.9982351},"labels":[],"label_agreement":null},{"id":"W4214526237","doi":"10.55365/1923.x2020.18.03","title":"Cross-Cultural Differences in the Perception of Portfolio Risk","year":2020,"lang":"en","type":"article","venue":"Review of Economics and Finance","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Portfolio; Risk perception; Perception; Asset allocation; Perspective (graphical); Asset (computer security); Cross-cultural; Investment (military); Actuarial science; Economics; Financial economics; Psychology; Sociology; Political science; Computer science; Politics","score_opus":0.1461150940702534,"score_gpt":0.39301324695927325,"score_spread":0.24689815288901987,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4214526237","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98733145,0.010960417,0.000012035323,0.00071433577,0.000061637016,0.00012149895,0.00004969676,0.0000013050839,0.0007476543],"genre_scores_gemma":[0.7462779,0.25316405,0.00019382435,0.0003258011,0.000019751593,0.0000029895803,0.0000011666777,0.0000019448585,0.000012526731],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9986384,0.00006005335,0.0008812466,0.00025684087,0.00007995759,0.00008353673],"domain_scores_gemma":[0.99869466,0.00026889902,0.0006803909,0.00025139225,0.00008478899,0.000019889481],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014312272,0.00008546048,0.00047853836,0.000031429943,0.00003873757,0.00007322384,0.00046657855,0.000036281763,0.000082210434],"category_scores_gemma":[0.00065585616,0.000049166625,0.00012130587,0.00016705735,0.00015451177,0.00023713379,0.000064085245,0.00008735452,0.000019080948],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012591254,0.000026709395,0.08849259,0.00008681285,0.0000023659177,6.6663614e-7,0.00036636175,0.0000548572,0.000004983413,0.0025776336,0.0005114792,0.90786296],"study_design_scores_gemma":[0.00040865663,0.00025922238,0.8596867,0.0010518846,0.000031709213,0.0000109426355,0.000753156,0.0056538987,0.000015522763,0.034851316,0.097008616,0.00026839483],"about_ca_topic_score_codex":0.000033972618,"about_ca_topic_score_gemma":0.000010186256,"teacher_disagreement_score":0.90759456,"about_ca_system_score_codex":0.000007634422,"about_ca_system_score_gemma":0.000024235846,"threshold_uncertainty_score":0.20049568},"labels":[],"label_agreement":null},{"id":"W4214741076","doi":"10.1177/01461672221077791","title":"Anxiety, Cognitive Availability, and the Talisman Effect of Insurance","year":2022,"lang":"en","type":"article","venue":"Personality and Social Psychology Bulletin","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brock University","funders":"","keywords":"Psychology; Anxiety; Cognition; Social psychology; Clinical psychology; Psychiatry","score_opus":0.07057242817275633,"score_gpt":0.4006610758127681,"score_spread":0.3300886476400118,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4214741076","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9797904,0.0003469484,0.000013466839,0.01631031,0.0002708037,0.00022754924,0.00018129616,0.000010928594,0.0028483002],"genre_scores_gemma":[0.99749297,0.00003303315,0.000014520323,0.0021460927,0.000056682715,0.000036861104,0.000004097096,0.0000059341546,0.00020982361],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99649996,0.0019545653,0.0004404315,0.000502405,0.00043392842,0.00016873151],"domain_scores_gemma":[0.99640846,0.0030145703,0.00026081252,0.00019116103,0.00008551213,0.000039482693],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.009050584,0.00012503842,0.00047450553,0.00005494386,0.00080040016,0.00006563453,0.00035176115,0.000083753745,0.001773214],"category_scores_gemma":[0.00083273306,0.00008371539,0.00015273427,0.00017565845,0.001789408,0.000031940664,0.00032902582,0.00033744492,0.00003505389],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005314616,0.0002933857,0.41958535,0.000021479967,0.0000744263,0.000007921269,0.018958492,0.0000018847093,0.000051927702,0.0028727495,0.023323204,0.5294946],"study_design_scores_gemma":[0.007469348,0.0006844181,0.77751446,0.000009432893,0.000090248286,0.000115709976,0.006934121,0.000029080335,0.000017331447,0.087145776,0.11964337,0.00034673224],"about_ca_topic_score_codex":0.00013866702,"about_ca_topic_score_gemma":0.000018709396,"teacher_disagreement_score":0.5291478,"about_ca_system_score_codex":0.000013589368,"about_ca_system_score_gemma":0.000014653039,"threshold_uncertainty_score":0.9991393},"labels":[],"label_agreement":null},{"id":"W4220685513","doi":"10.1016/j.cognition.2022.105107","title":"Information about task progress modulates cognitive demand avoidance","year":2022,"lang":"en","type":"article","venue":"Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":25,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"Psychology; Task (project management); Cognition; Cognitive psychology; Variety (cybernetics); Action (physics); Computer science; Neuroscience","score_opus":0.06068563833822345,"score_gpt":0.3580696607402074,"score_spread":0.29738402240198397,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220685513","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9895573,0.00016869587,0.003922389,0.000225077,0.00053798215,0.00034159995,0.00029865606,0.00008022729,0.0048680194],"genre_scores_gemma":[0.99871856,0.000009070676,0.00017741395,0.0005318716,0.000048390477,0.00015512454,0.00019903386,0.00000877141,0.00015178845],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9978506,0.00017658413,0.0006209872,0.00026957414,0.00086651446,0.00021573382],"domain_scores_gemma":[0.9982867,0.00051549677,0.00041730286,0.00022853634,0.0004729587,0.00007898134],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0015959748,0.00013100344,0.00019670108,0.00031717715,0.0006382218,0.00045939736,0.00035164348,0.000050721945,0.0009955664],"category_scores_gemma":[0.00089568045,0.00011881188,0.00009649704,0.0005517644,0.000109627625,0.0013268449,0.00023333897,0.00021311978,0.0012384402],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001239305,0.00009788191,0.002629404,0.0000030096917,0.0000082686865,0.000006158976,0.0009933681,0.00033792385,0.00007029633,0.00010496156,0.0025301226,0.9930947],"study_design_scores_gemma":[0.0052272966,0.0012241901,0.114531025,0.000250559,0.00023758349,0.0002698681,0.022407606,0.03529737,0.0049208407,0.6423744,0.17154872,0.0017105266],"about_ca_topic_score_codex":0.0000028525972,"about_ca_topic_score_gemma":0.000003509921,"teacher_disagreement_score":0.99138415,"about_ca_system_score_codex":0.00006298507,"about_ca_system_score_gemma":0.000058977475,"threshold_uncertainty_score":0.9999177},"labels":[],"label_agreement":null},{"id":"W4220750995","doi":"10.1002/bdm.2280","title":"Information‐seeking when information doesn't matter","year":2022,"lang":"en","type":"article","venue":"Journal of Behavioral Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Outcome (game theory); Portfolio; Certainty; Action (physics); Psychology; Instrumental variable; Economics; Actuarial science; Microeconomics; Finance; Econometrics","score_opus":0.06879234510743981,"score_gpt":0.3845880225931744,"score_spread":0.31579567748573456,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220750995","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95093215,0.000052183943,0.04245535,0.00051897974,0.0042752237,0.00020456807,0.000074686875,0.000029485687,0.001457378],"genre_scores_gemma":[0.97722656,0.0000041325284,0.020486519,0.0019991482,0.00014088397,0.000010067993,0.000006215738,0.000018754541,0.000107712294],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99083084,0.0002801255,0.004082189,0.00021622161,0.00416108,0.00042956937],"domain_scores_gemma":[0.99264747,0.0012262323,0.0038448556,0.00079083204,0.0012827722,0.00020782309],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0071700956,0.00029514433,0.00069446623,0.0024530306,0.0007965349,0.0018593883,0.0022549576,0.00012533998,0.010631663],"category_scores_gemma":[0.0010104725,0.00023163547,0.000584885,0.0010330768,0.00006809542,0.008702168,0.0010586074,0.0009223677,0.0015474465],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033180384,0.00011103992,0.017907742,0.0000017968661,0.0000076237484,0.000037016413,0.0026252398,0.00509273,0.000045519555,0.000060904997,0.06502555,0.90875304],"study_design_scores_gemma":[0.0025674116,0.0010312385,0.050225276,0.00022029967,0.00015603704,0.0025296798,0.01883617,0.0027825008,0.000045744608,0.23867439,0.68198794,0.0009433099],"about_ca_topic_score_codex":0.00001897346,"about_ca_topic_score_gemma":0.0000052978125,"teacher_disagreement_score":0.90780973,"about_ca_system_score_codex":0.0005016725,"about_ca_system_score_gemma":0.00024255562,"threshold_uncertainty_score":0.99922997},"labels":[],"label_agreement":null},{"id":"W4220956819","doi":"10.1098/rsos.211977","title":"Trivially informative semantic context inflates people's confidence they can perform a highly complex skill","year":2022,"lang":"en","type":"article","venue":"Royal Society Open Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kwantlen Polytechnic University","funders":"","keywords":"Overconfidence effect; Context (archaeology); Feeling; Metacognition; Psychology; Social psychology; Cognitive psychology; Fluency; Persuasion; Metamemory; Computer science; Cognition; Mathematics education; History","score_opus":0.08228390346554458,"score_gpt":0.37672688774804086,"score_spread":0.29444298428249627,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220956819","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9849729,0.00002071278,0.00031476733,0.0026716467,0.00088950637,0.00079930987,0.00012158438,0.00006124208,0.010148363],"genre_scores_gemma":[0.9934872,0.000007782858,0.0013880662,0.0027493758,0.00003849021,0.00008031052,0.000009847379,0.00001591876,0.002223041],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9933068,0.00019149938,0.0012671171,0.0011518415,0.0032326025,0.00085010426],"domain_scores_gemma":[0.99511546,0.001574985,0.0008373367,0.0012591842,0.00081859546,0.0003944366],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.012567129,0.00033071413,0.0007251227,0.00019364449,0.0045481524,0.0037973907,0.010598863,0.00007312117,0.0023601742],"category_scores_gemma":[0.0016932965,0.00025921743,0.0003494984,0.002086496,0.001221428,0.001905535,0.0069758785,0.0005626964,0.0005363289],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002632607,0.0006468469,0.076700166,0.000015492506,0.00006999093,0.00003128363,0.2101214,0.022743609,0.0009567312,0.013976871,0.10353171,0.57094264],"study_design_scores_gemma":[0.0036350172,0.0014474486,0.24387278,0.00008432654,0.000069876754,0.00013865279,0.22346425,0.3393258,0.00042187166,0.10605487,0.0792403,0.0022448176],"about_ca_topic_score_codex":0.0048607932,"about_ca_topic_score_gemma":0.0027657507,"teacher_disagreement_score":0.5686978,"about_ca_system_score_codex":0.00061400526,"about_ca_system_score_gemma":0.0018233686,"threshold_uncertainty_score":0.999986},"labels":[],"label_agreement":null},{"id":"W4221054841","doi":"10.1111/caje.12572","title":"Present bias and externalities: Can government intervention raise welfare?","year":2022,"lang":"en","type":"article","venue":"Canadian Journal of Economics/Revue canadienne d économique","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Economic and Social Research Council","keywords":"Externality; Economics; Economic interventionism; Welfare; Intervention (counseling); Government (linguistics); Context (archaeology); Public economics; Microeconomics; Market failure; Market economy; Political science","score_opus":0.337604643441556,"score_gpt":0.2732559769974578,"score_spread":0.0643486664440982,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4221054841","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9879172,0.00032202288,0.00004332867,0.0067682965,0.0030023018,0.00021521842,0.00087577413,0.000005004745,0.00085087196],"genre_scores_gemma":[0.99717975,0.000035030163,0.00017560017,0.0004947181,0.000340489,0.000024278828,0.0000067546302,0.000039757437,0.00170365],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9965966,0.0002927311,0.0018679999,0.0005700492,0.000028155438,0.0006444675],"domain_scores_gemma":[0.99526954,0.00051658106,0.0015624011,0.00064894435,0.0001932511,0.0018093013],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0044158935,0.0002859588,0.00072247715,0.0007628502,0.0005948824,0.00064419926,0.0013396207,0.00009375101,0.0025117958],"category_scores_gemma":[0.00084793015,0.00030856061,0.0003986525,0.00018363995,0.00018279067,0.0005184887,0.00019693155,0.00048427953,0.000014467512],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000411617,0.00012251874,0.0625716,0.00002716313,0.00026622083,0.0010704864,0.00694372,0.034094162,0.000013799825,0.19782783,0.01030518,0.6863457],"study_design_scores_gemma":[0.0013314714,0.00089653715,0.004877062,0.000057425423,0.000057653353,0.0019286423,0.011960077,0.0029445246,0.00004055052,0.44391587,0.5313812,0.00060900016],"about_ca_topic_score_codex":0.12315575,"about_ca_topic_score_gemma":0.9024653,"teacher_disagreement_score":0.7793095,"about_ca_system_score_codex":0.003900053,"about_ca_system_score_gemma":0.0010122311,"threshold_uncertainty_score":0.99993664},"labels":[],"label_agreement":null},{"id":"W4225545418","doi":"10.1007/s10899-021-10103-5","title":"Using Icon Arrays to Communicate Gambling Information Reduces the Appeal of Scratch Card Games","year":2022,"lang":"en","type":"article","venue":"Journal of Gambling Studies","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Icon; Appeal; Salience (neuroscience); Psychology; Scratch; Perception; Feeling; Social psychology; Internet privacy; Computer science; Advertising; Cognitive psychology","score_opus":0.409108575537668,"score_gpt":0.496902943627795,"score_spread":0.08779436809012703,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4225545418","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9928988,0.0014339207,0.0010245929,0.0028663902,0.0014037826,0.000118610034,0.000013318198,0.0000084406765,0.00023214647],"genre_scores_gemma":[0.9943402,0.0002397934,0.0048692324,0.00038046887,0.0001267194,0.0000033923266,4.190479e-7,0.0000087347735,0.000031065323],"study_design_codex":"design_other","study_design_gemma":"qualitative","domain_scores_codex":[0.99593824,0.0003468113,0.0019167574,0.00014523686,0.0014276155,0.00022533277],"domain_scores_gemma":[0.9944726,0.0015647629,0.0021111486,0.0004999659,0.0012805029,0.00007102562],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009562704,0.00015361329,0.00066278264,0.0007200648,0.00084800523,0.00028443645,0.0014236307,0.000031779833,0.00002111838],"category_scores_gemma":[0.0030770695,0.00009549337,0.00028402163,0.00094811514,0.00015284214,0.0007714053,0.000896783,0.00046162657,0.000009888458],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00066223356,0.0002022119,0.006237972,0.00002097708,0.0004161443,0.000019201689,0.054672364,0.3257074,0.00846648,0.00026922065,0.019671964,0.5836538],"study_design_scores_gemma":[0.0026785056,0.0024667077,0.004544993,0.0010029998,0.00058166013,0.00053159974,0.7763829,0.014725147,0.011706341,0.07068292,0.11357412,0.0011221076],"about_ca_topic_score_codex":0.000031464064,"about_ca_topic_score_gemma":0.0000091998945,"teacher_disagreement_score":0.72171056,"about_ca_system_score_codex":0.00017022199,"about_ca_system_score_gemma":0.00015543586,"threshold_uncertainty_score":0.6522256},"labels":[],"label_agreement":null},{"id":"W4225620916","doi":"10.1007/s10614-022-10252-8","title":"The Slicing Method: Determining Insensitivity Regions of Probability Weighting Functions","year":2022,"lang":"en","type":"article","venue":"Computational Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"CHIST-ERA; Xunta de Galicia; Natural Sciences and Engineering Research Council of Canada; Mitacs; Agencia Nacional de Investigación e Innovación","keywords":"Weighting; Heuristic; Rule of thumb; Computer science; Subadditivity; Slicing; Mathematical optimization; Class (philosophy); Mathematics; Algorithm; Artificial intelligence","score_opus":0.17850966088803258,"score_gpt":0.3926388063783125,"score_spread":0.21412914549027992,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4225620916","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9096734,0.000015585887,0.087038025,0.0009498891,0.0007899997,0.00015046443,0.00007286635,0.000025854102,0.0012839156],"genre_scores_gemma":[0.9677387,0.0000017470305,0.031806756,0.00017474708,0.00005999502,0.000023300305,0.0000120306795,0.000012037903,0.00017071907],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99751294,0.00044334686,0.0010542335,0.0004775122,0.00031126072,0.000200702],"domain_scores_gemma":[0.988294,0.010119603,0.00075728085,0.00050545443,0.00025369666,0.0000699812],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.005850664,0.00012241123,0.00029590252,0.00018438676,0.0016179468,0.0002008334,0.0005974031,0.000033872857,0.000085348605],"category_scores_gemma":[0.0013603185,0.00010163596,0.00020672483,0.00035666244,0.0001496879,0.00022354156,0.00054327765,0.0002475212,0.00003231233],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019735176,0.00004354103,0.0033207003,7.460205e-7,0.00001081562,0.0000012049472,0.0002583331,0.6830185,0.00000972158,0.012530852,0.00053271063,0.30025312],"study_design_scores_gemma":[0.00015719816,0.00005136376,0.00673383,0.000002940606,0.000010350652,0.000059938197,0.0011313959,0.42685193,0.00001294296,0.5513465,0.013522895,0.000118728014],"about_ca_topic_score_codex":0.000027829346,"about_ca_topic_score_gemma":0.00007860422,"teacher_disagreement_score":0.5388156,"about_ca_system_score_codex":0.00022546995,"about_ca_system_score_gemma":0.00030196592,"threshold_uncertainty_score":0.99968183},"labels":[],"label_agreement":null},{"id":"W4225620988","doi":"10.1007/s10899-022-10125-7","title":"Push Outcomes Bias Perceptions of Scratch Card Games","year":2022,"lang":"en","type":"article","venue":"Journal of Gambling Studies","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Scratch; Lottery; Psychology; Feeling; Social psychology; Outcome (game theory); Perception; Odds; Propensity score matching; Advertising; Computer science; Medicine; Business; Economics","score_opus":0.37481589475820437,"score_gpt":0.5004427257893715,"score_spread":0.12562683103116717,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4225620988","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9932527,0.0016549268,0.00013671897,0.002441442,0.0021484501,0.000055102664,0.00002618011,0.000009385572,0.000275094],"genre_scores_gemma":[0.9965137,0.00030092493,0.001893116,0.00021533994,0.0001188816,0.0000033117894,2.5447835e-7,0.000011135123,0.00094330206],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9961285,0.00023904903,0.0016644181,0.0002204353,0.0015521309,0.00019544749],"domain_scores_gemma":[0.9946799,0.0022398236,0.001481001,0.00036398313,0.0011606036,0.00007466547],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00554798,0.00014840777,0.00091065466,0.0007635672,0.00044252857,0.00011519019,0.00080591656,0.000031496525,0.00026748964],"category_scores_gemma":[0.0049053505,0.00009857895,0.00056346983,0.0006427352,0.00016181594,0.00029031205,0.0004700138,0.00035237466,0.000025314253],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012348966,0.00037729667,0.6380556,0.00000814753,0.00038420816,0.00008076815,0.008959968,0.009946707,0.00059413153,0.00013845543,0.07799445,0.26333678],"study_design_scores_gemma":[0.002495592,0.0023207415,0.39126274,0.00021247847,0.0005377706,0.00038236598,0.37304124,0.00037689976,0.00029635805,0.15537177,0.07291036,0.0007916847],"about_ca_topic_score_codex":0.000013170811,"about_ca_topic_score_gemma":0.000019679113,"teacher_disagreement_score":0.36408126,"about_ca_system_score_codex":0.00013057282,"about_ca_system_score_gemma":0.00012774034,"threshold_uncertainty_score":0.58725166},"labels":[],"label_agreement":null},{"id":"W4226269705","doi":"10.22215/etd/2022-14861","title":"Anchoring in Time Estimation: The Effects of Explicit Anchoring on Prospective Time Estimates","year":2022,"lang":"en","type":"dissertation","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Anchoring; Replicate; Duration (music); Psychology; Statistics; Social psychology; Mathematics","score_opus":0.03386917435593306,"score_gpt":0.3715369848990984,"score_spread":0.33766781054316536,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4226269705","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9787429,0.0001969842,0.000043786054,0.000039868642,0.0011182164,0.0008749311,0.000014672543,0.00006564791,0.018902987],"genre_scores_gemma":[0.974317,0.000018124683,0.0013519322,0.00004897404,0.00014829921,0.0003355835,0.00010284244,0.000067467125,0.023609761],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99602914,0.00014257884,0.0011509751,0.00087863416,0.0014878679,0.00031083176],"domain_scores_gemma":[0.9923639,0.005696201,0.00077094615,0.0009309303,0.00017247921,0.00006551056],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002004374,0.0003769487,0.0007997022,0.00070538453,0.00026274117,0.00035493725,0.0014535758,0.00018511967,0.002046689],"category_scores_gemma":[0.0035676218,0.0002544557,0.00023141177,0.0009586298,0.00003822979,0.00032613086,0.0001772749,0.00055585825,0.000973892],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00065098994,0.00073032646,0.007338243,0.00009516991,0.00007913361,0.00007806006,0.0058807936,0.012709382,0.0036891513,0.0017265469,0.013387571,0.9536346],"study_design_scores_gemma":[0.0046997913,0.004162905,0.2044481,0.004024184,0.00048308756,0.00003157611,0.00881584,0.1653728,0.10183887,0.49796295,0.003907203,0.0042526736],"about_ca_topic_score_codex":0.00007061272,"about_ca_topic_score_gemma":0.000039992843,"teacher_disagreement_score":0.94938195,"about_ca_system_score_codex":0.00026957106,"about_ca_system_score_gemma":0.000116766656,"threshold_uncertainty_score":0.99999076},"labels":[],"label_agreement":null},{"id":"W4230091828","doi":"10.31234/osf.io/xugaz","title":"Risky-choice framing and rational decision-making","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Framing (construction); Framing effect; Narrative; Epistemology; Empirical research; Prospect theory; Psychology; Management science; Positive economics; Social psychology; Economics; Microeconomics; Philosophy","score_opus":0.11670704486615605,"score_gpt":0.4287130858463343,"score_spread":0.31200604098017826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4230091828","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91748506,0.0007334547,0.07151386,0.0003563021,0.003011205,0.00022866618,0.000048420243,0.0000904442,0.006532603],"genre_scores_gemma":[0.9019166,0.00008082127,0.09634211,0.00055881374,0.00035872788,0.000018229863,0.000014391821,0.00003474455,0.00067552],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99388254,0.0002143517,0.0017194614,0.001956663,0.0018361687,0.0003908119],"domain_scores_gemma":[0.98079014,0.015734242,0.0007592788,0.0016716149,0.0008179336,0.00022677174],"candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0034254561,0.00046314107,0.0009155555,0.0006177851,0.0004020772,0.0043877796,0.0014267205,0.0006273848,0.0039550113],"category_scores_gemma":[0.01862446,0.00037188336,0.00037517585,0.000450137,0.00015459384,0.0005303672,0.0038872052,0.0009935995,0.00031919606],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017427185,0.000062112726,0.012344987,0.000005533353,0.000020835654,0.000048786264,0.00025117013,0.002745457,0.000020514903,0.00024526424,0.004863715,0.9793742],"study_design_scores_gemma":[0.0004849289,0.000048758742,0.060059026,0.000905962,0.00009322004,0.00010876834,0.002218564,0.041641336,0.00005564577,0.8631723,0.029901942,0.0013095296],"about_ca_topic_score_codex":0.000106841006,"about_ca_topic_score_gemma":0.0005024153,"teacher_disagreement_score":0.97806466,"about_ca_system_score_codex":0.0001236016,"about_ca_system_score_gemma":0.00047362398,"threshold_uncertainty_score":0.99987334},"labels":[],"label_agreement":null},{"id":"W4230460414","doi":"10.31234/osf.io/ja3p6","title":"Plans or Outcomes: How do we attribute intelligence to others?","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Companhia Brasileira de Metalurgia e Mineração; National Science Foundation","keywords":"Attribution; Outcome (game theory); Planner; Task (project management); Psychology; Human intelligence; Quality (philosophy); Key (lock); Cognitive psychology; Artificial intelligence; Social psychology; Computer science; Applied psychology","score_opus":0.3732261221806011,"score_gpt":0.46503834505788605,"score_spread":0.09181222287728497,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4230460414","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6853811,0.00024872553,0.27485788,0.027768109,0.0071974318,0.0007974845,0.0006427951,0.00023895074,0.002867547],"genre_scores_gemma":[0.91718346,0.00031061118,0.032631926,0.0021376503,0.000220677,0.000073883115,0.000025083236,0.00007123995,0.0473455],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9941955,0.00019947554,0.0013674226,0.0020908897,0.0015866797,0.00056002365],"domain_scores_gemma":[0.9924438,0.0028637194,0.00052974996,0.0031015743,0.0006004856,0.0004606472],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0028097075,0.00058268814,0.0013543351,0.00064111134,0.00015377863,0.004514871,0.003811149,0.00055378705,0.009251233],"category_scores_gemma":[0.004870667,0.00035605126,0.0006316798,0.00080198166,0.000091782895,0.00028683763,0.0035825216,0.0007536757,0.0034697796],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000053855263,0.00014084605,0.009761465,0.000009617624,0.000049146056,0.00018800452,0.0011977631,0.0028070877,0.000010055857,0.00024330539,0.032826368,0.9527125],"study_design_scores_gemma":[0.00043799108,0.00048418003,0.0068520424,0.0013998545,0.00018114943,0.00013458332,0.05763317,0.0023915805,0.0018989797,0.19419235,0.73039204,0.004002096],"about_ca_topic_score_codex":0.00012450022,"about_ca_topic_score_gemma":0.0014921421,"teacher_disagreement_score":0.9487104,"about_ca_system_score_codex":0.00020528997,"about_ca_system_score_gemma":0.0004902012,"threshold_uncertainty_score":0.99988914},"labels":[],"label_agreement":null},{"id":"W4232149942","doi":"10.1007/978-3-319-19650-3_628","title":"Judgment and Decision-Making","year":2021,"lang":"en","type":"book-chapter","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Psychology; Computer science","score_opus":0.12860954690620185,"score_gpt":0.3861719165396077,"score_spread":0.25756236963340584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4232149942","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011945833,0.0014439785,0.005247515,0.00027277897,0.0018522561,0.00021872477,0.000041930816,0.00007767358,0.9788993],"genre_scores_gemma":[0.03865138,0.0005068833,0.048977077,0.0013813652,0.00036388353,0.000006212442,0.00000648414,0.000106842024,0.90999985],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.995243,0.00002225332,0.0014210099,0.0014451683,0.0015673507,0.00030122034],"domain_scores_gemma":[0.992772,0.004588608,0.00053603196,0.0014633941,0.00042104037,0.00021892166],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0017062527,0.0004687645,0.00094927766,0.00055790466,0.00021713026,0.0012125765,0.0008785453,0.000498454,0.018166816],"category_scores_gemma":[0.0013061499,0.0003488832,0.00037602964,0.000095096635,0.0001540761,0.00022122546,0.0010306725,0.0004340835,0.0020899584],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014702199,0.000012514756,0.00003068333,0.0000014357059,0.00001523666,0.00013315967,0.000023581928,0.000021223019,0.0000019190938,0.038552847,0.022909584,0.9382831],"study_design_scores_gemma":[0.00009973468,0.00003209233,0.000038675862,0.00023834179,0.000027320002,0.00006382635,0.000059673395,0.00012920427,0.0000022776997,0.60248065,0.39651328,0.00031493054],"about_ca_topic_score_codex":0.0000044423873,"about_ca_topic_score_gemma":0.00007823443,"teacher_disagreement_score":0.9379682,"about_ca_system_score_codex":0.00011121149,"about_ca_system_score_gemma":0.00016785055,"threshold_uncertainty_score":0.9998963},"labels":[],"label_agreement":null},{"id":"W4232396141","doi":"10.1007/978-3-642-27772-6_36-2","title":"Behavioral Economics","year":2013,"lang":"en","type":"book-chapter","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Economics; Psychology","score_opus":0.25913948660727326,"score_gpt":0.3978045030057434,"score_spread":0.13866501639847012,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4232396141","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.028435556,0.00007908429,0.00009789404,0.00025865276,0.0019840314,0.00027969253,0.000106047155,0.00010389904,0.96865517],"genre_scores_gemma":[0.010992809,0.000093496084,0.002008771,0.0004156317,0.00032020258,0.0000091649845,0.000025522504,0.00009163711,0.98604274],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9961748,0.000018024712,0.0016357963,0.0012048505,0.00060689653,0.00035962203],"domain_scores_gemma":[0.9960897,0.0005466554,0.0007928428,0.0018975777,0.00036604132,0.00030721517],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00096239505,0.0005318647,0.00096119195,0.00057506876,0.00013911957,0.0011129731,0.0017938709,0.00073173805,0.09410621],"category_scores_gemma":[0.00010203859,0.00040761652,0.00062626804,0.000039349045,0.00019584862,0.0004619122,0.00052000984,0.00047832058,0.107035354],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000052036403,0.000022041173,0.000021396289,4.419361e-7,0.000008141085,0.000010310314,0.00001747352,0.000012329148,0.0000010604585,0.07440453,0.12008609,0.805411],"study_design_scores_gemma":[0.000080722006,0.000053164316,0.000013191094,0.000010218182,0.000022866665,0.000013801444,0.000019197918,0.00007043401,0.0000043011146,0.4361246,0.56325346,0.00033404716],"about_ca_topic_score_codex":0.000058972095,"about_ca_topic_score_gemma":0.0001434356,"teacher_disagreement_score":0.80507696,"about_ca_system_score_codex":0.00017575159,"about_ca_system_score_gemma":0.00017495833,"threshold_uncertainty_score":0.99992394},"labels":[],"label_agreement":null},{"id":"W4232578827","doi":"10.3410/f.736831598.793571328","title":"Faculty Opinions recommendation of Goal congruency dominates reward value in accounting for behavioral and neural correlates of value-based decision-making.","year":2020,"lang":"en","type":"dataset","venue":"Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Value (mathematics); Neural correlates of consciousness; Psychology; Computer science; Machine learning; Neuroscience; Cognition","score_opus":0.07119474552928302,"score_gpt":0.42564506324935536,"score_spread":0.35445031772007235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4232578827","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005330553,0.0006144897,0.00020659002,0.036559485,0.0015415432,0.0017233219,0.9587933,0.000021435937,0.0000067788196],"genre_scores_gemma":[0.0034451731,0.00007435979,0.004625126,0.0012817964,0.00011823805,0.00014287035,0.99024785,0.00003162514,0.000032970176],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9916274,0.0005780954,0.004110558,0.0011627328,0.0021091013,0.0004120938],"domain_scores_gemma":[0.9839427,0.003554439,0.004109547,0.0014895381,0.006637872,0.00026594067],"candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0051372084,0.00060414145,0.001832342,0.0009042549,0.00023626372,0.00037730287,0.0026899495,0.0008190597,0.00017346126],"category_scores_gemma":[0.046295326,0.00039604033,0.0008769694,0.0026515303,0.0005714994,0.000651671,0.00075968326,0.000983161,0.000019393965],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009739699,0.00037872102,0.00029543694,0.0011019635,0.000026088632,5.626387e-7,0.00013183054,0.000010402917,0.0000016172826,0.00011030274,0.94433665,0.05350902],"study_design_scores_gemma":[0.0011965332,0.00033817723,0.003905579,0.011169926,0.00020412968,0.000018333425,0.00012068091,0.0012384669,0.000009168363,0.0013446714,0.98006177,0.000392539],"about_ca_topic_score_codex":0.00009043872,"about_ca_topic_score_gemma":0.00001544108,"teacher_disagreement_score":0.053116478,"about_ca_system_score_codex":0.0001291927,"about_ca_system_score_gemma":0.0006727107,"threshold_uncertainty_score":0.99984914},"labels":[],"label_agreement":null},{"id":"W4233140950","doi":"10.31234/osf.io/2vz53","title":"Teaching &amp;amp; Learning Guide for: Risky-choice framing and rational decision-making","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Framing effect; Framing (construction); Narrative; Interpretation (philosophy); Rational planning model; Epistemology; Empirical research; Decision theory; Management science; Psychology; Computer science; Social psychology; Economics; Microeconomics; Philosophy","score_opus":0.13320554899220494,"score_gpt":0.450261345456847,"score_spread":0.31705579646464205,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4233140950","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5892872,0.0004306314,0.4031874,0.00030373264,0.0016917438,0.0003344954,0.00003933363,0.00012226701,0.0046031573],"genre_scores_gemma":[0.5545615,0.000053443888,0.43687636,0.00042301056,0.0006037266,0.000054422748,0.000075194424,0.0000709317,0.007281421],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9921735,0.0004987166,0.0024992907,0.0024308227,0.0017731013,0.00062459084],"domain_scores_gemma":[0.9633506,0.03238556,0.0013157385,0.0016599721,0.001017825,0.0002703319],"candidate_categories":["metaresearch","metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.010103884,0.0006521098,0.0012547685,0.00082175696,0.0013380769,0.004970674,0.0016052215,0.0007486445,0.0013679775],"category_scores_gemma":[0.069017544,0.0005606197,0.0006357868,0.00030352306,0.00013780987,0.00072130846,0.0034800519,0.0021297403,0.0002606127],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003693804,0.0000679765,0.01231574,0.000018138053,0.000041427593,0.00000777066,0.00089503755,0.019387681,0.00012275361,0.00032575658,0.011435254,0.9553455],"study_design_scores_gemma":[0.0005614131,0.000037083602,0.0049660476,0.0010014598,0.00012102457,0.00007787835,0.0020186189,0.027101925,0.000011963128,0.28371692,0.67910874,0.0012769352],"about_ca_topic_score_codex":0.00042140676,"about_ca_topic_score_gemma":0.0028626383,"teacher_disagreement_score":0.9540686,"about_ca_system_score_codex":0.00024393573,"about_ca_system_score_gemma":0.000512369,"threshold_uncertainty_score":0.99996203},"labels":[],"label_agreement":null},{"id":"W4233458252","doi":"10.1093/oso/9780198851486.001.0001","title":"Rational Powers in Action","year":2020,"lang":"en","type":"book","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":50,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Action (physics); Political science; Physics","score_opus":0.33040717382437557,"score_gpt":0.4516956300311673,"score_spread":0.12128845620679174,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4233458252","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003572709,0.0000250838,0.0007147992,0.0014509072,0.0015625192,0.0001556417,0.000034438654,0.000046743757,0.9924372],"genre_scores_gemma":[0.0070299655,0.000014600751,0.0007019777,0.00084818614,0.0002591626,0.0000043466493,0.000049253103,0.000019417981,0.9910731],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9974171,0.00004663933,0.00083027093,0.0006373315,0.00092876115,0.00013990974],"domain_scores_gemma":[0.9982548,0.0008293709,0.00030055403,0.00039120347,0.00012372415,0.000100380734],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0009109829,0.00018258175,0.00039966084,0.00045137006,0.000045571087,0.00032417517,0.0006326753,0.00028920555,0.0079143895],"category_scores_gemma":[0.00077712594,0.00014264668,0.00018194891,0.00020886486,0.000048366175,0.0002663659,0.00013106887,0.00037017252,0.009203998],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002220648,0.000015811134,0.00009705463,8.256429e-7,0.000002918258,0.000021245178,0.00004348163,0.00009367462,0.0000059393083,0.0041238475,0.6387191,0.3568539],"study_design_scores_gemma":[0.00011118171,0.000027009819,0.00021351642,0.000013762906,0.0000038348503,0.00000400255,0.000056879933,0.00038370973,0.000004653689,0.25670072,0.74233145,0.00014927523],"about_ca_topic_score_codex":0.000009626126,"about_ca_topic_score_gemma":0.00020463628,"teacher_disagreement_score":0.35670462,"about_ca_system_score_codex":0.00026755483,"about_ca_system_score_gemma":0.00059012277,"threshold_uncertainty_score":0.9929925},"labels":[],"label_agreement":null},{"id":"W4233891675","doi":"10.1007/978-3-319-16999-6_627-1","title":"Biases","year":2017,"lang":"en","type":"book-chapter","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Computer science","score_opus":0.49530477997228206,"score_gpt":0.46725930840554675,"score_spread":0.028045471566735314,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4233891675","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00089244795,0.00012728889,0.00008327513,0.0002958098,0.0016044775,0.00009709794,0.00007530918,0.00006269498,0.9967616],"genre_scores_gemma":[0.008978526,0.000058144717,0.0005071174,0.0002572329,0.00029200985,0.0000014894234,0.000008108051,0.000035328212,0.989862],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99727654,0.000010700463,0.00078236737,0.00078285043,0.00095727644,0.00019027723],"domain_scores_gemma":[0.9950362,0.0013684295,0.0007453161,0.0024239826,0.0002740415,0.00015202879],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0011977188,0.0002938668,0.0006224131,0.0003667484,0.00026420056,0.0011843533,0.0020950823,0.0003791568,0.02821374],"category_scores_gemma":[0.0020721918,0.00019629316,0.0004167174,0.0000100211355,0.00019514754,0.00024395631,0.00043801666,0.00026166256,0.037462786],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004988671,0.0000057133675,0.000017983159,2.7568166e-7,0.0000056898057,0.00003972583,0.0000070858855,0.000002183304,7.491244e-7,0.024685908,0.17958085,0.7956488],"study_design_scores_gemma":[0.000042557458,0.000020100993,0.000020816182,0.000037934962,0.00001075795,0.000009528867,0.0000043941345,0.000016261327,0.0000038168214,0.4321949,0.5674721,0.0001668667],"about_ca_topic_score_codex":0.000022288601,"about_ca_topic_score_gemma":0.0001437215,"teacher_disagreement_score":0.795482,"about_ca_system_score_codex":0.00004034212,"about_ca_system_score_gemma":0.00012106272,"threshold_uncertainty_score":0.99985254},"labels":[],"label_agreement":null},{"id":"W4234105302","doi":"10.32920/ryerson.14651751.v1","title":"Deviations from Bayes' Theorem During Belief Updating in Younger and Older Adults: Evidence From Behaviour and Neural Activity","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Representativeness heuristic; Heuristics; Bayes' theorem; Psychology; Cognition; Cognitive psychology; Young adult; Developmental psychology; Bayesian probability; Social psychology; Artificial intelligence; Computer science","score_opus":0.07655386352396361,"score_gpt":0.36649835503709416,"score_spread":0.28994449151313056,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4234105302","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99576586,0.0011135964,0.0011458093,0.00044220142,0.0007608006,0.00036766322,0.00025275105,0.000058774323,0.00009255828],"genre_scores_gemma":[0.99433726,0.00024402987,0.005007975,0.0001027143,0.00012680294,0.000037757607,0.000042230182,0.000030433375,0.000070780254],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9952773,0.0004048072,0.0011431007,0.0020501914,0.0007763617,0.00034826825],"domain_scores_gemma":[0.99411726,0.003578114,0.00061813253,0.0012227652,0.00026112742,0.00020262408],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0014321074,0.0004430356,0.0008521867,0.0003384658,0.00024457177,0.0020943838,0.00078619696,0.00043875337,0.00101196],"category_scores_gemma":[0.00264847,0.00036972365,0.00016119509,0.00029164256,0.00013646741,0.0014111701,0.0028790927,0.0009571479,0.000019894154],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009050206,0.00015171291,0.7635336,0.0000102802205,0.000020053392,0.00007882106,0.0031633112,0.00020079158,0.000688612,0.000019737468,0.00003512851,0.23200743],"study_design_scores_gemma":[0.0004497284,0.000013458622,0.97457707,0.0011174412,0.00005510376,0.000007894006,0.0038360334,0.009273901,0.0004915366,0.009711322,0.0000023170062,0.00046418307],"about_ca_topic_score_codex":0.00987557,"about_ca_topic_score_gemma":0.0056244596,"teacher_disagreement_score":0.23154324,"about_ca_system_score_codex":0.00012775161,"about_ca_system_score_gemma":0.000134887,"threshold_uncertainty_score":0.99990124},"labels":[],"label_agreement":null},{"id":"W4235726460","doi":"10.1007/978-3-319-51161-0_1","title":"Cost-Benefit Versus Expected Utility Acceptance Rules","year":2017,"lang":"en","type":"book-chapter","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Northern British Columbia","funders":"","keywords":"Dominance (genetics); Maximization; Stochastic dominance; Expected utility hypothesis; Positive economics; Economics; Mathematical economics; Management science; Econometrics; Microeconomics","score_opus":0.41075627385493957,"score_gpt":0.44769182297235033,"score_spread":0.03693554911741076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4235726460","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009355096,0.00028114725,0.00031055434,0.00017840933,0.0044407886,0.00038930567,0.0003722904,0.0001608357,0.98451155],"genre_scores_gemma":[0.05027518,0.0001285154,0.001708887,0.000107954824,0.00036411834,0.000014887535,0.000044305354,0.0000660964,0.94729006],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99512887,0.000024318122,0.0013249285,0.0015910194,0.0014984645,0.0004323854],"domain_scores_gemma":[0.99208933,0.0016462589,0.0012482267,0.004015653,0.0007045093,0.0002960254],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0013169765,0.00059323345,0.0011000994,0.00036523354,0.0005029172,0.0015234621,0.0035403369,0.00072756544,0.04124557],"category_scores_gemma":[0.0016544762,0.00045076237,0.00062606425,0.000031543186,0.00040141505,0.0005609442,0.0007700565,0.00054721866,0.016939145],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019863145,0.000021351358,0.000054881893,0.0000010933217,0.000022692026,0.000032002496,0.000042440923,0.0000019266276,0.0000011504914,0.021948684,0.031634603,0.9460406],"study_design_scores_gemma":[0.0004589793,0.000052823056,0.0006402036,0.000041867985,0.000033314234,0.0000047121207,0.000058423615,0.00007890154,0.000011774354,0.33118114,0.66697454,0.00046330405],"about_ca_topic_score_codex":0.000059987397,"about_ca_topic_score_gemma":0.00094021764,"teacher_disagreement_score":0.94557726,"about_ca_system_score_codex":0.00016293635,"about_ca_system_score_gemma":0.00018488134,"threshold_uncertainty_score":0.9997944},"labels":[],"label_agreement":null},{"id":"W4235997834","doi":"10.24124/2018/58843","title":"Uncertain-monetary promotions: A consumer motivational perspective.","year":2018,"lang":"en","type":"dissertation","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Northern British Columbia","funders":"","keywords":"Regulatory focus theory; Promotion (chess); Attractiveness; Perspective (graphical); Economics; Marketing; Business; Psychology; Political science; Computer science","score_opus":0.1447302497561931,"score_gpt":0.4385586099542296,"score_spread":0.2938283601980365,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4235997834","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.83137614,0.000333473,0.00035061818,0.0004899195,0.0033794218,0.0005194245,0.00013534677,0.00013707805,0.16327855],"genre_scores_gemma":[0.7292824,0.00005389143,0.010440683,0.00045382694,0.0008331744,0.00010730934,0.0011196042,0.00010382609,0.2576053],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9953135,0.00013810025,0.0012304337,0.0013200297,0.0016490383,0.0003488936],"domain_scores_gemma":[0.9944608,0.0009824049,0.0007009173,0.0009983239,0.0026814928,0.00017603686],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0015406588,0.00042374563,0.0006380116,0.0008409383,0.00038155756,0.00063168496,0.0011685902,0.00046878515,0.017920164],"category_scores_gemma":[0.003954746,0.00031938587,0.00036768444,0.0008105376,0.00016836713,0.00045377543,0.00007938827,0.0003945774,0.008316172],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032905603,0.00086183386,0.0038810074,0.000017114535,0.00020394688,0.0000535832,0.0044557885,0.00005701541,0.00023863524,0.014256523,0.444711,0.5309345],"study_design_scores_gemma":[0.00062404334,0.0002698506,0.024138989,0.00018801489,0.00013396482,0.0000372213,0.021173248,0.0009703291,0.00039223648,0.8277054,0.12323261,0.0011340915],"about_ca_topic_score_codex":0.00020556487,"about_ca_topic_score_gemma":0.0009938915,"teacher_disagreement_score":0.8134489,"about_ca_system_score_codex":0.00025560556,"about_ca_system_score_gemma":0.0006286151,"threshold_uncertainty_score":0.9999258},"labels":[],"label_agreement":null},{"id":"W4236164238","doi":"10.31219/osf.io/dnkcz","title":"Thinking in a foreign language distorts allocation of cognitive effort: Evidence from reasoning.","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Narodowym Centrum Nauki","keywords":"Syllogism; Logical reasoning; Foreign language; Cognitive psychology; Cognition; Context (archaeology); Computer science; Psychology; Linguistics; Cognitive science; Artificial intelligence","score_opus":0.11229728898278578,"score_gpt":0.4056076443021786,"score_spread":0.2933103553193928,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4236164238","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9758127,0.00070910464,0.013076458,0.00006431322,0.0007876911,0.0005585066,0.00010533281,0.000039435927,0.008846487],"genre_scores_gemma":[0.9950511,0.0000465511,0.0040998594,0.00009146286,0.00007063211,0.00002749766,0.00008178733,0.000022600887,0.0005085025],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9956973,0.00016838888,0.0013954102,0.0011549984,0.0013419911,0.00024188141],"domain_scores_gemma":[0.9921846,0.004942054,0.001192823,0.0012159128,0.0003871921,0.00007744031],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003966237,0.00029423705,0.0008402518,0.0004927218,0.000051287152,0.00036092463,0.0015412519,0.00038910177,0.00070214027],"category_scores_gemma":[0.00679247,0.00023030512,0.0002666144,0.0003189493,0.00009286406,0.00040481015,0.0013668532,0.0005273629,0.00030246453],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002712271,0.00022614197,0.4616172,0.000030208907,0.000042764143,0.00006578905,0.015723294,0.004334033,0.00013092623,0.0006348486,0.0011786057,0.5157449],"study_design_scores_gemma":[0.0010404426,0.00021000564,0.44749066,0.015442165,0.000185649,0.000008966417,0.01876111,0.037455253,0.0023733482,0.475553,0.00013059635,0.0013487863],"about_ca_topic_score_codex":0.0046344656,"about_ca_topic_score_gemma":0.0015294023,"teacher_disagreement_score":0.5143962,"about_ca_system_score_codex":0.00018603221,"about_ca_system_score_gemma":0.00031047742,"threshold_uncertainty_score":0.93915695},"labels":[],"label_agreement":null},{"id":"W4236212379","doi":"10.1007/978-3-319-19650-3_626","title":"Heuristics","year":2021,"lang":"en","type":"book-chapter","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Heuristics; Operating system","score_opus":0.27482052644624455,"score_gpt":0.4133903640068509,"score_spread":0.13856983756060637,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4236212379","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00038433855,0.00026823996,0.00116794,0.00027001693,0.0018236388,0.00006981139,0.000071135095,0.000055426703,0.9958894],"genre_scores_gemma":[0.0022086785,0.00008851983,0.00256159,0.000541612,0.0002848315,9.973782e-7,0.000020249941,0.00004184499,0.99425167],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9968168,0.000018276829,0.0010212532,0.00083261175,0.0011184971,0.00019255065],"domain_scores_gemma":[0.99635303,0.001160139,0.00038658004,0.0014150168,0.00052503374,0.00016020804],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00094972004,0.00029128013,0.0006566835,0.00027690857,0.00009483063,0.00063383643,0.00096296537,0.00041070857,0.044924192],"category_scores_gemma":[0.0009694357,0.00021621062,0.00040303668,0.00005766336,0.00009901834,0.00008692147,0.00042857413,0.00036252307,0.016699497],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003217877,0.000010389702,0.000012115007,7.800665e-7,0.0000087448325,0.00014446942,0.0000085690635,0.0000064503,0.0000014784762,0.17511469,0.18855679,0.6361323],"study_design_scores_gemma":[0.00003738148,0.000014275784,0.0000069245816,0.000021110052,0.000014452451,0.000018352714,0.000014353299,0.000032216885,0.0000039507327,0.41029125,0.58936995,0.00017577235],"about_ca_topic_score_codex":0.000004376612,"about_ca_topic_score_gemma":0.000038375874,"teacher_disagreement_score":0.6359565,"about_ca_system_score_codex":0.00006176666,"about_ca_system_score_gemma":0.00018755753,"threshold_uncertainty_score":0.9840661},"labels":[],"label_agreement":null},{"id":"W4236801214","doi":"10.1007/978-3-319-19650-3_627","title":"Biases","year":2021,"lang":"en","type":"book-chapter","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Philosophy","score_opus":0.41818560886549183,"score_gpt":0.4364041179637958,"score_spread":0.01821850909830397,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4236801214","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0019612287,0.00039766394,0.0001625958,0.00031762253,0.0013837836,0.00007088725,0.00006148487,0.00006227736,0.99558246],"genre_scores_gemma":[0.0030933286,0.0000878757,0.0010654499,0.0006211284,0.00023446759,0.000001422652,0.000020962647,0.00003568154,0.99483967],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99701303,0.000018846387,0.0009122685,0.0008501668,0.0010249224,0.00018077981],"domain_scores_gemma":[0.9958221,0.001978779,0.000346207,0.0013185405,0.00039045772,0.00014395494],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00088389416,0.00027772214,0.0006276296,0.0003505589,0.00009176406,0.0006589133,0.0009030115,0.0003495332,0.079795025],"category_scores_gemma":[0.0014027015,0.00019679348,0.0004600356,0.000064995824,0.0000933558,0.00013496475,0.00038905433,0.00026797722,0.017702997],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000032961555,0.000010369327,0.000012746251,4.2547276e-7,0.000008448566,0.000111239904,0.000008001294,0.000007947519,0.0000026234175,0.06117044,0.16477656,0.7738879],"study_design_scores_gemma":[0.000043646447,0.000017984783,0.000008982436,0.00004993968,0.000013720652,0.000021528776,0.000026207392,0.000021425461,0.000014320788,0.31597766,0.68360573,0.00019888158],"about_ca_topic_score_codex":0.000009654945,"about_ca_topic_score_gemma":0.00009159108,"teacher_disagreement_score":0.77368903,"about_ca_system_score_codex":0.00004965104,"about_ca_system_score_gemma":0.00017476299,"threshold_uncertainty_score":0.98306185},"labels":[],"label_agreement":null},{"id":"W4237539246","doi":"10.17771/pucrio.acad.53029","title":"ESSAYS ON BEHAVIORAL FINANCE","year":2021,"lang":"en","type":"dissertation","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Pontifícia Universidade Católica do Rio de Janeiro; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; McMaster University","keywords":"Weighting; Prospect theory; Cumulative prospect theory; Predictive power; Preference; Empirical research; Econometrics; Expected utility hypothesis; Framing (construction); Attractiveness; Function (biology); Economics; Positive economics; Mathematical economics; Mathematics; Psychology; Epistemology; Microeconomics; Geography; Statistics; Philosophy","score_opus":0.17011684089423756,"score_gpt":0.463179215404956,"score_spread":0.2930623745107184,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4237539246","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.78571415,0.00010649762,0.000022480464,0.000070229406,0.0041788,0.000113416514,0.000045761135,0.00004903046,0.20969962],"genre_scores_gemma":[0.6699977,0.000054762924,0.00081251364,0.0002030326,0.0001708789,0.000046793368,0.000380604,0.00004786448,0.32828587],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9958733,0.000089896406,0.0010744715,0.0012097902,0.0014291042,0.00032345514],"domain_scores_gemma":[0.9968556,0.00059136795,0.0005401138,0.0013801233,0.0005316721,0.000101131795],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0009072288,0.00037339274,0.0007176128,0.00042596742,0.00019158468,0.00083663745,0.0012168005,0.0005031021,0.0078070783],"category_scores_gemma":[0.00064335647,0.00028699005,0.00043741093,0.00059009896,0.000032982956,0.00020768547,0.000074484975,0.0004979451,0.0049824184],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000059339854,0.00034338806,0.00015709813,0.0000021846831,0.000004389816,0.00010480158,0.00021879563,0.000049465743,0.000053815063,0.0022179815,0.071731,0.9250577],"study_design_scores_gemma":[0.00131065,0.001301014,0.011237702,0.0008230052,0.0002222833,0.000045325247,0.014957206,0.0006446864,0.007068733,0.3749268,0.58415186,0.0033106986],"about_ca_topic_score_codex":0.00006317631,"about_ca_topic_score_gemma":0.0011195666,"teacher_disagreement_score":0.921747,"about_ca_system_score_codex":0.000085784566,"about_ca_system_score_gemma":0.00028736127,"threshold_uncertainty_score":0.9999582},"labels":[],"label_agreement":null},{"id":"W4237784729","doi":"10.31234/osf.io/ma7rb","title":"Negative Context Reduces the Discriminability of Verbal Probabilities","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Context (archaeology); Meaning (existential); Negation; Context effect; Psychology; Affect (linguistics); Cognitive psychology; Event (particle physics); Social psychology; Computer science; Linguistics; Communication; Word (group theory); History","score_opus":0.3639614586971992,"score_gpt":0.44068385196592863,"score_spread":0.07672239326872943,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4237784729","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9752396,0.00010347693,0.00029276806,0.009241062,0.0014100679,0.0007368151,0.00021498244,0.000051415096,0.012709857],"genre_scores_gemma":[0.9975686,0.000010274213,0.0009798653,0.0002879535,0.00011673793,0.000053253127,0.000005149497,0.000014418161,0.0009637432],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99530464,0.00049862306,0.0016656305,0.0011522624,0.0011382728,0.00024054066],"domain_scores_gemma":[0.99153465,0.0047865957,0.0009642126,0.0018073581,0.00078227214,0.00012491438],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0030235148,0.00033617506,0.0009536839,0.00010289659,0.00014752918,0.0004655711,0.0027910774,0.00023990229,0.0010586971],"category_scores_gemma":[0.010580964,0.0001717585,0.000579573,0.00028146026,0.001115419,0.0001962819,0.0026466586,0.0006455707,0.00017283142],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031635453,0.00030396966,0.0031005004,0.000054287775,0.000070742804,0.0000049776972,0.021557681,0.00055683183,0.0001465405,0.010947047,0.033625133,0.9293159],"study_design_scores_gemma":[0.0001279877,0.00011257032,0.0032326127,0.00005797643,0.000044369728,0.0000018018922,0.026816815,0.00055084407,0.0041827606,0.9602425,0.004386069,0.00024366868],"about_ca_topic_score_codex":0.00060097314,"about_ca_topic_score_gemma":0.0002380734,"teacher_disagreement_score":0.94929546,"about_ca_system_score_codex":0.00011156512,"about_ca_system_score_gemma":0.0005449838,"threshold_uncertainty_score":0.99985445},"labels":[],"label_agreement":null},{"id":"W4238021447","doi":"10.1002/9781119547174.ch239","title":"Risk Taking","year":2020,"lang":"en","type":"other","venue":"The Wiley Encyclopedia of Personality and Individual Differences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Sensation seeking; Personality; Psychology; Construct (python library); Relevance (law); Big Five personality traits; Social psychology; Sensation; Cognitive psychology; Political science; Computer science","score_opus":0.13402321292640612,"score_gpt":0.34691013452518815,"score_spread":0.21288692159878203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4238021447","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.43797407,0.0057713315,0.00009657956,0.0009526277,0.0012949959,0.00044236038,0.0030304468,0.000113429516,0.55032414],"genre_scores_gemma":[0.8064349,0.03308249,0.0019835245,0.0009504211,0.0027722348,0.00005415031,0.00010523551,0.00039232473,0.1542247],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99598694,0.00053863344,0.0008599915,0.0008008163,0.001505386,0.00030825424],"domain_scores_gemma":[0.99458504,0.0019464224,0.002571914,0.00065242196,0.00006169302,0.00018248528],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0020125948,0.0004147235,0.00095648464,0.00024047881,0.00024103971,0.00030921807,0.0019246627,0.00033298225,0.006714908],"category_scores_gemma":[0.0028834343,0.00023352011,0.0002610699,0.00038565518,0.0008156266,0.00011969105,0.0005375167,0.00057260605,0.00019042745],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002471591,0.00006591168,0.0767867,0.00002237066,0.00011207435,0.000003365774,0.0038746507,6.475825e-7,9.004264e-7,0.0004229286,0.2911297,0.627556],"study_design_scores_gemma":[0.0003886903,0.00024648628,0.22212054,0.00048406702,0.00041969412,0.000008973074,0.0030223732,0.0000744999,0.0000027371284,0.06709038,0.70543844,0.00070313434],"about_ca_topic_score_codex":0.0015300235,"about_ca_topic_score_gemma":0.00063360884,"teacher_disagreement_score":0.62685287,"about_ca_system_score_codex":0.000010784545,"about_ca_system_score_gemma":0.000116307565,"threshold_uncertainty_score":0.9941931},"labels":[],"label_agreement":null},{"id":"W4238190096","doi":"10.22215/etd/2020-14272","title":"Scalar implicatures under uncertainty","year":2020,"lang":"en","type":"dissertation","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Implicature; Scalar (mathematics); Probabilistic logic; Axiom; Probability theory; Interpretation (philosophy); Literal (mathematical logic); Computer science; Psychology; Mathematics; Cognitive psychology; Artificial intelligence; Pragmatics; Linguistics; Statistics; Algorithm","score_opus":0.14641566515392626,"score_gpt":0.44770024879351816,"score_spread":0.3012845836395919,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4238190096","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.79745424,0.00036438432,0.0005168689,0.0022460115,0.0036551743,0.00038877287,0.00008664018,0.0002403087,0.1950476],"genre_scores_gemma":[0.9355688,0.00004561127,0.0014921016,0.0021836984,0.00035647515,0.000027534463,0.00058735575,0.00007173745,0.059666656],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99608094,0.000079977646,0.0010685715,0.0012291381,0.001228878,0.0003124757],"domain_scores_gemma":[0.9969996,0.00075311994,0.0005112197,0.0010757782,0.00039325314,0.00026700023],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0008202721,0.00037299492,0.00070877356,0.0003144329,0.00018326714,0.0008517664,0.0017146231,0.00055961584,0.004234411],"category_scores_gemma":[0.0011850997,0.00025587901,0.00045777948,0.00062577066,0.000045511657,0.0001799171,0.00011410026,0.0005408183,0.0060789655],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012170381,0.000058854293,0.00011391255,0.0000054986485,0.000025451762,0.000014384985,0.00026282828,0.000430009,0.0004354256,0.005176516,0.1629385,0.8304169],"study_design_scores_gemma":[0.00025145625,0.00008791275,0.005158507,0.000039182265,0.00006546952,0.00000756067,0.0038317908,0.00089069235,0.00045777237,0.4901726,0.4983426,0.0006944783],"about_ca_topic_score_codex":0.000077254146,"about_ca_topic_score_gemma":0.00054597814,"teacher_disagreement_score":0.8297224,"about_ca_system_score_codex":0.00007919668,"about_ca_system_score_gemma":0.00024310782,"threshold_uncertainty_score":0.99998933},"labels":[],"label_agreement":null},{"id":"W4238506832","doi":"10.1111/cjag.2016.64.issue-4","title":"Applications of Behavioral and Experimental Economics to Decision Making in the Agricultural, Food, and Resource Sectors: An Introduction","year":2016,"lang":"en","type":"paratext","venue":"Canadian Journal of Agricultural Economics/Revue canadienne d agroeconomie","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science","score_opus":0.0504477902068556,"score_gpt":0.2849680295479383,"score_spread":0.2345202393410827,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4238506832","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9916788,0.0009387278,0.000025510255,0.0026790495,0.0020773874,0.00081425655,0.0010770826,0.000003936709,0.000705287],"genre_scores_gemma":[0.99594206,0.00014353679,0.00052994187,0.00025129307,0.0021953888,0.000055042645,0.000074433774,0.000044928478,0.0007633588],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9948951,0.00020956052,0.0028137667,0.001186081,0.000075485616,0.000820011],"domain_scores_gemma":[0.9942386,0.0008240244,0.002302115,0.00085347827,0.00039620887,0.0013855313],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0019900454,0.0006648499,0.0015053237,0.0014698625,0.0003791599,0.0010466371,0.0019582359,0.0004857763,0.0005067344],"category_scores_gemma":[0.00018326448,0.0004249976,0.00034126462,0.00038435374,0.0003317554,0.0012704147,0.00015543091,0.0006088993,0.00009972149],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007806524,0.0004591572,0.0043943524,0.0001193273,0.00045436673,0.00006865528,0.032082144,0.02259172,0.0005847351,0.010230446,0.3003438,0.62789065],"study_design_scores_gemma":[0.0022659812,0.004418607,0.033497427,0.0007045853,0.0002553689,0.0036862371,0.070878215,0.000047170128,0.00031277258,0.010093825,0.87119937,0.002640431],"about_ca_topic_score_codex":0.0034825269,"about_ca_topic_score_gemma":0.4695621,"teacher_disagreement_score":0.6252502,"about_ca_system_score_codex":0.0019810651,"about_ca_system_score_gemma":0.00065278483,"threshold_uncertainty_score":0.99999034},"labels":[],"label_agreement":null},{"id":"W4238924615","doi":"10.33423/jabe.v22i12.3878","title":"A Method for Diagnosing the Causes of Escalating Commitment","year":2020,"lang":"en","type":"article","venue":"Journal of Applied Business and Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Decision maker; Management science; Computer science; Operations research; Risk analysis (engineering); Economics; Engineering; Business","score_opus":0.16637593919381946,"score_gpt":0.382025206416582,"score_spread":0.21564926722276254,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4238924615","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9642228,0.000087054,0.03145778,0.0036115074,0.00022703422,0.00014038874,0.00001526748,0.0000026526868,0.00023550664],"genre_scores_gemma":[0.95968,0.00010747494,0.0392479,0.0007107282,0.00023597825,0.000003682426,4.4208954e-7,0.000010908183,0.0000028645768],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.998512,0.00001912133,0.0010614871,0.00017016914,0.00012148684,0.000115713236],"domain_scores_gemma":[0.99603677,0.0022362303,0.0012321573,0.00015371855,0.0002594908,0.000081652106],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019618047,0.00010465023,0.00048907375,0.00008375989,0.00012776065,0.00023316381,0.00038553393,0.000049520586,0.000018955463],"category_scores_gemma":[0.00045563612,0.00006299703,0.0001201332,0.00016164228,0.00006149353,0.00018233879,0.00011238456,0.000099649296,0.000002421629],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028998018,0.00005217109,0.0018223386,0.000014306177,0.00003793676,0.0000013624012,0.0010149196,0.02299997,0.00045253243,0.002735198,0.0012433644,0.9693359],"study_design_scores_gemma":[0.006540404,0.0008124236,0.034382146,0.00021852869,0.00058088946,0.00017169498,0.019623734,0.14556655,0.008610738,0.53072524,0.2517162,0.0010514486],"about_ca_topic_score_codex":0.0000065594504,"about_ca_topic_score_gemma":0.000008482208,"teacher_disagreement_score":0.9682845,"about_ca_system_score_codex":0.000022946533,"about_ca_system_score_gemma":0.000071084374,"threshold_uncertainty_score":0.25689444},"labels":[],"label_agreement":null},{"id":"W4239508753","doi":"10.32920/14638635.v1","title":"Decisions from experience: adaptive information search and choice in younger and older adults","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Canadian Institutes of Health Research","keywords":"Cognition; Psychology; Neuropsychology; Valence (chemistry); Cognitive psychology; Affect (linguistics); Psychiatry","score_opus":0.14043805600269083,"score_gpt":0.40797124856968847,"score_spread":0.26753319256699765,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4239508753","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99356896,0.00042164157,0.0035070835,0.0001896875,0.00067539816,0.00039930365,0.00011011029,0.000027909473,0.0010998888],"genre_scores_gemma":[0.9906441,0.00024052884,0.0085157,0.00029446618,0.000052775522,0.00004686321,0.00005296439,0.000011008784,0.00014158746],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9961761,0.00017311393,0.0012408628,0.0010331705,0.0010816661,0.00029507533],"domain_scores_gemma":[0.99507064,0.0029900172,0.00024080074,0.0009380035,0.00052923005,0.00023133896],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0013212576,0.00030717684,0.00061629317,0.0006302789,0.0001380118,0.002011359,0.0007020536,0.00045285153,0.00089909544],"category_scores_gemma":[0.0028076833,0.0002378082,0.00009762573,0.00041334744,0.00017368396,0.0019120778,0.0025169707,0.00068475597,0.00010518622],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008370026,0.00006505053,0.022248738,0.000002822323,0.000008135606,0.000015034209,0.0153067,0.00025006002,0.000009602597,0.000053049203,0.00033804262,0.9616191],"study_design_scores_gemma":[0.0013623008,0.000060319337,0.8735616,0.00087144034,0.000019443398,0.000015478972,0.06756502,0.03976323,0.00010749879,0.01447827,0.0014583564,0.0007370511],"about_ca_topic_score_codex":0.0061370153,"about_ca_topic_score_gemma":0.0021790736,"teacher_disagreement_score":0.960882,"about_ca_system_score_codex":0.000090672445,"about_ca_system_score_gemma":0.00021245408,"threshold_uncertainty_score":0.9990246},"labels":[],"label_agreement":null},{"id":"W4240091398","doi":"10.3982/ecta16467","title":"Present Bias","year":2021,"lang":"en","type":"article","venue":"Econometrica","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Axiom; Discounting; Preference; Class (philosophy); Mathematical economics; Hyperbolic discounting; Revealed preference; Dynamic inconsistency; Econometrics; Economics; Time preference; Mathematics; Microeconomics; Computer science","score_opus":0.4644787090694801,"score_gpt":0.44651020906383526,"score_spread":0.017968500005644816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4240091398","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.86443835,0.0005891381,0.0005872285,0.0021106703,0.0012085648,0.000057213212,0.000026647886,0.00004148295,0.13094068],"genre_scores_gemma":[0.98480815,0.00003715849,0.0018358328,0.00036180846,0.00018801764,0.0000057614975,0.000004440463,0.0000113038095,0.0127475085],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9978983,0.00009288372,0.00072414265,0.00062298303,0.0004083291,0.00025340338],"domain_scores_gemma":[0.99621487,0.0021709327,0.00022017729,0.00097015896,0.0002382712,0.00018558027],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0014688009,0.00011454882,0.00032801295,0.00080080604,0.000113141985,0.0006604006,0.00066684134,0.00007210338,0.008445272],"category_scores_gemma":[0.005934073,0.0000937123,0.00021598987,0.0025506446,0.00004554768,0.0003125408,0.00029947035,0.0001162666,0.009918513],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004015259,0.00010060474,0.016922953,4.540226e-7,0.000007689634,0.000042981428,0.000045490968,0.00014542555,0.000011919946,0.0008386689,0.055628285,0.92625153],"study_design_scores_gemma":[0.00018597647,0.00003173315,0.021157164,0.0000027463261,0.0000056878366,0.00002520689,0.00020356613,0.0006178601,0.000491907,0.06255027,0.91456515,0.00016276166],"about_ca_topic_score_codex":0.000011062732,"about_ca_topic_score_gemma":0.000009812772,"teacher_disagreement_score":0.92608875,"about_ca_system_score_codex":0.000070471266,"about_ca_system_score_gemma":0.00011885747,"threshold_uncertainty_score":0.99246114},"labels":[],"label_agreement":null},{"id":"W4241644014","doi":"10.31234/osf.io/s5ard","title":"Resource-rational approach to meta-control problems across the lifespan","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Concordia University","funders":"","keywords":"Affect (linguistics); Control (management); Cognition; Resource (disambiguation); Psychology; Meta-analysis; Adaptation (eye); Cognitive aging; Economics; Computer science; Medicine","score_opus":0.371235415926663,"score_gpt":0.4261028211373005,"score_spread":0.05486740521063754,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4241644014","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24814527,0.00064442365,0.43543652,0.1277142,0.003445835,0.006842775,0.0021311902,0.0006851954,0.17495462],"genre_scores_gemma":[0.97229946,0.0000021401866,0.009980867,0.008332326,0.00065278506,0.00054028956,0.00004433089,0.000047990903,0.008099812],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9931215,0.00049686845,0.0017494683,0.0019430291,0.0021695779,0.00051953865],"domain_scores_gemma":[0.9939679,0.002183414,0.00067926914,0.002317662,0.00045306454,0.000398715],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0077914945,0.0005246432,0.0012878005,0.00017537916,0.00048524377,0.0032753665,0.004497322,0.00039100193,0.00066407456],"category_scores_gemma":[0.0031281945,0.00026415056,0.0010957005,0.000599703,0.0001656222,0.00016899372,0.0027111508,0.0010493847,0.0023297884],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022675369,0.00048053009,0.0007286002,0.000019592166,0.0011659217,0.00001045015,0.0079339035,0.30354306,0.00005345821,0.006822578,0.45317665,0.2258385],"study_design_scores_gemma":[0.00051268225,0.00010346291,0.0014959937,0.000017996323,0.0006128685,0.000019774394,0.0024858206,0.039541103,0.00002848072,0.20031238,0.75398505,0.00088439503],"about_ca_topic_score_codex":0.00010660442,"about_ca_topic_score_gemma":0.00009703604,"teacher_disagreement_score":0.7241542,"about_ca_system_score_codex":0.00008339342,"about_ca_system_score_gemma":0.00027421888,"threshold_uncertainty_score":0.99998105},"labels":[],"label_agreement":null},{"id":"W4242806196","doi":"10.1108/978-1-80071-817-320211002","title":"Overcoming Irrationality: The Popperian Approach","year":2021,"lang":"en","type":"book-chapter","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Irrationality; Epistemology; Psychology; Cognitive science; Sociology; Philosophy; Rationality","score_opus":0.26452028734202415,"score_gpt":0.3866511234006699,"score_spread":0.12213083605864578,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4242806196","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0012090527,0.00023931875,0.0017025272,0.0015903477,0.000978837,0.00017694329,0.000054859574,0.00004081717,0.9940073],"genre_scores_gemma":[0.013451739,0.000025678317,0.0032931773,0.0015297276,0.0004327713,0.0000071029044,0.00005351679,0.000039922408,0.98116636],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99636436,0.000068042384,0.0010327968,0.00091294915,0.0014097106,0.0002121287],"domain_scores_gemma":[0.9962343,0.00124422,0.000434951,0.0016235376,0.0003560313,0.000106989544],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0025060535,0.00031860452,0.00057009264,0.00017397974,0.00034682534,0.0013066186,0.0013344847,0.00034985386,0.012996721],"category_scores_gemma":[0.0005907651,0.00018049852,0.0004743512,0.00008991157,0.00016659347,0.00020228988,0.000498887,0.00045415835,0.0017714353],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000069004486,0.000021918811,0.000033315922,0.0000013880672,0.000025099234,0.000013954662,0.00009087872,0.000047143556,0.0000050570734,0.5334992,0.056781728,0.40947345],"study_design_scores_gemma":[0.00005811081,0.000008385177,0.000056332145,0.000016035749,0.000019853129,0.000031225674,0.00020245361,0.0002477057,0.0000022384322,0.3483633,0.650792,0.00020231893],"about_ca_topic_score_codex":0.000020848523,"about_ca_topic_score_gemma":0.00007458863,"teacher_disagreement_score":0.5940103,"about_ca_system_score_codex":0.00009120197,"about_ca_system_score_gemma":0.000245717,"threshold_uncertainty_score":0.9997301},"labels":[],"label_agreement":null},{"id":"W4243517039","doi":"10.3917/ecop.159.0105","title":"Généralisation de l'espérance d'utilité : le cas des jeux de loterie en France","year":2003,"lang":"fr","type":"article","venue":"Économie & prévision","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Nautical Research Society","funders":"","keywords":"Humanities; Mathematics; Philosophy","score_opus":0.07881348929308107,"score_gpt":0.3682670373736771,"score_spread":0.28945354808059603,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4243517039","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95137215,0.0047455947,0.029421177,0.004121471,0.0028437357,0.00038817688,0.000065208704,0.00009400553,0.006948497],"genre_scores_gemma":[0.946264,0.00088928477,0.033685368,0.0008762484,0.00031758315,0.00003076692,0.000007864857,0.00007083821,0.017858047],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9947806,0.0009560002,0.0014618167,0.001272236,0.00040647626,0.0011228449],"domain_scores_gemma":[0.9951144,0.002205678,0.0005707608,0.0012996097,0.0002785732,0.00053096435],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00567698,0.0005059388,0.00074659183,0.00030875637,0.00068255374,0.0008704804,0.001089867,0.00061633013,0.0015918835],"category_scores_gemma":[0.0036868772,0.0005371987,0.0003945883,0.0005874047,0.00061406544,0.0017111244,0.00020221011,0.00051489065,0.002017981],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009900267,0.00031419387,0.0458346,0.000027943457,0.000016582006,0.00005949488,0.0021536357,0.003750755,0.0012203063,0.010010984,0.0031104682,0.93340206],"study_design_scores_gemma":[0.0012575102,0.00030081059,0.037766587,0.00039139393,0.00005628438,0.00022926797,0.0009904375,0.012040996,0.0076476517,0.38464534,0.55387384,0.0007998831],"about_ca_topic_score_codex":0.0010580078,"about_ca_topic_score_gemma":0.00051950134,"teacher_disagreement_score":0.93260217,"about_ca_system_score_codex":0.0012622663,"about_ca_system_score_gemma":0.0013213502,"threshold_uncertainty_score":0.99970794},"labels":[],"label_agreement":null},{"id":"W4244185607","doi":"10.32920/ryerson.14646000.v1","title":"Decision Making Under Risk Across Different Contexts","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Context (archaeology); Quality (philosophy); Event (particle physics); Decision quality; Psychology; Actuarial science; Economics; Operations management; Geography","score_opus":0.15248665554039428,"score_gpt":0.4659299394577652,"score_spread":0.31344328391737086,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4244185607","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.84186894,0.00051035907,0.14754844,0.00016682415,0.0070263105,0.00031858584,0.00022627946,0.00013918903,0.0021950768],"genre_scores_gemma":[0.9903536,0.00013906794,0.006890149,0.00043912945,0.0002591092,0.000028884338,0.000026043708,0.00006455643,0.0017994583],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9912567,0.00047512,0.0024613603,0.0026173438,0.0024136244,0.0007758543],"domain_scores_gemma":[0.9875289,0.006205528,0.0014665596,0.0036230178,0.0008729482,0.00030302053],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0041763,0.0007527568,0.0015974919,0.00037125498,0.00053055986,0.0055820607,0.0030280205,0.0009209911,0.004785048],"category_scores_gemma":[0.0045777257,0.0005149263,0.0011447088,0.0004240975,0.00019372925,0.00033403301,0.0073596435,0.0015846366,0.0012671294],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006958249,0.00019085135,0.012546929,0.0000040189266,0.000040999646,0.00007681997,0.00048456734,0.006640101,0.0000123740565,0.00013467674,0.004245225,0.9755539],"study_design_scores_gemma":[0.0009038629,0.000083913,0.15451862,0.00087621633,0.0001120914,0.00006475015,0.005371888,0.011683781,0.00017435457,0.81931376,0.0053649596,0.0015317786],"about_ca_topic_score_codex":0.00014387941,"about_ca_topic_score_gemma":0.0020321026,"teacher_disagreement_score":0.9740221,"about_ca_system_score_codex":0.00033488264,"about_ca_system_score_gemma":0.0002363606,"threshold_uncertainty_score":0.9997302},"labels":[],"label_agreement":null},{"id":"W4244976668","doi":"10.4018/978-1-5225-5478-3.ch023","title":"Economic Decision Making, Emotion, and Prefrontal Cortex","year":2018,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Neuroeconomics; Consumer neuroscience; Prefrontal cortex; Psychology; Self-reference effect; Posterior parietal cortex; Cognitive psychology; Anterior cingulate cortex; Neuroscience; Social decision making; Decision-making; Cognitive science; Cognition; Economics","score_opus":0.05292380798354687,"score_gpt":0.3471795807916345,"score_spread":0.2942557728080877,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4244976668","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21341018,0.0001949525,0.0005468017,0.000022677015,0.0027259607,0.00034310127,0.0005109089,0.000098467906,0.78214693],"genre_scores_gemma":[0.8848477,0.000015059463,0.003146337,0.00041146218,0.00093536265,0.0000077223785,0.0000066118087,0.0000948553,0.11053489],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99524873,0.000040085233,0.0016112672,0.0017101035,0.00092835794,0.00046145427],"domain_scores_gemma":[0.9963861,0.00048396015,0.0010143638,0.0015162481,0.00028206897,0.00031724057],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0010989989,0.00067757844,0.001031721,0.00029732633,0.00030128795,0.0010389483,0.0012990825,0.0007930029,0.0026397263],"category_scores_gemma":[0.00024871307,0.0005783335,0.0004175901,0.000025424166,0.00047323923,0.00022962723,0.00085552654,0.00032567672,0.008750356],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016879346,0.000014094844,0.00034425117,0.0000031720294,0.000041426523,0.000060421706,0.000093654875,0.0000059862514,0.0000035013456,0.19362473,0.05386968,0.7517703],"study_design_scores_gemma":[0.00034362258,0.0002018412,0.001992612,0.00023386194,0.000062599785,0.00019645624,0.000047556263,0.00014552678,0.0000019372326,0.8556309,0.14058837,0.00055471604],"about_ca_topic_score_codex":0.000032783602,"about_ca_topic_score_gemma":0.0005987392,"teacher_disagreement_score":0.7512156,"about_ca_system_score_codex":0.00061635213,"about_ca_system_score_gemma":0.0003268348,"threshold_uncertainty_score":0.9999981},"labels":[],"label_agreement":null},{"id":"W4245033913","doi":"10.32920/ryerson.14651751","title":"Deviations from Bayes' Theorem During Belief Updating in Younger and Older Adults: Evidence From Behaviour and Neural Activity","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Representativeness heuristic; Heuristics; Bayes' theorem; Psychology; Cognition; Cognitive psychology; Young adult; Developmental psychology; Bayesian probability; Social psychology; Artificial intelligence; Computer science","score_opus":0.07655386352396361,"score_gpt":0.36649835503709416,"score_spread":0.28994449151313056,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4245033913","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99576586,0.0011135964,0.0011458093,0.00044220142,0.0007608006,0.00036766322,0.00025275105,0.000058774323,0.00009255828],"genre_scores_gemma":[0.99433726,0.00024402987,0.005007975,0.0001027143,0.00012680294,0.000037757607,0.000042230182,0.000030433375,0.000070780254],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9952773,0.0004048072,0.0011431007,0.0020501914,0.0007763617,0.00034826825],"domain_scores_gemma":[0.99411726,0.003578114,0.00061813253,0.0012227652,0.00026112742,0.00020262408],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0014321074,0.0004430356,0.0008521867,0.0003384658,0.00024457177,0.0020943838,0.00078619696,0.00043875337,0.00101196],"category_scores_gemma":[0.00264847,0.00036972365,0.00016119509,0.00029164256,0.00013646741,0.0014111701,0.0028790927,0.0009571479,0.000019894154],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009050206,0.00015171291,0.7635336,0.0000102802205,0.000020053392,0.00007882106,0.0031633112,0.00020079158,0.000688612,0.000019737468,0.00003512851,0.23200743],"study_design_scores_gemma":[0.0004497284,0.000013458622,0.97457707,0.0011174412,0.00005510376,0.000007894006,0.0038360334,0.009273901,0.0004915366,0.009711322,0.0000023170062,0.00046418307],"about_ca_topic_score_codex":0.00987557,"about_ca_topic_score_gemma":0.0056244596,"teacher_disagreement_score":0.23154324,"about_ca_system_score_codex":0.00012775161,"about_ca_system_score_gemma":0.000134887,"threshold_uncertainty_score":0.99990124},"labels":[],"label_agreement":null},{"id":"W4245479670","doi":"10.17722/ijme.v9i3.374","title":"Break-Even Analysis as a powerful tool in Decision-Making","year":2017,"lang":"en","type":"article","venue":"International Journal of Management Excellence","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science","score_opus":0.05264939498581956,"score_gpt":0.43381627507174875,"score_spread":0.3811668800859292,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4245479670","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9598179,0.00007916253,0.018921474,0.0017017133,0.0023877034,0.000093669216,0.000008108811,0.000006868589,0.016983407],"genre_scores_gemma":[0.99171335,0.0001843887,0.0065113,0.00026764136,0.00015201597,0.0000016452465,5.5905906e-7,0.000009663319,0.0011594394],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9950685,0.000082103295,0.0016064908,0.0004478116,0.0025621813,0.00023290029],"domain_scores_gemma":[0.9951721,0.0010510602,0.0019661468,0.0009710673,0.0007665898,0.000073046394],"candidate_categories":["scholarly_communication","open_science","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0043893475,0.00017914828,0.00047110068,0.0020525607,0.00016038812,0.001705363,0.005573484,0.00006882438,0.0015431747],"category_scores_gemma":[0.0031309365,0.00014243765,0.000474513,0.0004352091,0.000104001825,0.0012828725,0.0009631395,0.00023769314,0.0005459124],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002927959,0.00019388931,0.06650972,0.0000010587985,0.00030424068,0.0017006408,0.00018326519,0.005600455,0.000010719523,0.0010627453,0.0028924346,0.921248],"study_design_scores_gemma":[0.0016875187,0.00015820256,0.4303646,0.0006426603,0.000296306,0.00020178779,0.0012242708,0.006378373,0.000038903694,0.5132891,0.04523589,0.00048237998],"about_ca_topic_score_codex":0.000049294147,"about_ca_topic_score_gemma":0.000097756376,"teacher_disagreement_score":0.92076564,"about_ca_system_score_codex":0.00019393119,"about_ca_system_score_gemma":0.000060618557,"threshold_uncertainty_score":0.9998068},"labels":[],"label_agreement":null},{"id":"W4245561046","doi":"10.31234/osf.io/my4hd","title":"Living near the edge: How extreme outcomes and their neighbours drive risky choice","year":2017,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Optimal distinctiveness theory; Salience (neuroscience); Salient; Odds; Psychology; Outcome (game theory); Perception; Extreme value theory; Social psychology; Cognitive psychology; Computer science; Logistic regression; Mathematics; Statistics; Artificial intelligence","score_opus":0.20895204336355575,"score_gpt":0.3942458066075788,"score_spread":0.18529376324402305,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4245561046","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97528857,0.00050692447,0.0020339068,0.008099856,0.003560821,0.00045682472,0.00008490135,0.00010696389,0.009861203],"genre_scores_gemma":[0.98260456,0.00011603786,0.0012803811,0.00047221273,0.0003197358,0.000026751195,0.0000029846585,0.000041638952,0.015135708],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9960803,0.00031201178,0.0007856983,0.0014811826,0.0008431923,0.0004976141],"domain_scores_gemma":[0.985189,0.008934757,0.0012901294,0.0039526857,0.00039177484,0.00024165306],"candidate_categories":["metaresearch","metaepi_narrow","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0045853625,0.00059982203,0.0010601889,0.00021270062,0.0016064964,0.013918731,0.004383841,0.00047884003,0.00062415015],"category_scores_gemma":[0.008607143,0.00028629362,0.0005455806,0.00011139331,0.0008354445,0.00051468756,0.005329317,0.0010837256,0.00033890706],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000059199942,0.00005216711,0.18192782,0.0000038699013,0.000049014478,0.000006238988,0.001878623,0.00010991525,0.000006556882,0.00017491076,0.012008733,0.80377626],"study_design_scores_gemma":[0.0003273367,0.000058236346,0.67215985,0.0002463647,0.00009925757,0.000023822373,0.0040976033,0.012072561,0.00002156333,0.1662816,0.14352651,0.0010852688],"about_ca_topic_score_codex":0.0006501222,"about_ca_topic_score_gemma":0.0015960595,"teacher_disagreement_score":0.802691,"about_ca_system_score_codex":0.00007274054,"about_ca_system_score_gemma":0.00031486916,"threshold_uncertainty_score":0.99995893},"labels":[],"label_agreement":null},{"id":"W4246475774","doi":"10.1007/978-3-319-28099-8_3-1","title":"Balanced Inventory of Desirable Responding","year":2017,"lang":"en","type":"book-chapter","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Psychology","score_opus":0.31252907887780607,"score_gpt":0.4224497992122344,"score_spread":0.10992072033442835,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4246475774","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009973089,0.00016418847,0.00020137378,0.00006477028,0.0011237246,0.00013976007,0.00003995654,0.000034034285,0.9882591],"genre_scores_gemma":[0.06343222,0.000046916797,0.0010737951,0.000069302325,0.000105149506,0.0000017562231,0.000004399458,0.000035653684,0.9352308],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9968391,0.000030796586,0.0011659543,0.0007042397,0.001035454,0.00022445525],"domain_scores_gemma":[0.99513227,0.0007831027,0.0014851206,0.0021084584,0.00035648627,0.00013457715],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002939252,0.00028231705,0.00086581614,0.0009290147,0.00018768625,0.0003224729,0.0019808533,0.0004112892,0.0067536724],"category_scores_gemma":[0.0013953978,0.00021253971,0.00039809084,0.000036238114,0.00024321285,0.000296733,0.00039811168,0.0002803985,0.0023850463],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014591657,0.000030337338,0.00077508343,0.000008927305,0.00003688061,0.00005653012,0.000094628725,0.000022168639,0.00023409224,0.16146497,0.08615054,0.7509799],"study_design_scores_gemma":[0.00014100625,0.00005394333,0.0000681306,0.0001428163,0.000019119787,0.000005119167,0.00001823367,0.00006386018,0.000116860785,0.496639,0.5025107,0.00022118402],"about_ca_topic_score_codex":0.000019775982,"about_ca_topic_score_gemma":0.000045886893,"teacher_disagreement_score":0.7507587,"about_ca_system_score_codex":0.00008464764,"about_ca_system_score_gemma":0.0002093702,"threshold_uncertainty_score":0.9983917},"labels":[],"label_agreement":null},{"id":"W4246619927","doi":"10.32920/14668917.v1","title":"The Effect of Time Pressure on Risky Financial Decisions from Description and Decisions from Experience","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Risk-seeking; Economics; Actuarial science; Psychology; Social psychology","score_opus":0.09418522141655992,"score_gpt":0.372694988609122,"score_spread":0.27850976719256204,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4246619927","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9864585,0.0016027435,0.0062689176,0.00016637908,0.0029139516,0.0005760113,0.0010500279,0.00005321236,0.00091029296],"genre_scores_gemma":[0.9937605,0.0006037296,0.0039857808,0.000080861704,0.00022238206,0.000082414575,0.00010637761,0.00003508081,0.0011228414],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9928228,0.0008968237,0.001898007,0.0019919234,0.0019832365,0.00040719882],"domain_scores_gemma":[0.9558487,0.039202526,0.0009805546,0.003220237,0.00046643676,0.00028156978],"candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002797134,0.00059473387,0.0013585337,0.00029500618,0.00067846634,0.0020227,0.0026088753,0.00076366396,0.0017827426],"category_scores_gemma":[0.033110842,0.00034233092,0.0005967209,0.00042813944,0.0004233432,0.0003530043,0.0030135917,0.0009477438,0.00039405184],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00062053587,0.00014224378,0.0071028657,0.0000013088436,0.000060186747,0.000029719911,0.001179315,0.00179335,0.0010866015,0.000054196888,0.014630015,0.9732997],"study_design_scores_gemma":[0.0043294234,0.002351964,0.26988456,0.0039785164,0.001244868,0.00002339149,0.0037238852,0.04964134,0.019116465,0.53248024,0.10986478,0.0033605911],"about_ca_topic_score_codex":0.0017928588,"about_ca_topic_score_gemma":0.00083129876,"teacher_disagreement_score":0.96993905,"about_ca_system_score_codex":0.00006711131,"about_ca_system_score_gemma":0.0002641985,"threshold_uncertainty_score":0.99990284},"labels":[],"label_agreement":null},{"id":"W4247480983","doi":"10.1207/s15327043hup2001_2","title":"The Effects of Self-Efficacy on Behavior in Escalation Situations","year":2007,"lang":"en","type":"article","venue":"Human Performance","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Psychology; Self-efficacy; Negative feedback; Social psychology; Interaction; Perception; Positive feedback; Statistics; Mathematics","score_opus":0.07204022670432507,"score_gpt":0.39500133980670166,"score_spread":0.3229611131023766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4247480983","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9969593,0.000021570413,0.000067906854,0.000027847673,0.00036859355,0.00024688273,8.683633e-7,0.000024026884,0.0022829575],"genre_scores_gemma":[0.99943155,0.00001495569,0.00014913347,0.000027201742,0.00004437129,0.000011710859,0.0000015453439,0.000007224409,0.00031228605],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99831927,0.000041763167,0.0006742683,0.00023355873,0.0005263175,0.00020479866],"domain_scores_gemma":[0.9970429,0.002050946,0.00024629218,0.00050838257,0.000106751264,0.00004476317],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002363322,0.0000953557,0.00015509466,0.00027691506,0.00032145882,0.00009093253,0.00046493084,0.000062070176,0.000031567553],"category_scores_gemma":[0.00053266634,0.000062247935,0.0000681337,0.00042453836,0.000073016614,0.00021361579,0.00005249858,0.00015440487,0.00021482947],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000039562117,0.0005616651,0.08533787,0.000004350381,0.0000022689533,0.0000047161675,0.0006817683,0.00022374715,0.0012024284,0.0010449842,0.0004052662,0.91049135],"study_design_scores_gemma":[0.00039697086,0.00026882126,0.9920553,0.000035224628,0.000008054164,0.0000018686883,0.00006548617,0.00070762506,0.0028306174,0.0017551783,0.0017829947,0.000091834445],"about_ca_topic_score_codex":0.000005712256,"about_ca_topic_score_gemma":0.0001106244,"teacher_disagreement_score":0.91039956,"about_ca_system_score_codex":0.00006745547,"about_ca_system_score_gemma":0.0000236638,"threshold_uncertainty_score":0.276127},"labels":[],"label_agreement":null},{"id":"W4247756014","doi":"10.4000/laboreal.6342","title":"Carga mental","year":2013,"lang":"es","type":"article","venue":"Laboreal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Cegep de Sept Iles","funders":"","keywords":"Psychology","score_opus":0.05235341542435849,"score_gpt":0.36610274286047706,"score_spread":0.31374932743611855,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4247756014","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9635284,0.00022394366,0.000027241103,0.0020123662,0.0027300667,0.00028384742,0.0003113492,0.00006059782,0.030822214],"genre_scores_gemma":[0.9941204,0.00010783875,0.0007953213,0.0006201642,0.0003314765,0.000017355502,0.000022850145,0.000027928112,0.0039566266],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9971363,0.00010877175,0.00077564776,0.0006828417,0.00079575676,0.00050066126],"domain_scores_gemma":[0.99791944,0.0003459523,0.0002595642,0.000851935,0.0003106498,0.00031248102],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00065246015,0.000273269,0.0004284794,0.00020409285,0.00024368725,0.0016452448,0.001015853,0.00021026806,0.008448003],"category_scores_gemma":[0.0002843037,0.00021004993,0.0001876819,0.0005456201,0.00020490277,0.00069301564,0.00032388212,0.00023661216,0.022730125],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014017036,0.00013302764,0.028525554,0.0000021233575,0.000012453619,0.000014912506,0.00041606496,0.0000052909936,0.00036989746,0.0018612776,0.14384009,0.8248053],"study_design_scores_gemma":[0.0008586938,0.00028686252,0.20471689,0.000078420686,0.000045497894,0.00003527491,0.0016183112,0.002062886,0.0006533422,0.05919455,0.729742,0.00070725556],"about_ca_topic_score_codex":0.0017651776,"about_ca_topic_score_gemma":0.00008589398,"teacher_disagreement_score":0.82409805,"about_ca_system_score_codex":0.00010169903,"about_ca_system_score_gemma":0.0001321056,"threshold_uncertainty_score":0.99939114},"labels":[],"label_agreement":null},{"id":"W4248008665","doi":"10.1002/0470018860.s00504","title":"Counterfactual Thinking","year":2005,"lang":"en","type":"other","venue":"Encyclopedia of Cognitive Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Counterfactual thinking; Computer science; Philosophy; Epistemology","score_opus":0.0572854262444517,"score_gpt":0.39306178538030895,"score_spread":0.33577635913585724,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4248008665","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018828552,0.000388077,0.0011081739,0.000060072194,0.002088717,0.00028795333,0.00024159177,0.00009548017,0.9769014],"genre_scores_gemma":[0.19509171,0.0004453433,0.0021333524,0.00024507203,0.00079842814,0.000012184459,0.000008022561,0.00019634147,0.80106956],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9938152,0.00008864002,0.0009587829,0.0012550454,0.0033585746,0.00052376324],"domain_scores_gemma":[0.99517107,0.0018687315,0.0012247541,0.000798908,0.00070805557,0.00022846823],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0039629866,0.00037462084,0.0007299624,0.0016404733,0.00019769992,0.00035294206,0.0029859527,0.00024285637,0.016883884],"category_scores_gemma":[0.007862601,0.00028831014,0.0001930589,0.0015114091,0.0020357615,0.0005426242,0.0005969772,0.00035092246,0.0033953346],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013394058,0.000083665844,0.0005960293,0.0000028100828,0.000007895899,0.00000982038,0.00067331764,0.0000032561024,0.00001258502,0.00021315065,0.11527528,0.8831088],"study_design_scores_gemma":[0.00035464257,0.00012388597,0.0015878986,0.0005780341,0.000040147053,0.000013261197,0.0015401071,0.000055782974,0.00014370696,0.016578346,0.9784172,0.0005669505],"about_ca_topic_score_codex":0.000081698345,"about_ca_topic_score_gemma":0.00021020396,"teacher_disagreement_score":0.88254184,"about_ca_system_score_codex":0.00007383847,"about_ca_system_score_gemma":0.00081039063,"threshold_uncertainty_score":0.9999569},"labels":[],"label_agreement":null},{"id":"W4249443823","doi":"10.31234/osf.io/5u9jq","title":"Valence bias in metacontrol of decision making in adolescents and young adults","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Deutsche Forschungsgemeinschaft","keywords":"Framing effect; Framing (construction); Psychology; Valence (chemistry); Cognition; Young adult; Developmental psychology; Social psychology; Cognitive psychology; Engineering","score_opus":0.1706091423540632,"score_gpt":0.4089149332879135,"score_spread":0.23830579093385032,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4249443823","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9928734,0.00053893914,0.0042665047,0.00014897363,0.0010341024,0.0005347408,0.00005073982,0.000024040604,0.00052856695],"genre_scores_gemma":[0.9935064,0.00013459778,0.0061191884,0.00013507977,0.000036956695,0.00001607015,0.0000021056555,0.000021584745,0.000028030085],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9941644,0.00028260003,0.0024720386,0.0015203531,0.0012193524,0.000341252],"domain_scores_gemma":[0.9964407,0.001270388,0.0009329315,0.0009922447,0.00022865518,0.00013509736],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0038700288,0.00037707583,0.0013254109,0.0011792714,0.000033193384,0.00034457212,0.0015351769,0.000397628,0.00011787464],"category_scores_gemma":[0.0061155474,0.00029515589,0.0002413933,0.00072970265,0.00010334635,0.00028399442,0.0021209053,0.0007842585,0.00007364702],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003848887,0.00011253577,0.36369222,0.000035014426,0.0000042285865,0.00007297204,0.00055819144,0.00084610167,0.000025498546,0.00003927884,0.00011994194,0.63410914],"study_design_scores_gemma":[0.0024857223,0.00012388009,0.6734869,0.007883719,0.00003738569,0.000020252748,0.0013549902,0.071224496,0.000081146536,0.24241611,0.00014363951,0.00074176595],"about_ca_topic_score_codex":0.0005381283,"about_ca_topic_score_gemma":0.0030408714,"teacher_disagreement_score":0.63336736,"about_ca_system_score_codex":0.000107404885,"about_ca_system_score_gemma":0.0001471393,"threshold_uncertainty_score":0.99995005},"labels":[],"label_agreement":null},{"id":"W4249899931","doi":"10.32920/ryerson.14646000","title":"Decision Making Under Risk Across Different Contexts","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Context (archaeology); Quality (philosophy); Event (particle physics); Decision quality; Rare events; Psychology; Actuarial science; Economics; Mathematics; Statistics; Operations management; Geography","score_opus":0.15248665554039428,"score_gpt":0.4659299394577652,"score_spread":0.31344328391737086,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4249899931","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.84186894,0.00051035907,0.14754844,0.00016682415,0.0070263105,0.00031858584,0.00022627946,0.00013918903,0.0021950768],"genre_scores_gemma":[0.9903536,0.00013906794,0.006890149,0.00043912945,0.0002591092,0.000028884338,0.000026043708,0.00006455643,0.0017994583],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9912567,0.00047512,0.0024613603,0.0026173438,0.0024136244,0.0007758543],"domain_scores_gemma":[0.9875289,0.006205528,0.0014665596,0.0036230178,0.0008729482,0.00030302053],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0041763,0.0007527568,0.0015974919,0.00037125498,0.00053055986,0.0055820607,0.0030280205,0.0009209911,0.004785048],"category_scores_gemma":[0.0045777257,0.0005149263,0.0011447088,0.0004240975,0.00019372925,0.00033403301,0.0073596435,0.0015846366,0.0012671294],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006958249,0.00019085135,0.012546929,0.0000040189266,0.000040999646,0.00007681997,0.00048456734,0.006640101,0.0000123740565,0.00013467674,0.004245225,0.9755539],"study_design_scores_gemma":[0.0009038629,0.000083913,0.15451862,0.00087621633,0.0001120914,0.00006475015,0.005371888,0.011683781,0.00017435457,0.81931376,0.0053649596,0.0015317786],"about_ca_topic_score_codex":0.00014387941,"about_ca_topic_score_gemma":0.0020321026,"teacher_disagreement_score":0.9740221,"about_ca_system_score_codex":0.00033488264,"about_ca_system_score_gemma":0.0002363606,"threshold_uncertainty_score":0.9997302},"labels":[],"label_agreement":null},{"id":"W4249947943","doi":"10.4324/9780203496398-12","title":"Egocentric Biases in Availability and Attribution","year":2004,"lang":"en","type":"book-chapter","venue":"Social Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":662,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Attribution; Psychology; Cognitive psychology; Social psychology","score_opus":0.26749866006345757,"score_gpt":0.40293785381664093,"score_spread":0.13543919375318336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4249947943","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.70549244,0.00045753695,0.00013781294,0.00067996583,0.00077169936,0.00066759984,0.0007940764,0.00009150636,0.29090738],"genre_scores_gemma":[0.98854977,0.00012848983,0.00004259949,0.00010558341,0.00021889026,0.000007037018,0.00017238614,0.000021557864,0.010753695],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9976394,0.00006449746,0.00078554836,0.0006447644,0.00064311153,0.00022268617],"domain_scores_gemma":[0.99834466,0.00061654137,0.00042551677,0.00019385244,0.00034150897,0.00007791184],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0015895213,0.00022777343,0.00046167677,0.000426914,0.00022516945,0.00022833486,0.00018701439,0.0004925657,0.0017384957],"category_scores_gemma":[0.0011698392,0.0002164677,0.00016971366,0.00015588985,0.00021904444,0.00023571975,0.000111798676,0.00034757503,0.00088703283],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000085898464,0.00008076772,0.0006432038,0.000009084642,0.000008720968,0.00003310575,0.00021063711,0.00000485723,0.000012431805,0.020538846,0.001272816,0.97709966],"study_design_scores_gemma":[0.0004924303,0.000053785374,0.005928543,0.00012579923,0.000046302936,0.000005398565,0.0000785977,0.000012062178,0.000014585553,0.9754374,0.017527021,0.00027808375],"about_ca_topic_score_codex":0.000035686924,"about_ca_topic_score_gemma":0.0002445705,"teacher_disagreement_score":0.97682154,"about_ca_system_score_codex":0.00040790284,"about_ca_system_score_gemma":0.00017317932,"threshold_uncertainty_score":0.99989086},"labels":[],"label_agreement":null},{"id":"W4250931847","doi":"10.31234/osf.io/b5a2m","title":"The effort paradox: Effort is both costly and valued","year":2017,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":79,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Cognition; Value (mathematics); Mental effort; Control (management); Cognitive psychology; Psychology; Computer science; Risk analysis (engineering); Artificial intelligence; Neuroscience; Machine learning; Business","score_opus":0.17902761388057345,"score_gpt":0.43514533283013374,"score_spread":0.25611771894956026,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4250931847","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94348884,0.00066253444,0.00076895655,0.002159551,0.003992445,0.0007531977,0.000081822196,0.000090975496,0.04800171],"genre_scores_gemma":[0.9639222,0.0005532145,0.0021794736,0.00091446674,0.0002781259,0.000058530368,0.000008913089,0.000045467084,0.032039635],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9952837,0.00007940731,0.0012831498,0.001445177,0.0014153633,0.00049315067],"domain_scores_gemma":[0.9929561,0.0013096145,0.0010609761,0.004102694,0.00029411743,0.00027650967],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0065653496,0.00046500794,0.00085865904,0.00019424962,0.0012495617,0.005384549,0.003718776,0.0004969085,0.0004900523],"category_scores_gemma":[0.001293952,0.00025121745,0.0004383923,0.00009020938,0.0005122163,0.00025396276,0.0032500986,0.00074126787,0.0010246313],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000066713146,0.000043781336,0.019498192,0.000005062185,0.000043148997,0.00002091535,0.0002457656,0.000038556762,0.0000028470922,0.0014238212,0.10646262,0.8721486],"study_design_scores_gemma":[0.00043225705,0.00007812563,0.04347665,0.000089389825,0.00007893471,0.00003585694,0.0002781199,0.0048019197,0.000079856436,0.5868706,0.36314416,0.00063409074],"about_ca_topic_score_codex":0.00029237763,"about_ca_topic_score_gemma":0.00023835021,"teacher_disagreement_score":0.8715145,"about_ca_system_score_codex":0.00007571284,"about_ca_system_score_gemma":0.00029474974,"threshold_uncertainty_score":0.999994},"labels":[],"label_agreement":null},{"id":"W4250934738","doi":"10.1007/978-3-319-24612-3_3","title":"Balanced Inventory of Desirable Responding","year":2020,"lang":"en","type":"book-chapter","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":22,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Psychology; Computer science","score_opus":0.2834393150543603,"score_gpt":0.3908684707216172,"score_spread":0.10742915566725686,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4250934738","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005801737,0.00016405758,0.00049710536,0.00021462509,0.00074314,0.00015480864,0.00004629885,0.000057426794,0.9923208],"genre_scores_gemma":[0.08134076,0.000035962912,0.002158552,0.00037632752,0.00013131792,0.000001985678,0.000007767655,0.000048867973,0.91589844],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99664235,0.000037706923,0.0013183878,0.00074954744,0.0010665777,0.00018545389],"domain_scores_gemma":[0.9969221,0.00088652613,0.00083263713,0.0009199174,0.00026177953,0.00017705541],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001603399,0.00027804592,0.00085947826,0.0007441594,0.0000686776,0.00015107456,0.0012025094,0.00033067397,0.0076066167],"category_scores_gemma":[0.0010077838,0.00021518517,0.00038918943,0.00016530989,0.00013464804,0.00018147424,0.00034600295,0.00031169658,0.0032281901],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025208743,0.00003278094,0.00049394387,0.000015294281,0.000049912425,0.00008796064,0.0001708507,0.00006251134,0.000599297,0.39213252,0.15306936,0.45303348],"study_design_scores_gemma":[0.0001465474,0.00009184779,0.0000217283,0.00009241566,0.000022281187,0.0000040743876,0.00004735449,0.00019600887,0.0001853001,0.50125575,0.49769315,0.00024353187],"about_ca_topic_score_codex":0.0000070443166,"about_ca_topic_score_gemma":0.000011517343,"teacher_disagreement_score":0.45278993,"about_ca_system_score_codex":0.00008112879,"about_ca_system_score_gemma":0.00019051746,"threshold_uncertainty_score":0.9975479},"labels":[],"label_agreement":null},{"id":"W4251314509","doi":"10.5539/ijsp.v8n6p79","title":"Expected Winning Probabilities in Sequential Truels under Uniform Distributions","year":2019,"lang":"en","type":"article","venue":"International Journal of Statistics and Probability","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Mathematics; Conjecture; Sequential estimation; Mathematical economics; Computer science; Mathematical optimization; Combinatorics","score_opus":0.08631143428977427,"score_gpt":0.38676363064836405,"score_spread":0.3004521963585898,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4251314509","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9618583,0.000032546002,0.035447873,0.00075473735,0.0010734439,0.00012560587,0.000367384,0.000004750474,0.0003354098],"genre_scores_gemma":[0.9844346,0.000013848308,0.015341288,0.00005039755,0.000058895064,0.0000018556032,0.000012000117,0.0000049532246,0.000082156614],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99750334,0.00011492237,0.0011829275,0.00024138394,0.0008111865,0.00014626856],"domain_scores_gemma":[0.99679786,0.0011794614,0.0005323569,0.00019215373,0.0012120091,0.00008614423],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022443149,0.00011058784,0.00029363018,0.00023761817,0.00004452262,0.00034532807,0.00049953355,0.00006156328,0.00050371146],"category_scores_gemma":[0.0017842102,0.000083496685,0.00007801097,0.00016799624,0.00012604705,0.00042683975,0.0001302578,0.00022815968,0.000020771411],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00066394184,0.00065793504,0.46431506,0.000017502654,0.00009873882,0.00008123661,0.0016571135,0.0060531944,0.0005022705,0.19269003,0.0013694327,0.33189353],"study_design_scores_gemma":[0.000600776,0.00012700011,0.08052031,0.000044272994,0.00000733031,0.00006538594,0.00047817684,0.0014563942,0.000048515256,0.9144777,0.0020703287,0.0001037889],"about_ca_topic_score_codex":0.00004846384,"about_ca_topic_score_gemma":0.00010584647,"teacher_disagreement_score":0.7217877,"about_ca_system_score_codex":0.00023696406,"about_ca_system_score_gemma":0.00021178971,"threshold_uncertainty_score":0.55152875},"labels":[],"label_agreement":null},{"id":"W4251657215","doi":"10.1017/s0012217318000094","title":"Testing Rationality","year":2018,"lang":"en","type":"article","venue":"Dialogue","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Trent University","funders":"","keywords":"Irrationality; Rationality; Suspect; Decision theory; Expected utility hypothesis; Evidential decision theory; Psychology; Subjective expected utility; Decision problem; Test (biology); Ecological rationality; Causal decision theory; Prospect theory; Social psychology; Mathematical economics; Decision analysis; Epistemology; Computer science; Economics; Business decision mapping; Microeconomics; Evidential reasoning approach; Philosophy; Criminology","score_opus":0.3648410174443131,"score_gpt":0.4480813042545267,"score_spread":0.08324028681021362,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4251657215","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9650136,0.0000062834315,0.0018406962,0.0002985558,0.0009992605,0.000049239043,0.000022015945,0.00004407875,0.031726237],"genre_scores_gemma":[0.9946976,1.5138983e-7,0.0039605806,0.0004751253,0.000533656,0.0000029913303,0.00000547043,0.00000518202,0.00031929076],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986547,0.000069863425,0.00040127785,0.0003236321,0.00040121592,0.0001492613],"domain_scores_gemma":[0.9974789,0.0014535391,0.00013369307,0.00043386908,0.0004270699,0.00007290943],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0018767308,0.00007125733,0.00013994881,0.00009151882,0.0001944729,0.00024916872,0.00044138092,0.00005124293,0.00067134056],"category_scores_gemma":[0.00795786,0.000053141986,0.000053972708,0.00040924083,0.00014371071,0.00020659505,0.000103507045,0.00006000029,0.0057905074],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010163454,0.000042888434,0.055967644,2.3086112e-7,0.0000019839367,0.0000046167347,0.00022346212,0.00001560258,0.000759922,0.0020248236,0.021535976,0.9194127],"study_design_scores_gemma":[0.00021717246,0.000111065885,0.21213819,0.000008577001,0.0000057592874,0.0000124678945,0.00012239147,0.0016465138,0.00074707624,0.6822956,0.1024885,0.00020666722],"about_ca_topic_score_codex":0.000057975973,"about_ca_topic_score_gemma":0.00009901985,"teacher_disagreement_score":0.919206,"about_ca_system_score_codex":0.000022643588,"about_ca_system_score_gemma":0.00006598899,"threshold_uncertainty_score":0.9949836},"labels":[],"label_agreement":null},{"id":"W4251696374","doi":"10.31234/osf.io/g7jdm","title":"The conflict negativity: Neural correlate of value conflict and indecision during financial decision making","year":2017,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Negativity effect; Psychology; Perception; Social psychology; Odds; Value (mathematics); Stock (firearms); Cognitive psychology; Logistic regression; Computer science","score_opus":0.13344630884352715,"score_gpt":0.4156993564868871,"score_spread":0.28225304764335996,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4251696374","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9868345,0.0011579602,0.003216017,0.00032117643,0.0049466817,0.00069148035,0.0000973027,0.00006518084,0.0026696639],"genre_scores_gemma":[0.99560344,0.0007645485,0.002113278,0.00010087662,0.0002254453,0.000021217083,0.0000031603545,0.0000514979,0.0011165536],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9921514,0.0003985697,0.0027195385,0.0017977627,0.0022743181,0.000658406],"domain_scores_gemma":[0.9795676,0.012419459,0.0032048114,0.003732022,0.00083115447,0.00024496898],"candidate_categories":["metaresearch","metaepi_narrow","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.007227269,0.000709519,0.0015703076,0.00060746283,0.0017165926,0.0031433597,0.0037881199,0.0009055492,0.00013957656],"category_scores_gemma":[0.022562576,0.00044185488,0.0006242745,0.00025976804,0.0009117755,0.0005443319,0.006547945,0.0015630436,0.0001068045],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00057230867,0.000055881756,0.0071777836,0.000012151084,0.000023498185,0.00005193126,0.00047856936,0.0026660846,0.00009507597,0.00063711725,0.0018255769,0.986404],"study_design_scores_gemma":[0.002390257,0.00029493126,0.39111266,0.0018609423,0.00018020012,0.00020903385,0.00047290628,0.07787221,0.00056577707,0.49391133,0.029517794,0.0016119743],"about_ca_topic_score_codex":0.0001897718,"about_ca_topic_score_gemma":0.00021863179,"teacher_disagreement_score":0.98479205,"about_ca_system_score_codex":0.00011788055,"about_ca_system_score_gemma":0.00039374316,"threshold_uncertainty_score":0.9998033},"labels":[],"label_agreement":null},{"id":"W4252203010","doi":"10.31234/osf.io/vphgc","title":"Biased confabulation in risky choice","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Leverhulme Trust","keywords":"Confabulation (neural networks); Recall; Psychology; Cognitive psychology; Task (project management); Encoding (memory); Context (archaeology); Value (mathematics); Episodic memory; Memory errors; Cognition; Social psychology; Decision quality; Computer science; Machine learning","score_opus":0.42276926828582717,"score_gpt":0.48276778350862376,"score_spread":0.05999851522279659,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4252203010","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9730009,0.000043773583,0.0040720208,0.0026598892,0.0016984405,0.0003462835,0.000052927207,0.000101239864,0.01802456],"genre_scores_gemma":[0.99555767,0.000011117551,0.0026103782,0.0006723405,0.00017666032,0.000015120725,0.00003249078,0.000019268778,0.0009049306],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9961738,0.00018728027,0.0013606509,0.0011690189,0.00087744533,0.00023181387],"domain_scores_gemma":[0.9960205,0.0019936718,0.0005497924,0.0010697,0.00020644326,0.00015992635],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0019893125,0.00026210217,0.0006550741,0.00051772676,0.000051869694,0.0007677436,0.0013383555,0.00039520185,0.002219045],"category_scores_gemma":[0.004953171,0.00020829187,0.00022984017,0.0005105018,0.000053721884,0.00017641515,0.0010314138,0.00068720785,0.0026322054],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000059116504,0.00013360078,0.07175814,0.000007705288,0.000010077475,0.000041393963,0.0004154727,0.013572666,0.000111613874,0.000601882,0.026087424,0.8872009],"study_design_scores_gemma":[0.000855865,0.000058938633,0.18060939,0.000119086224,0.000026083835,0.0000030032713,0.00033064233,0.09844672,0.00018812768,0.6262025,0.092374444,0.0007851711],"about_ca_topic_score_codex":0.00086839043,"about_ca_topic_score_gemma":0.0009002338,"teacher_disagreement_score":0.8864157,"about_ca_system_score_codex":0.0001171111,"about_ca_system_score_gemma":0.00022163318,"threshold_uncertainty_score":0.99869305},"labels":[],"label_agreement":null},{"id":"W4252793816","doi":"10.31234/osf.io/ueymx","title":"Worse is Bad: Divergent Inferences From Logically Equivalent Comparisons","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Framing (construction); Framing effect; Logical equivalence; Markedness; Psychology; Linguistics; Social psychology; Econometrics; Mathematics; Philosophy; Equivalence (formal languages)","score_opus":0.4223242593578988,"score_gpt":0.45951297667675856,"score_spread":0.037188717318859754,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4252793816","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9492376,0.0003954629,0.017503694,0.0017020268,0.006925703,0.00046836722,0.0007981318,0.00014289597,0.022826143],"genre_scores_gemma":[0.98066556,0.00022965719,0.009925894,0.00086024014,0.00020892914,0.00002360791,0.000082655555,0.000024322278,0.007979133],"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99277294,0.00025189383,0.0020723897,0.0021806145,0.0021736696,0.00054850295],"domain_scores_gemma":[0.99313027,0.002015822,0.0011016888,0.0028439288,0.0005347692,0.00037352493],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0019412874,0.00062305504,0.0014581729,0.0003134176,0.00018902392,0.0018129911,0.004292912,0.00072013744,0.053086735],"category_scores_gemma":[0.0005547497,0.00040978147,0.00072284724,0.00029822724,0.00019131345,0.00022985457,0.0069903517,0.0009933538,0.023293277],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010570544,0.00066169107,0.2220712,0.000008782757,0.00016063085,0.000043608758,0.00075290096,0.0073980433,0.000024592597,0.00088814576,0.38794467,0.37994],"study_design_scores_gemma":[0.00073561596,0.00022938204,0.15693924,0.00047018516,0.00022044296,0.0000034212758,0.0019728718,0.017242787,0.00016683615,0.6199647,0.20009474,0.0019597374],"about_ca_topic_score_codex":0.0012934534,"about_ca_topic_score_gemma":0.0002684816,"teacher_disagreement_score":0.6190766,"about_ca_system_score_codex":0.00015040491,"about_ca_system_score_gemma":0.0003866321,"threshold_uncertainty_score":0.99983543},"labels":[],"label_agreement":null},{"id":"W4253273833","doi":"10.24124/2010/bpgub639","title":"Can the magnitude of the belief-bias in causal reasoning be attenuated through the manipulation of content?","year":2010,"lang":"en","type":"dissertation","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Library and Archives Canada","funders":"","keywords":"Content (measure theory); Psychology; Causal model; Causal reasoning; Social psychology; Health belief model; Confirmation bias; Cognitive psychology; Developmental psychology; Cognition; Mathematics; Statistics; Medicine; Public health; Psychiatry","score_opus":0.2924260782582968,"score_gpt":0.41928156086085894,"score_spread":0.12685548260256213,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4253273833","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9882756,0.00006525569,0.000014206241,0.0016926744,0.0015177267,0.00053556653,0.000055000317,0.000011146122,0.007832822],"genre_scores_gemma":[0.99156696,0.000017906377,0.0001906005,0.0002372204,0.00004891895,0.000018343315,0.00006960488,0.000023718487,0.007826752],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9961971,0.00032538024,0.001547314,0.00045975333,0.0012405425,0.00022988263],"domain_scores_gemma":[0.99432415,0.0018773366,0.0016606865,0.0013319198,0.0007770304,0.00002890607],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027866992,0.00026232362,0.00054542726,0.00014298836,0.00023983046,0.00017811534,0.0019257014,0.00034790515,0.00036262264],"category_scores_gemma":[0.0034923812,0.000107735235,0.0002880994,0.00072812865,0.000214711,0.00017061335,0.0001518953,0.0007187644,0.000017524519],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012134506,0.0010560272,0.25430724,0.00008174787,0.00027675732,0.000022396629,0.06415662,0.00437309,0.018865498,0.045613244,0.020079901,0.589954],"study_design_scores_gemma":[0.00079050387,0.00011405658,0.88852215,0.0004273598,0.00019378809,0.000013947931,0.04247218,0.0015894442,0.0067554815,0.054918762,0.0037378846,0.00046444856],"about_ca_topic_score_codex":0.0109695615,"about_ca_topic_score_gemma":0.11783244,"teacher_disagreement_score":0.6342149,"about_ca_system_score_codex":0.000048176968,"about_ca_system_score_gemma":0.00022219501,"threshold_uncertainty_score":0.9956165},"labels":[],"label_agreement":null},{"id":"W4253476940","doi":"10.32920/14668917","title":"The Effect of Time Pressure on Risky Financial Decisions from Description and Decisions from Experience","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Risk-seeking; Economics; Actuarial science; Psychology; Social psychology","score_opus":0.09418522141655992,"score_gpt":0.372694988609122,"score_spread":0.27850976719256204,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4253476940","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9864585,0.0016027435,0.0062689176,0.00016637908,0.0029139516,0.0005760113,0.0010500279,0.00005321236,0.00091029296],"genre_scores_gemma":[0.9937605,0.0006037296,0.0039857808,0.000080861704,0.00022238206,0.000082414575,0.00010637761,0.00003508081,0.0011228414],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9928228,0.0008968237,0.001898007,0.0019919234,0.0019832365,0.00040719882],"domain_scores_gemma":[0.9558487,0.039202526,0.0009805546,0.003220237,0.00046643676,0.00028156978],"candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002797134,0.00059473387,0.0013585337,0.00029500618,0.00067846634,0.0020227,0.0026088753,0.00076366396,0.0017827426],"category_scores_gemma":[0.033110842,0.00034233092,0.0005967209,0.00042813944,0.0004233432,0.0003530043,0.0030135917,0.0009477438,0.00039405184],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00062053587,0.00014224378,0.0071028657,0.0000013088436,0.000060186747,0.000029719911,0.001179315,0.00179335,0.0010866015,0.000054196888,0.014630015,0.9732997],"study_design_scores_gemma":[0.0043294234,0.002351964,0.26988456,0.0039785164,0.001244868,0.00002339149,0.0037238852,0.04964134,0.019116465,0.53248024,0.10986478,0.0033605911],"about_ca_topic_score_codex":0.0017928588,"about_ca_topic_score_gemma":0.00083129876,"teacher_disagreement_score":0.96993905,"about_ca_system_score_codex":0.00006711131,"about_ca_system_score_gemma":0.0002641985,"threshold_uncertainty_score":0.99990284},"labels":[],"label_agreement":null},{"id":"W4253539784","doi":"10.32920/14638635","title":"Decisions from experience: adaptive information search and choice in younger and older adults","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Canadian Institutes of Health Research","keywords":"Cognition; Psychology; Neuropsychology; Valence (chemistry); Affect (linguistics); Cognitive psychology; Psychiatry","score_opus":0.14043805600269083,"score_gpt":0.40797124856968847,"score_spread":0.26753319256699765,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4253539784","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99356896,0.00042164157,0.0035070835,0.0001896875,0.00067539816,0.00039930365,0.00011011029,0.000027909473,0.0010998888],"genre_scores_gemma":[0.9906441,0.00024052884,0.0085157,0.00029446618,0.000052775522,0.00004686321,0.00005296439,0.000011008784,0.00014158746],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9961761,0.00017311393,0.0012408628,0.0010331705,0.0010816661,0.00029507533],"domain_scores_gemma":[0.99507064,0.0029900172,0.00024080074,0.0009380035,0.00052923005,0.00023133896],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0013212576,0.00030717684,0.00061629317,0.0006302789,0.0001380118,0.002011359,0.0007020536,0.00045285153,0.00089909544],"category_scores_gemma":[0.0028076833,0.0002378082,0.00009762573,0.00041334744,0.00017368396,0.0019120778,0.0025169707,0.00068475597,0.00010518622],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008370026,0.00006505053,0.022248738,0.000002822323,0.000008135606,0.000015034209,0.0153067,0.00025006002,0.000009602597,0.000053049203,0.00033804262,0.9616191],"study_design_scores_gemma":[0.0013623008,0.000060319337,0.8735616,0.00087144034,0.000019443398,0.000015478972,0.06756502,0.03976323,0.00010749879,0.01447827,0.0014583564,0.0007370511],"about_ca_topic_score_codex":0.0061370153,"about_ca_topic_score_gemma":0.0021790736,"teacher_disagreement_score":0.960882,"about_ca_system_score_codex":0.000090672445,"about_ca_system_score_gemma":0.00021245408,"threshold_uncertainty_score":0.9990246},"labels":[],"label_agreement":null},{"id":"W4254003416","doi":"10.1007/978-94-007-0753-5_103425","title":"Rational Behavior","year":2014,"lang":"en","type":"book-chapter","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brandon University; University of Northern British Columbia","funders":"","keywords":"Computer science","score_opus":0.21160128680386206,"score_gpt":0.40237257812064636,"score_spread":0.1907712913167843,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4254003416","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0022394876,0.000035218465,0.0023757357,0.0002522929,0.0015159143,0.00018614769,0.00006719826,0.000073262774,0.9932547],"genre_scores_gemma":[0.017608892,0.00000786901,0.001561011,0.00053452427,0.00041503055,0.000009826477,0.000034608645,0.000042001862,0.9797862],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9964859,0.000021728738,0.0010981067,0.00082077563,0.0013816926,0.00019178144],"domain_scores_gemma":[0.99692357,0.0008897542,0.0004976338,0.0011078294,0.00041523206,0.00016598735],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0013999902,0.0003166078,0.0005821284,0.0004129711,0.00013421795,0.0005095006,0.0010674957,0.00043540986,0.049267754],"category_scores_gemma":[0.00033200835,0.0002287004,0.00040438646,0.00003795598,0.0001296525,0.00012299884,0.00023612303,0.00030737987,0.033959724],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000054633533,0.000011178257,0.00006095533,3.239959e-7,0.000004131707,0.000013046919,0.0000070985566,0.0000046332607,0.0000036881227,0.19977428,0.120592676,0.6795225],"study_design_scores_gemma":[0.00007807658,0.00003365099,0.000111760484,0.000010524261,0.000025487096,0.000016797778,0.000004219524,0.00003970048,0.000004306952,0.32687464,0.6725711,0.00022971936],"about_ca_topic_score_codex":0.0000051275256,"about_ca_topic_score_gemma":0.00005097146,"teacher_disagreement_score":0.6792928,"about_ca_system_score_codex":0.00006699811,"about_ca_system_score_gemma":0.00013027102,"threshold_uncertainty_score":0.96679246},"labels":[],"label_agreement":null},{"id":"W4255226570","doi":"10.1167/14.10.1029","title":"Probability Cues Enhance Perceptual Estimations","year":2014,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Cued speech; Kurtosis; Perception; Probability distribution; Psychology; Computer science; Statistics; Cognitive psychology; Mathematics","score_opus":0.13127397038766372,"score_gpt":0.4414980236351232,"score_spread":0.3102240532474595,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4255226570","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96900016,0.000034376008,0.02753137,0.0010599943,0.0007738887,0.000053023192,0.0000022691327,0.000010706786,0.0015342034],"genre_scores_gemma":[0.9728615,0.0000076044034,0.026611393,0.00010655537,0.00019237857,5.2829193e-7,3.323854e-7,0.000006430591,0.00021325401],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9972753,0.00021170356,0.0011733255,0.00023037226,0.0009636779,0.00014561773],"domain_scores_gemma":[0.9965188,0.0013409756,0.0007906574,0.00044838482,0.0007546322,0.00014653718],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005538271,0.00010460511,0.00034185368,0.00024644655,0.00015057664,0.00030870692,0.00068879547,0.000075156975,0.0005455508],"category_scores_gemma":[0.006893858,0.00006613566,0.00022050763,0.00027555143,0.00010022639,0.0007507241,0.000095943804,0.00022158795,0.00047051822],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000041088097,0.00017362548,0.0027388567,0.0000013017705,0.0000027229019,0.0000026555986,0.00033273484,0.0010163902,0.0019924887,0.00022721954,0.010044288,0.98342663],"study_design_scores_gemma":[0.00065550185,0.0016133914,0.20344417,0.00019051395,0.000039050406,0.00016912773,0.0005356412,0.013984524,0.00093442324,0.69742703,0.08068411,0.00032252216],"about_ca_topic_score_codex":0.000003653807,"about_ca_topic_score_gemma":0.0000104455385,"teacher_disagreement_score":0.9831041,"about_ca_system_score_codex":0.00006329586,"about_ca_system_score_gemma":0.00007479559,"threshold_uncertainty_score":0.825309},"labels":[],"label_agreement":null},{"id":"W4256517360","doi":"10.4309/jgi.2009.23.10","title":"Neuroeconomics: A Guide to the New Science of Making Choices","year":2009,"lang":"en","type":"article","venue":"Journal of Gambling Issues","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Neuroeconomics; Psychology; Humanities; Cognitive psychology; Philosophy","score_opus":0.2841576854003311,"score_gpt":0.5093635788632356,"score_spread":0.22520589346290448,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4256517360","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98296016,0.0005639301,0.001892466,0.011423996,0.0011878462,0.00007424148,0.0000015635641,0.000008367487,0.0018874051],"genre_scores_gemma":[0.9797019,0.000053506577,0.01779925,0.0009814125,0.00062232127,1.5015829e-7,2.8894817e-8,0.0000069935354,0.0008344351],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99676657,0.000057740373,0.0015549951,0.00028247936,0.0010790133,0.00025921117],"domain_scores_gemma":[0.996506,0.00064301677,0.0013246497,0.00057877175,0.0007602606,0.00018729964],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0067474893,0.00012987283,0.0004522856,0.0008301182,0.00018742452,0.0007977423,0.0025535584,0.00003785851,0.00009650929],"category_scores_gemma":[0.005486567,0.00007630165,0.00020880278,0.000930729,0.00012031489,0.0008553843,0.00015011942,0.00020250992,0.00009705193],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009863272,0.00006149759,0.0014249928,8.780729e-7,0.000007087684,0.000018704935,0.0014130414,0.011911453,0.005959306,0.00043714404,0.033999335,0.94466794],"study_design_scores_gemma":[0.0006056161,0.0012651539,0.02111393,0.00032111572,0.000048845155,0.00028127962,0.0020729727,0.002332641,0.010919956,0.07315355,0.8875561,0.0003288746],"about_ca_topic_score_codex":0.000024795248,"about_ca_topic_score_gemma":0.0000210798,"teacher_disagreement_score":0.94433904,"about_ca_system_score_codex":0.000063659514,"about_ca_system_score_gemma":0.00036391438,"threshold_uncertainty_score":0.76926476},"labels":[],"label_agreement":null},{"id":"W4280552674","doi":"10.1287/mksc.2022.1364","title":"The Importance of Selling Formats: When Integrating Purchase and Quantity Decisions Increases Sales","year":2022,"lang":"en","type":"article","venue":"Marketing Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Business; Marketing; Sales management; Advertising","score_opus":0.09148159845372901,"score_gpt":0.3746963510346606,"score_spread":0.2832147525809316,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4280552674","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9967136,0.00044330404,0.0010496357,0.00035062595,0.00032917282,0.00013562018,0.000031164076,0.000028906503,0.00091796654],"genre_scores_gemma":[0.99229616,0.000045942255,0.0074042706,0.00012244894,0.00001953915,0.000013261436,9.631991e-7,0.0000075776065,0.00008983776],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9957536,0.0004214995,0.0010386928,0.0006257631,0.0017571895,0.00040328506],"domain_scores_gemma":[0.9834796,0.014355974,0.00078665116,0.00085157965,0.00037335837,0.0001528],"candidate_categories":["metaresearch","sts"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.042423736,0.00013940902,0.00026116348,0.0003163365,0.0035822561,0.00081262004,0.0021303492,0.00002339958,0.00010714006],"category_scores_gemma":[0.045500007,0.00008917958,0.00008965316,0.0013601636,0.001032032,0.0006732833,0.0015204168,0.00027005954,0.000009167583],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014622559,0.00007928426,0.29217035,0.0000026350995,0.000003317108,0.000009346653,0.0009653996,0.00043640655,0.0014412123,0.0024507192,0.0012193902,0.70107573],"study_design_scores_gemma":[0.0011330129,0.00055209943,0.24761578,0.00038655245,0.000055528642,0.00044460263,0.08955842,0.20985962,0.00096234813,0.39643997,0.051654905,0.0013371424],"about_ca_topic_score_codex":0.000107639244,"about_ca_topic_score_gemma":0.00021915599,"teacher_disagreement_score":0.69973856,"about_ca_system_score_codex":0.00008853812,"about_ca_system_score_gemma":0.00027480762,"threshold_uncertainty_score":0.99771494},"labels":[],"label_agreement":null},{"id":"W4281766773","doi":"10.1016/j.ijpsycho.2022.05.014","title":"Decision-making in uncertain contexts: The role of autonomic markers in resolving indecision","year":2022,"lang":"en","type":"article","venue":"International Journal of Psychophysiology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; St. Joseph’s Healthcare Hamilton","funders":"National Science Foundation","keywords":"Psychology; Impulsivity; Skin conductance; Context (archaeology); Moderation; Deliberation; Social psychology; Developmental psychology; Medicine","score_opus":0.03541866394613039,"score_gpt":0.3982517453826542,"score_spread":0.36283308143652376,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281766773","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99426,0.00040921566,0.00035329972,0.00068362174,0.0035349717,0.00010586821,0.000023147459,0.0000029470173,0.00062690553],"genre_scores_gemma":[0.9981084,0.000043336593,0.0012973758,0.00038359742,0.00012680696,0.0000072807616,0.0000012082562,0.000012024437,0.000020003119],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9953071,0.00059055956,0.0022861257,0.00035490564,0.0012373644,0.00022398608],"domain_scores_gemma":[0.9915266,0.0059623905,0.0016334846,0.0004119631,0.0004198142,0.000045733956],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005457117,0.00014803662,0.0005106191,0.0015574722,0.00008556611,0.00008222888,0.0030531532,0.00007800586,0.00084745587],"category_scores_gemma":[0.0027643107,0.00010399825,0.0002787857,0.00064703636,0.00013326915,0.00030335196,0.00053716876,0.000666653,0.00002055337],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0029103195,0.0002561207,0.021048715,2.9391637e-7,0.00002902123,0.00009913188,0.00084882666,0.05924481,0.0049597225,0.00043942322,0.0011104957,0.90905315],"study_design_scores_gemma":[0.0019568582,0.00045129473,0.15651365,0.00017249848,0.0000069678567,0.00023082452,0.0059858295,0.009395404,0.00007225836,0.8089938,0.016032217,0.00018838204],"about_ca_topic_score_codex":0.00008501005,"about_ca_topic_score_gemma":0.00009774959,"teacher_disagreement_score":0.90886474,"about_ca_system_score_codex":0.0004295928,"about_ca_system_score_gemma":0.00024114353,"threshold_uncertainty_score":0.9279048},"labels":[],"label_agreement":null},{"id":"W4281900369","doi":"10.1111/cjag.12308","title":"A portion cap rule with two products: An experimental evaluation","year":2022,"lang":"en","type":"article","venue":"Canadian Journal of Agricultural Economics/Revue canadienne d agroeconomie","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"National Institute of Food and Agriculture","keywords":"Intuition; Valuation (finance); Microeconomics; Business; Economics; Marketing; Psychology","score_opus":0.11726685266222571,"score_gpt":0.29174773731671455,"score_spread":0.17448088465448885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281900369","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9930399,0.00028966786,0.000004055094,0.002261592,0.002724699,0.0004614857,0.00023079276,0.000011031486,0.0009767772],"genre_scores_gemma":[0.9977789,0.0000031711481,0.00045483065,0.00034888924,0.0007667904,0.000051765757,0.00009540008,0.00003337816,0.00046688502],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9961855,0.00028079623,0.0017762992,0.0008263181,0.00014587767,0.00078523246],"domain_scores_gemma":[0.99472535,0.00015221606,0.0018942341,0.0006639355,0.00089068426,0.0016735955],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0039971797,0.00037118245,0.00074801646,0.0008553114,0.00086859416,0.00070767343,0.0014948185,0.00007746061,0.0031326734],"category_scores_gemma":[0.00033534935,0.00029217004,0.00024929867,0.0004512628,0.00014962108,0.0019766898,0.00007579014,0.0004756963,0.00007392036],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009155679,0.0005136537,0.024329264,0.000014273372,0.00039174996,0.0006320629,0.015456681,0.6917976,0.0022100757,0.008123064,0.029582392,0.22603358],"study_design_scores_gemma":[0.01794082,0.017435525,0.24745509,0.00021040851,0.001021538,0.03628931,0.24027695,0.015301855,0.0042660167,0.102944106,0.30960113,0.0072572664],"about_ca_topic_score_codex":0.020469662,"about_ca_topic_score_gemma":0.53828555,"teacher_disagreement_score":0.6764958,"about_ca_system_score_codex":0.005326194,"about_ca_system_score_gemma":0.0029260651,"threshold_uncertainty_score":0.99995303},"labels":[],"label_agreement":null},{"id":"W4281969102","doi":"10.1017/s0140525x22001157","title":"Conviction Narrative Theory: A theory of choice under radical uncertainty","year":2022,"lang":"en","type":"article","venue":"Behavioral and Brain Sciences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":116,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Economic and Social Research Council; Engineering and Physical Sciences Research Council; Aarhus Universitets Forskningsfond; University of Cambridge; UK Research and Innovation; Aarhus Universitet","keywords":"Narrative; Conviction; Psychology; Futures contract; Cognition; Mental representation; Vocabulary; Cognitive psychology; Deliberation; Epistemology; Social psychology; Linguistics; Economics","score_opus":0.1813556990338463,"score_gpt":0.4260144985023377,"score_spread":0.2446587994684914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281969102","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99604887,0.00014474499,0.00045807325,0.0018224315,0.000587009,0.00017795619,0.00007115896,0.000030308942,0.00065945537],"genre_scores_gemma":[0.9979247,0.0000032419025,0.0002553275,0.0006567106,0.000041409377,0.000025692694,0.0000043443706,0.0000066664966,0.0010818931],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99605566,0.00097551954,0.00064233463,0.000719108,0.0013093223,0.00029808085],"domain_scores_gemma":[0.995898,0.003100247,0.00038699436,0.00032608103,0.00015211549,0.00013655069],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.009979659,0.0001730103,0.00036592208,0.00033510796,0.0012698327,0.00024618523,0.0009722954,0.00006261142,0.0023410092],"category_scores_gemma":[0.0008947888,0.00011816561,0.00012538841,0.0013164822,0.0018497158,0.00043144793,0.00046593932,0.0002412766,0.000014818639],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035233703,0.0007430089,0.034067474,0.0000021750238,0.000013071326,0.000015649659,0.010403964,0.0023164733,0.0039158207,0.14438039,0.006011556,0.79777807],"study_design_scores_gemma":[0.00081023434,0.0015756106,0.02903771,0.000015581287,0.000041635743,0.0000791643,0.09380633,0.0008307303,0.00026212362,0.85075545,0.022355083,0.00043036055],"about_ca_topic_score_codex":0.00021143074,"about_ca_topic_score_gemma":0.00008807466,"teacher_disagreement_score":0.7973477,"about_ca_system_score_codex":0.000060098413,"about_ca_system_score_gemma":0.00021713573,"threshold_uncertainty_score":0.998571},"labels":[],"label_agreement":null},{"id":"W4283361691","doi":"10.1177/00222437221112312","title":"“It Could Be Better” Can Make It Worse: When and Why People Mistakenly Communicate Upward Counterfactual Information","year":2022,"lang":"en","type":"article","venue":"Journal of Marketing Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Booth University College","funders":"","keywords":"Counterfactual thinking; Real estate; Ideal (ethics); Psychology; Computer science; Social psychology; Economics; Epistemology; Philosophy","score_opus":0.2675501825770345,"score_gpt":0.45028033585034966,"score_spread":0.18273015327331515,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4283361691","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9287686,0.000111217014,0.00008019995,0.066773884,0.00035510573,0.0001464458,0.00007802593,0.000008170888,0.0036783728],"genre_scores_gemma":[0.994846,0.0001280413,0.0007832921,0.0033625942,0.00008893444,0.0000069743646,0.000006379564,0.000015478536,0.00076234195],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9908628,0.002890691,0.0015847469,0.0002375336,0.0038861302,0.000538088],"domain_scores_gemma":[0.98463076,0.011723048,0.00093385606,0.0006999148,0.0017569396,0.00025545858],"candidate_categories":["metaresearch","scholarly_communication","insufficient_payload"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.08448654,0.00015209462,0.0004411913,0.0010008451,0.0010982701,0.0014226555,0.002067882,0.00008217466,0.0020846785],"category_scores_gemma":[0.01595351,0.00012447315,0.00014113789,0.00065237854,0.00020347924,0.00056238455,0.0013973268,0.001919919,0.000029420069],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016092632,0.00009739758,0.017076852,0.000013484171,0.000028363651,0.000041001713,0.008647494,0.00026680567,0.000056178687,0.000008445805,0.5821771,0.3899776],"study_design_scores_gemma":[0.00078643387,0.0003545405,0.013043746,0.00008585222,0.000013540085,0.00032337703,0.032919526,0.0013988249,0.000009848643,0.0034837185,0.9474046,0.00017597541],"about_ca_topic_score_codex":0.00018497817,"about_ca_topic_score_gemma":0.0006867447,"teacher_disagreement_score":0.38980162,"about_ca_system_score_codex":0.00038422382,"about_ca_system_score_gemma":0.0004432223,"threshold_uncertainty_score":0.99961394},"labels":[],"label_agreement":null},{"id":"W4283689970","doi":"10.3389/fpsyg.2022.898027","title":"Artificial Intelligence Can’t Be Charmed: The Effects of Impartiality on Laypeople’s Algorithmic Preferences","year":2022,"lang":"en","type":"article","venue":"Frontiers in Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Impartiality; Psychology; Social psychology; Preference; Political science; Law; Economics; Microeconomics","score_opus":0.13425104857261405,"score_gpt":0.4257887007390891,"score_spread":0.29153765216647504,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4283689970","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.973121,0.00021548422,0.010527176,0.0030617847,0.011876835,0.00038991656,0.000069215,0.000018694114,0.00071992516],"genre_scores_gemma":[0.9971859,0.00004137804,0.0011701104,0.0013390098,0.00007733951,0.00010395065,0.0000044206195,0.000010340275,0.00006757773],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99658585,0.00083424064,0.00090761663,0.000660687,0.0006686464,0.00034294295],"domain_scores_gemma":[0.99733114,0.001254506,0.00038921833,0.0009031149,0.000056596695,0.000065401866],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029840737,0.00016301592,0.00045144797,0.00041241685,0.00021224344,0.000049638056,0.0016708137,0.00009181854,0.000421385],"category_scores_gemma":[0.0010364093,0.00011356549,0.00013244385,0.00083241967,0.00033103637,0.00006543195,0.00024693058,0.00047920563,0.00003056824],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021588201,0.00029894302,0.012136915,0.000002240348,0.000009774847,0.000014936672,0.0013025192,0.00023383356,0.000106958745,0.000377408,0.03582418,0.9494764],"study_design_scores_gemma":[0.00030089985,0.0014370694,0.018674588,0.000016787126,0.000024833636,0.000020597128,0.005864824,0.0021984745,0.0012538424,0.94591886,0.023953449,0.00033578047],"about_ca_topic_score_codex":0.00015035132,"about_ca_topic_score_gemma":0.00017497219,"teacher_disagreement_score":0.9491406,"about_ca_system_score_codex":0.00008493203,"about_ca_system_score_gemma":0.00008713275,"threshold_uncertainty_score":0.46310663},"labels":[],"label_agreement":null},{"id":"W4283827058","doi":"10.1007/s11409-022-09313-y","title":"How accurate and predictive are judgments of solvability? Explorations in a two-phase anagram solving paradigm","year":2022,"lang":"en","type":"article","venue":"Metacognition and Learning","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Okanagan College","funders":"Flinders University; Australian Government","keywords":"Anagrams; Anagram; Psychology; Task (project management); Set (abstract data type); Duration (music); Cognitive psychology; Developmental psychology; Computer science","score_opus":0.15767976839915737,"score_gpt":0.41044014986003546,"score_spread":0.2527603814608781,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4283827058","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99399894,0.00015980979,0.0047946842,0.00046232503,0.00011353305,0.00019226327,0.0000755731,0.000019835621,0.00018302532],"genre_scores_gemma":[0.99929994,0.000020635189,0.00036220564,0.00006992008,0.000015719143,0.000057186615,0.000025260026,0.000007974562,0.00014114112],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979411,0.0006143328,0.0004520441,0.00042408876,0.0004093945,0.00015904552],"domain_scores_gemma":[0.99848205,0.0007898816,0.00040228825,0.00015477606,0.000094689516,0.000076297765],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025250625,0.00011313352,0.00030273214,0.00041231554,0.00047328603,0.00032785395,0.00013306073,0.000025263296,0.00015959184],"category_scores_gemma":[0.0018106301,0.000102357255,0.000057655205,0.00050358154,0.00009156729,0.0006890457,0.00018544514,0.0003655038,0.0000029932605],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036963465,0.00071667775,0.08425553,0.000015032257,0.000040045423,0.000038791768,0.008802745,0.011138878,0.0014359005,0.00027206156,0.00015699487,0.8927577],"study_design_scores_gemma":[0.013303034,0.0024767537,0.119886786,0.00022162912,0.0003025438,0.00009340926,0.25439557,0.4013251,0.00076423265,0.18654831,0.019441264,0.0012413766],"about_ca_topic_score_codex":0.000017370669,"about_ca_topic_score_gemma":0.00004443684,"teacher_disagreement_score":0.8915163,"about_ca_system_score_codex":0.000032017237,"about_ca_system_score_gemma":0.000026851085,"threshold_uncertainty_score":0.41740078},"labels":[],"label_agreement":null},{"id":"W4284890194","doi":"10.23941/ejpe.v15i1.617","title":"The Case of Stated Preferences and Social Well-Being Indices","year":2022,"lang":"en","type":"article","venue":"Erasmus Journal for Philosophy and Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Popularity; Deliberation; Happiness; Paternalism; Positive economics; Politics; Preference; Social choice theory; Order (exchange); Social preferences; Public economics; Sociology; Economics; Political science; Psychology; Social psychology; Microeconomics; Law","score_opus":0.1124874216597746,"score_gpt":0.3654072601664208,"score_spread":0.2529198385066462,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4284890194","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99538463,0.0002665864,0.00002199322,0.0018073096,0.00092962553,0.00012197295,0.0001181125,0.000004964758,0.0013447818],"genre_scores_gemma":[0.99913317,0.00023701886,0.00017446763,0.0001448918,0.0002135879,0.000009105507,0.000002832723,0.000010236441,0.00007467683],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99849373,0.00011730125,0.0008004668,0.0002652434,0.00012115155,0.0002021278],"domain_scores_gemma":[0.9976104,0.0013307902,0.00073416246,0.00014469094,0.00009294281,0.00008703331],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0030458868,0.00012452873,0.00029951756,0.0001846743,0.0029298887,0.00058072916,0.00039872338,0.000045641063,0.000091485264],"category_scores_gemma":[0.00012571744,0.00008779601,0.00012089884,0.00009499471,0.00019244757,0.00035281823,0.0002371955,0.0002803968,0.000002497162],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007202073,0.00010271669,0.0035019245,0.000011208132,0.000113437905,0.000088812776,0.00741333,0.0010330915,0.000013584336,0.053574167,0.0022061828,0.9312213],"study_design_scores_gemma":[0.00055899646,0.00028377117,0.00019070372,0.0000036781069,0.000024745941,0.0013506709,0.005243422,0.0017102101,0.00001532741,0.9587279,0.03175998,0.00013058196],"about_ca_topic_score_codex":0.000018454899,"about_ca_topic_score_gemma":0.000057196743,"teacher_disagreement_score":0.9310908,"about_ca_system_score_codex":0.000041170722,"about_ca_system_score_gemma":0.00006715528,"threshold_uncertainty_score":0.99836814},"labels":[],"label_agreement":null},{"id":"W4285008158","doi":"10.1038/s41562-022-01392-w","title":"The globalizability of temporal discounting","year":2022,"lang":"en","type":"article","venue":"Nature Human Behaviour","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":99,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; York University; McGill University","funders":"Medical Research Council; University of Cambridge; UK Research and Innovation","keywords":"Discounting; Psychology; Econometrics; Economics","score_opus":0.06845175588635537,"score_gpt":0.4238273547491535,"score_spread":0.3553755988627981,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285008158","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9954341,0.00026487935,0.000015927319,0.0004409983,0.0012685308,0.00018068911,0.000118976255,0.000034389013,0.0022415188],"genre_scores_gemma":[0.9985086,8.9421314e-7,0.0001299616,0.000107747954,0.00007120246,0.000018137987,0.0000123364225,0.000013677877,0.0011374729],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99623084,0.00030425223,0.0009494989,0.0005326244,0.0016944535,0.00028830662],"domain_scores_gemma":[0.99723285,0.000627589,0.00062224024,0.0011765251,0.00026950793,0.00007129027],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0058133015,0.00015742077,0.00030973717,0.00013075589,0.0016025017,0.00030195058,0.002029681,0.0001294407,0.0008836445],"category_scores_gemma":[0.0008205466,0.0001008198,0.00027919025,0.0006128908,0.00022322606,0.00018376895,0.0008437391,0.00093027874,0.000024816034],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000052667845,0.00030813314,0.885216,0.0000014057061,0.000007499846,0.000017985963,0.00032940146,0.00012683385,0.00028845566,0.00846032,0.027859475,0.07733185],"study_design_scores_gemma":[0.0006662972,0.00029833725,0.55952376,0.000011696036,0.000058038808,0.000046523917,0.00523784,0.00015142406,0.0002554504,0.26655513,0.16672233,0.00047317945],"about_ca_topic_score_codex":0.00013774776,"about_ca_topic_score_gemma":0.00024983,"teacher_disagreement_score":0.3256922,"about_ca_system_score_codex":0.00015025285,"about_ca_system_score_gemma":0.00008797198,"threshold_uncertainty_score":0.99969727},"labels":[],"label_agreement":null},{"id":"W4285021069","doi":"10.2139/ssrn.4088821","title":"Ups and Downs: How to Shape an Audience's Sentiment","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Advertising; Sentiment analysis; Psychology; Political science; Computer science; Business; Artificial intelligence","score_opus":0.059027629802241896,"score_gpt":0.3580510354677922,"score_spread":0.2990234056655503,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285021069","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99172103,0.0004640788,0.001650962,0.0050869966,0.0005706119,0.000119602686,0.000009318428,0.000021280186,0.00035610076],"genre_scores_gemma":[0.99629045,0.0001456697,0.00037267277,0.00050017476,0.00015038947,0.000010919134,0.0000012164197,0.000014673257,0.0025138275],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9961947,0.00023609684,0.00045013498,0.00053458917,0.0010906594,0.0014938229],"domain_scores_gemma":[0.9987678,0.0001789303,0.0002598347,0.00040027418,0.000120493925,0.00027265513],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008678056,0.00015797467,0.00026243733,0.00038791864,0.0009932466,0.0007836401,0.0010438374,0.000034786375,0.0005970435],"category_scores_gemma":[0.0003165309,0.0001248552,0.00011104264,0.000517874,0.00004872707,0.0005069967,0.0004342888,0.0011687943,0.000108793385],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000058041667,0.0000909728,0.0019923253,1.7267654e-7,0.000015115032,0.000019475918,0.00046589787,0.0003807122,0.00027710822,0.0038543278,0.0015642585,0.99128157],"study_design_scores_gemma":[0.0006119147,0.0019896834,0.0026225934,0.00000552191,0.000026853144,0.002607845,0.021376863,0.0023268554,0.000030985095,0.88841087,0.0796072,0.00038279608],"about_ca_topic_score_codex":0.000018796436,"about_ca_topic_score_gemma":0.00022741049,"teacher_disagreement_score":0.9908988,"about_ca_system_score_codex":0.0007897627,"about_ca_system_score_gemma":0.0008684418,"threshold_uncertainty_score":0.763935},"labels":[],"label_agreement":null},{"id":"W4285086941","doi":"10.26509/frbc-wp-202128r","title":"Communicating Data Uncertainty: Multi-Wave Experimental Evidence for UK GDP","year":2022,"lang":"en","type":"report","venue":"Working paper","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bank of Canada","funders":"Warwick Business School, University of Warwick; University of Warwick","keywords":"Probabilistic logic; Point estimation; Measurement uncertainty; Econometrics; Qualitative property; Control (management); Point (geometry); Statistics; Computer science; Economics; Mathematics; Artificial intelligence","score_opus":0.8489929296110112,"score_gpt":0.5691288876152597,"score_spread":0.27986404199575154,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285086941","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.27814463,0.24863365,0.010863635,0.0075085745,0.13100067,0.017971285,0.012069626,0.002212887,0.29159504],"genre_scores_gemma":[0.91388017,0.0014035583,0.048338715,0.0011307733,0.0014239228,0.00051497354,0.0012235735,0.0002468999,0.031837415],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9917309,0.00041013004,0.002159494,0.002166229,0.0028645245,0.00066871336],"domain_scores_gemma":[0.9789291,0.010883116,0.0018276215,0.007734987,0.0004356929,0.00018949273],"candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.014418906,0.00056733744,0.0011726368,0.00037180918,0.0011969657,0.0011632761,0.007363723,0.0003909879,0.004897683],"category_scores_gemma":[0.014364563,0.0004848271,0.0004967336,0.00056596706,0.0002201376,0.00044476765,0.007488642,0.0011048652,0.00015929228],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010159412,0.00020355271,0.0013869792,0.00001460906,0.000054247143,0.000045100223,0.00079564593,0.0004635868,0.00028397643,0.00002838333,0.15080953,0.8458128],"study_design_scores_gemma":[0.00036790082,0.000083175626,0.00015050743,0.000724863,0.00009056679,0.00007536254,0.0019893667,0.0031757152,0.000021196885,0.00072452007,0.99193096,0.00066586206],"about_ca_topic_score_codex":0.0008568076,"about_ca_topic_score_gemma":0.0009800863,"teacher_disagreement_score":0.84514695,"about_ca_system_score_codex":0.0007995189,"about_ca_system_score_gemma":0.0013087585,"threshold_uncertainty_score":0.99987364},"labels":[],"label_agreement":null},{"id":"W4285218571","doi":"10.3982/ecta18137","title":"Randomize at Your Own Risk: On the Observability of Ambiguity Aversion","year":2022,"lang":"en","type":"article","venue":"Econometrica","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Erasmus Research Institute of Management; Social Sciences and Humanities Research Council of Canada; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Erasmus Universiteit Rotterdam","keywords":"Ambiguity; Ambiguity aversion; Observability; Incentive; Risk aversion (psychology); Econometrics; Isolation (microbiology); Incentive compatibility; Economics; Hedge; Expected utility hypothesis; Microeconomics; Mathematical economics; Computer science; Mathematics; Applied mathematics","score_opus":0.28636243543570555,"score_gpt":0.3775546163438651,"score_spread":0.09119218090815956,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285218571","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98628503,0.000072642746,0.000034132347,0.001043408,0.0009101427,0.00029515295,0.00027281494,0.000021520393,0.011065141],"genre_scores_gemma":[0.99727374,0.000020463218,0.00010200669,0.00024235678,0.000035721165,0.000028970237,0.0000041771436,0.000010094371,0.0022824442],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99662316,0.00070818927,0.0010136734,0.0006386381,0.0007710058,0.0002453321],"domain_scores_gemma":[0.98781615,0.009547563,0.0009563145,0.0014564819,0.000114561924,0.00010890943],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.01055978,0.00015396134,0.0005510594,0.00064885814,0.0008025115,0.00010906301,0.0015770296,0.000051455867,0.015533411],"category_scores_gemma":[0.0109376935,0.000097512544,0.0004626457,0.0020123746,0.00013498797,0.00014596932,0.0010876075,0.0003255625,0.0008969408],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0031043147,0.0010051287,0.2653816,0.000002990689,0.00005753755,0.000008501111,0.0009784685,0.006364243,0.00008457027,0.0006158791,0.10305688,0.6193399],"study_design_scores_gemma":[0.007126041,0.001171995,0.3612758,0.000007658693,0.000080824364,0.000011467247,0.0029712163,0.0051072245,0.00092603086,0.11171119,0.50896305,0.0006475326],"about_ca_topic_score_codex":0.00013304122,"about_ca_topic_score_gemma":0.0000148953695,"teacher_disagreement_score":0.61869234,"about_ca_system_score_codex":0.00041416255,"about_ca_system_score_gemma":0.00006238488,"threshold_uncertainty_score":0.99988097},"labels":[],"label_agreement":null},{"id":"W4285222328","doi":"10.1007/978-3-319-55065-7_1526","title":"Stochastic Distributions","year":2022,"lang":"en","type":"book-chapter","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Computer science","score_opus":0.19191756333767215,"score_gpt":0.3922298651262077,"score_spread":0.20031230178853557,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285222328","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0003019771,0.000098046046,0.011258949,0.0005064017,0.0016784003,0.0001779708,0.0010166675,0.000098359225,0.9848632],"genre_scores_gemma":[0.023933103,0.000010068899,0.00032407267,0.00017123549,0.00013837425,0.000011965509,0.00012263696,0.00003686028,0.9752517],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.996791,0.000022844748,0.0009193343,0.0007931664,0.0012472103,0.00022644273],"domain_scores_gemma":[0.9967326,0.0012778806,0.00040984846,0.0012245832,0.00019380677,0.00016128477],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0011125403,0.00028084966,0.00051687565,0.00037494494,0.00036625573,0.0003367806,0.001272895,0.0001985306,0.17026769],"category_scores_gemma":[0.0006597943,0.0002191422,0.0004194581,0.000093030576,0.00012554845,0.00015410532,0.0006856049,0.00050848577,0.010950123],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008297615,0.000020187506,0.0000024365884,3.350493e-7,0.00001083597,0.000023939863,0.000013342469,0.00019198241,6.493032e-7,0.5169107,0.11891822,0.3638991],"study_design_scores_gemma":[0.00004454373,0.00002984759,0.000006144103,0.0000050510207,0.000018475588,0.000014730653,0.000014849815,0.0000764055,2.1259287e-7,0.4545923,0.5450308,0.00016666649],"about_ca_topic_score_codex":0.00001476327,"about_ca_topic_score_gemma":0.00003702604,"teacher_disagreement_score":0.42611256,"about_ca_system_score_codex":0.00020977824,"about_ca_system_score_gemma":0.000172732,"threshold_uncertainty_score":0.98981994},"labels":[],"label_agreement":null},{"id":"W4285260216","doi":"10.55365/1923.x2022.20.2","title":"Teaching1 Economics Students about Different Models for Dealing with Uncertainty and Risk Besides the Standard Capital Asset Pricing Model (CAPM) and the Subjective Expected Utility (SEU) Model","year":2022,"lang":"en","type":"article","venue":"Review of Economics and Finance","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Capital asset pricing model; Economics; Cumulative prospect theory; Prospect theory; Asset (computer security); Actuarial science; Behavioral economics; Risk aversion (psychology); Gold standard (test); Risk-seeking; Expected utility hypothesis; Financial economics; Microeconomics; Computer science; Finance","score_opus":0.06501563034508676,"score_gpt":0.3406378903042606,"score_spread":0.2756222599591739,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285260216","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96688485,0.022382192,0.008335466,0.00032322903,0.000057269488,0.001033943,0.0009077952,0.0000063160123,0.00006893606],"genre_scores_gemma":[0.82379144,0.17439649,0.0014919498,0.0001493167,0.0000110964,0.00011779872,0.000005476893,0.000016617018,0.000019823949],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977158,0.00016642937,0.001006765,0.0007073333,0.00016228906,0.00024139536],"domain_scores_gemma":[0.99679315,0.0013560416,0.0010600331,0.00060369156,0.00013164041,0.00005545511],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004747981,0.0002687129,0.00096567627,0.000057706606,0.0008694611,0.00027253045,0.0006130006,0.000044094562,0.0000035307648],"category_scores_gemma":[0.00026042882,0.00015197226,0.00015468163,0.000058952162,0.0003382352,0.0002848,0.0005303102,0.00027634547,1.5122018e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00070705387,0.00007146478,0.0056286566,0.000097025426,0.00008436939,3.586305e-7,0.0022899546,0.72030765,5.4050156e-7,0.052907135,0.0000513626,0.21785443],"study_design_scores_gemma":[0.0008846704,0.00009908714,0.001158164,0.00014976478,0.00009006846,0.0000069214966,0.0005301706,0.7769013,0.0000020743641,0.21972203,0.0002879095,0.00016785126],"about_ca_topic_score_codex":0.000165837,"about_ca_topic_score_gemma":0.00036882568,"teacher_disagreement_score":0.21768658,"about_ca_system_score_codex":0.0001089412,"about_ca_system_score_gemma":0.000120981,"threshold_uncertainty_score":0.668728},"labels":[],"label_agreement":null},{"id":"W4285298482","doi":"10.1093/restud/rdac023","title":"Measuring Belief-dependent Preferences without Data on Beliefs","year":2022,"lang":"en","type":"article","venue":"The Review of Economic Studies","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Economics; Econometrics; Positive economics; Mathematical economics; Microeconomics","score_opus":0.5461250964114086,"score_gpt":0.4749042238464929,"score_spread":0.07122087256491572,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285298482","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.64806753,0.3266938,0.000010435966,0.0059248176,0.0029534057,0.0010043595,0.0005375727,0.000050037623,0.014758017],"genre_scores_gemma":[0.89812195,0.09924103,0.00015174021,0.0012032249,0.0001634697,0.00009869697,0.000009625413,0.000020167725,0.0009901082],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9966238,0.00043861315,0.0013501497,0.00071368803,0.0006512836,0.00022248007],"domain_scores_gemma":[0.9941895,0.002171946,0.0009738622,0.0025167074,0.0001017698,0.00004621784],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010873254,0.00020540226,0.0009546527,0.00012274239,0.0005491852,0.00006776375,0.003786735,0.000017638431,0.00086487463],"category_scores_gemma":[0.0018720955,0.00011857808,0.00016564963,0.00016306229,0.00018851148,0.00020437512,0.0032454617,0.0002247125,0.0005741484],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004451224,0.00011577167,0.0027524072,0.00019265029,0.00022332407,0.0000026715843,0.0006776343,0.00091233687,0.000005393813,0.0012660736,0.05974204,0.93406516],"study_design_scores_gemma":[0.0012083974,0.001041378,0.004858062,0.00613001,0.00061232445,0.00009373375,0.0129387695,0.0007977933,0.00016631857,0.19344981,0.7773983,0.0013051366],"about_ca_topic_score_codex":0.000038004822,"about_ca_topic_score_gemma":0.000075140386,"teacher_disagreement_score":0.93276006,"about_ca_system_score_codex":0.00016963865,"about_ca_system_score_gemma":0.000120186145,"threshold_uncertainty_score":0.9469771},"labels":[],"label_agreement":null},{"id":"W4286539857","doi":"10.2139/ssrn.4158050","title":"Goal-Based Categorization: Dynamic Classification in the Display Advertising Industry","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Categorization; Advertising; Display advertising; Business; Computer science; Artificial intelligence; Online advertising; World Wide Web; The Internet","score_opus":0.048524539592846166,"score_gpt":0.36545674541670004,"score_spread":0.31693220582385384,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4286539857","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.979529,0.00029030294,0.014598701,0.004469902,0.00050241704,0.00012794862,0.000005903365,0.000013953611,0.00046186076],"genre_scores_gemma":[0.998982,0.00003847652,0.00004239264,0.00038543058,0.00006945714,0.000017460707,0.000009760262,0.000013765541,0.00044123884],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9962352,0.00060684205,0.0007235687,0.00033833354,0.0010984393,0.0009976386],"domain_scores_gemma":[0.99846387,0.0005133495,0.00043666095,0.00044411246,0.00009224953,0.000049765367],"candidate_categories":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.010638365,0.00012998149,0.00017863479,0.0003855907,0.00081023946,0.00036799556,0.0013556511,0.000097358374,0.00021848836],"category_scores_gemma":[0.00044354337,0.000089893765,0.00011883387,0.0011763078,0.000049636503,0.00031571073,0.00008064372,0.003568943,0.000049440536],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011081194,0.0002951827,0.032113623,6.954281e-7,0.000012761156,0.000024554905,0.0006157374,0.028731171,0.00031659473,0.02857416,0.0005249012,0.9086798],"study_design_scores_gemma":[0.0008482788,0.00031037003,0.031333778,0.000009546153,0.000022659175,0.0006322976,0.02224632,0.05221836,0.000007383909,0.88252234,0.009581962,0.00026670343],"about_ca_topic_score_codex":0.00003471246,"about_ca_topic_score_gemma":0.00064391166,"teacher_disagreement_score":0.9084131,"about_ca_system_score_codex":0.001751453,"about_ca_system_score_gemma":0.002110516,"threshold_uncertainty_score":0.9987299},"labels":[],"label_agreement":null},{"id":"W4287778702","doi":"10.48550/arxiv.2005.06673","title":"Comparison of Information Structures for Zero-Sum Games and a Partial\\n Converse to Blackwell Ordering in Standard Borel Spaces","year":2020,"lang":"","type":"preprint","venue":"arXiv (Cornell University)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bell (Canada)","funders":"","keywords":"Converse; Mathematics; Corollary; Generalization; Characterization (materials science); Zero-sum game; Zero (linguistics); Mathematical economics; Space (punctuation); Discrete mathematics; Variable (mathematics); State space; Combinatorics; Game theory; Computer science; Mathematical analysis; Statistics","score_opus":0.18032083885102967,"score_gpt":0.312557684023508,"score_spread":0.1322368451724783,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4287778702","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.81778204,0.000051165745,0.17968981,0.00017654042,0.0006902382,0.0010034495,0.000387977,0.00003024709,0.00018852239],"genre_scores_gemma":[0.9969988,0.00016647213,0.0025823424,0.00012396461,0.00003395015,0.0000026188363,0.00002192678,0.000021270369,0.000048658785],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.996203,0.0001684455,0.0015193729,0.0012778639,0.00032380794,0.00050747563],"domain_scores_gemma":[0.99571466,0.0009984805,0.0014256722,0.0008347871,0.0005876328,0.00043874545],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0011618315,0.00054095604,0.0014997819,0.0010215391,0.00020650108,0.000563621,0.0011488596,0.0004488622,0.00014188337],"category_scores_gemma":[0.001166666,0.0005760085,0.0003067786,0.0011002691,0.00038771596,0.001127634,0.0014633316,0.00052394177,0.00006365604],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0055954177,0.00017739976,0.11704106,0.00035795485,0.00012373462,0.000040308256,0.013230184,0.7419055,0.00014659559,0.019935949,0.0023200314,0.099125855],"study_design_scores_gemma":[0.0047500245,0.0015611763,0.008598675,0.00066216197,0.00039272715,0.0000037543534,0.031746846,0.7186017,0.0024328441,0.18401608,0.04556454,0.0016694848],"about_ca_topic_score_codex":0.00031167443,"about_ca_topic_score_gemma":0.00027588411,"teacher_disagreement_score":0.17921674,"about_ca_system_score_codex":0.00025458712,"about_ca_system_score_gemma":0.00041087443,"threshold_uncertainty_score":0.99966913},"labels":[],"label_agreement":null},{"id":"W4288942881","doi":"10.2139/ssrn.4176907","title":"Semantics Meets Attractiveness: Choice by Salience","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Salience (neuroscience); Transitive relation; Attractiveness; Salient; Computer science; Social psychology; Theoretical computer science; Psychology; Mathematics; Artificial intelligence; Combinatorics","score_opus":0.05931326050342803,"score_gpt":0.37347892585598347,"score_spread":0.3141656653525554,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4288942881","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9889633,0.0014086426,0.004923129,0.0026956932,0.0010744712,0.00009307192,0.000025205998,0.000031487703,0.0007850072],"genre_scores_gemma":[0.9962227,0.00035701698,0.000095748874,0.00030398706,0.00014928599,0.000008255703,0.0000030135002,0.000023860843,0.00283618],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9948592,0.000382136,0.00076073554,0.0005217876,0.0016321199,0.0018440019],"domain_scores_gemma":[0.99761546,0.0009462502,0.00061263546,0.00049254776,0.00018427304,0.00014882271],"candidate_categories":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00987125,0.00019030157,0.0003311644,0.0002749551,0.0011661388,0.0004164383,0.0018901967,0.00005727831,0.00067895476],"category_scores_gemma":[0.0009521601,0.00015929223,0.00021650297,0.00070967217,0.00007744731,0.00057299697,0.0003428958,0.0023636585,0.00022117396],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000107106134,0.00041094326,0.013793612,7.61132e-7,0.000057487494,0.000028227389,0.0002616578,0.002401301,0.0020757115,0.012098143,0.01215225,0.9566128],"study_design_scores_gemma":[0.0005315503,0.00045509025,0.000834666,0.0000053657395,0.000027633014,0.0011999155,0.004666707,0.0005833928,0.00012760473,0.66342217,0.32782555,0.00032039874],"about_ca_topic_score_codex":0.00007419153,"about_ca_topic_score_gemma":0.00022838174,"teacher_disagreement_score":0.9562924,"about_ca_system_score_codex":0.0013032932,"about_ca_system_score_gemma":0.0016957407,"threshold_uncertainty_score":0.99993795},"labels":[],"label_agreement":null},{"id":"W4289947959","doi":"10.1186/s12889-022-13928-w","title":"Estimating the lagged effect of price discounting: a time-series study on sugar sweetened beverage purchasing in a supermarket","year":2022,"lang":"en","type":"article","venue":"BMC Public Health","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University; McGill University Health Centre","funders":"Institut de Valorisation des Données","keywords":"Discounting; Purchasing; Delay discounting; Sugar; Economics; Econometrics; Medicine; Food science; Operations management","score_opus":0.1034258994670752,"score_gpt":0.39968536321195935,"score_spread":0.29625946374488416,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4289947959","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9949941,0.00003262965,0.0003979837,0.0025064584,0.00042441854,0.0009899293,0.000033028624,0.000041695617,0.0005797561],"genre_scores_gemma":[0.9984672,5.3771043e-7,0.00090859254,0.00025875843,0.00004789967,0.00010384784,0.000006599267,0.000022165508,0.00018437549],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99222195,0.0036524218,0.0013883077,0.00065277884,0.0015074462,0.0005771086],"domain_scores_gemma":[0.99243015,0.0057016956,0.0006838844,0.0009472883,0.0000910276,0.00014594388],"candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.03673445,0.0002090435,0.0006633694,0.0005352705,0.00081931485,0.00044870217,0.0012480607,0.000035960424,0.00029600767],"category_scores_gemma":[0.0085161785,0.00013237516,0.00013011259,0.001579386,0.00008440778,0.00046336357,0.0006248121,0.00043356998,0.000039073744],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006077245,0.0014517502,0.6647133,0.00004488101,0.00002123162,0.000029636632,0.017277762,0.0069643604,0.0000812,0.00014127417,0.0021543961,0.30651248],"study_design_scores_gemma":[0.0062404093,0.010941046,0.8305952,0.00018730438,0.000025236373,0.00011489604,0.035549447,0.096459344,0.000044387296,0.0051471507,0.013661213,0.0010344026],"about_ca_topic_score_codex":0.00035475713,"about_ca_topic_score_gemma":0.00019813461,"teacher_disagreement_score":0.30547807,"about_ca_system_score_codex":0.0003656273,"about_ca_system_score_gemma":0.00075418514,"threshold_uncertainty_score":0.9998355},"labels":[],"label_agreement":null},{"id":"W4290375586","doi":"10.1111/fire.12315","title":"Risk‐taking begets risk‐taking: Evidence from casino openings and investor portfolios","year":2022,"lang":"en","type":"article","venue":"Financial Review","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Portfolio; Spillover effect; Systematic risk; Monetary economics; Business; Economics; Affect (linguistics); Financial economics; Microeconomics; Psychology","score_opus":0.20269503028748848,"score_gpt":0.4132033250902302,"score_spread":0.21050829480274175,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4290375586","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.85616267,0.14061639,0.00020040345,0.0005342522,0.0011741191,0.0005487372,0.00024202726,0.000050031096,0.00047139142],"genre_scores_gemma":[0.9404239,0.053670198,0.0027963808,0.0022820865,0.00027995792,0.00012528554,0.000011204348,0.000040183393,0.00037079988],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99460334,0.00081052777,0.0015599356,0.0012413083,0.0013362521,0.0004486304],"domain_scores_gemma":[0.9904079,0.0023593025,0.005541917,0.0012126759,0.00021960353,0.00025859897],"candidate_categories":["metaresearch","metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.007666226,0.00034345654,0.0010782317,0.00022943222,0.0011879918,0.00028458028,0.0015607364,0.00009823527,0.002745162],"category_scores_gemma":[0.063574106,0.00029115172,0.0003208589,0.0011141779,0.00013698539,0.0006418705,0.0013405248,0.00078666594,0.0004823696],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027243883,0.00002616494,0.075855516,0.000023033044,0.000005707545,0.000095699164,0.0003551164,0.000015486237,0.00001771646,0.00008154027,0.02977105,0.89372575],"study_design_scores_gemma":[0.00029054456,0.00021781995,0.26176018,0.002459508,0.00022219778,0.0000863579,0.00009311355,0.00018635826,0.000024297176,0.028932992,0.7051081,0.000618537],"about_ca_topic_score_codex":0.0020244042,"about_ca_topic_score_gemma":0.00025413316,"teacher_disagreement_score":0.8931072,"about_ca_system_score_codex":0.00017276361,"about_ca_system_score_gemma":0.00040104488,"threshold_uncertainty_score":0.99995404},"labels":[],"label_agreement":null},{"id":"W4290617535","doi":"10.1111/caje.12615","title":"Asset integration and risk‐taking in the laboratory","year":2022,"lang":"en","type":"article","venue":"Canadian Journal of Economics/Revue canadienne d économique","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Calgary; Wilfrid Laurier University","funders":"","keywords":"Expected utility hypothesis; Preference; Risk aversion (psychology); Asset (computer security); Prospect theory; Cash; Economics; Loss aversion; Experimental economics; Rank (graph theory); Task (project management); Econometrics; Microeconomics; Actuarial science; Financial economics; Computer science; Finance; Mathematics","score_opus":0.2811639811675608,"score_gpt":0.2764366426569144,"score_spread":0.004727338510646384,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4290617535","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99532807,0.0002329941,0.0000354199,0.0017476302,0.001455642,0.00016266365,0.00037379653,0.0000023888235,0.0006613764],"genre_scores_gemma":[0.99855685,0.000055892677,0.00024625353,0.0008337364,0.00020554193,0.000015537698,0.0000053152125,0.00002075148,0.00006014093],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9973379,0.00052198156,0.0012841971,0.00038898241,0.000012978859,0.00045399807],"domain_scores_gemma":[0.9954751,0.0012082523,0.0019839997,0.00052985194,0.0001833085,0.0006194668],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008787471,0.00019226315,0.00050026603,0.0012915564,0.00052641856,0.000566209,0.0013605166,0.00008747504,0.00043813215],"category_scores_gemma":[0.0026213855,0.00017012047,0.0001476755,0.00042998078,0.00013882341,0.0005796276,0.000061706014,0.0008143169,0.000014110959],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016625856,0.000056813344,0.30165303,0.000005031404,0.000075804506,0.000612295,0.016450925,0.04020545,0.000020416725,0.14305928,0.011619043,0.48607564],"study_design_scores_gemma":[0.0008339127,0.00056451454,0.040440224,0.000034515084,0.000045880442,0.0011239673,0.020643005,0.006086643,0.00001593328,0.79574764,0.1339615,0.0005022382],"about_ca_topic_score_codex":0.08140673,"about_ca_topic_score_gemma":0.97047144,"teacher_disagreement_score":0.8890647,"about_ca_system_score_codex":0.0014872528,"about_ca_system_score_gemma":0.0018053887,"threshold_uncertainty_score":0.9247103},"labels":[],"label_agreement":null},{"id":"W4291710419","doi":"10.1016/j.cognition.2022.105245","title":"Biased confabulation in risky choice","year":2022,"lang":"en","type":"article","venue":"Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Economic and Social Research Council; Leverhulme Trust","keywords":"Psychology; Confabulation (neural networks); Recall; Cognitive psychology; Task (project management); Context (archaeology); Encoding (memory); Cognition; Reconstructive memory; Memory errors; Episodic memory; Value (mathematics); Social psychology; Explicit memory","score_opus":0.24053315150162266,"score_gpt":0.4307733157473803,"score_spread":0.19024016424575765,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4291710419","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9910723,0.000022798798,0.00043017598,0.00027903923,0.0004548139,0.00013675357,0.00004463167,0.000030688887,0.007528787],"genre_scores_gemma":[0.99914545,0.0000017196626,0.00010851533,0.0003557501,0.00003867557,0.000033932203,0.000049958515,0.000006715274,0.00025925908],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99840134,0.00018798106,0.000430926,0.00031376458,0.0005374713,0.00012851832],"domain_scores_gemma":[0.99858135,0.00087312,0.00017680871,0.00022858178,0.00009970907,0.00004045645],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0016471472,0.00006754357,0.00013257975,0.00036753516,0.00019846622,0.0001249198,0.00024877454,0.000032481115,0.0031237348],"category_scores_gemma":[0.0012423105,0.00006567011,0.000054905347,0.0006336915,0.000025466994,0.00023366143,0.00010435717,0.00015699964,0.00054970686],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007830989,0.00020244923,0.03263708,8.0330295e-7,0.0000021650258,0.000018540726,0.00025982637,0.0027536885,0.0010558277,0.00014400845,0.0043846457,0.95846266],"study_design_scores_gemma":[0.0026865972,0.00026265267,0.38068426,0.00002521507,0.000028242106,0.000030033258,0.0022834283,0.025850803,0.0010955354,0.40709695,0.1794595,0.0004967877],"about_ca_topic_score_codex":0.000032080563,"about_ca_topic_score_gemma":0.00008620871,"teacher_disagreement_score":0.95796585,"about_ca_system_score_codex":0.00008150772,"about_ca_system_score_gemma":0.00004006613,"threshold_uncertainty_score":0.99778754},"labels":[],"label_agreement":null},{"id":"W4292367851","doi":"10.31234/osf.io/u3bxc","title":"Replicability of the neuroanatomical correlates of impulsive personality traits in the ABCD study","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; St. Joseph’s Healthcare Hamilton","funders":"","keywords":"Sensation seeking; Psychology; Impulsivity; Personality; Big Five personality traits; Developmental psychology; Similarity (geometry); Neuroimaging; Clinical psychology; Neuroscience; Social psychology","score_opus":0.15159379036983778,"score_gpt":0.42664324238466084,"score_spread":0.27504945201482306,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4292367851","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.994861,0.0000346739,0.000012290916,0.0008566422,0.0006928598,0.00125941,0.00018933015,0.00001131562,0.0020824515],"genre_scores_gemma":[0.99958205,0.0000028497059,0.000056597433,0.00013633927,0.000018552262,0.000053676784,0.0000024729425,0.000010634262,0.00013685148],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9924044,0.0021887973,0.0021203477,0.0011836565,0.0018890229,0.00021379297],"domain_scores_gemma":[0.9895835,0.005842423,0.0012488718,0.0029773952,0.00029908106,0.000048761656],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0124067655,0.0002615779,0.00091051194,0.00017817,0.0001319133,0.000117208714,0.004904736,0.00017352331,0.0014754321],"category_scores_gemma":[0.0056575225,0.00012614462,0.0006816924,0.00078959897,0.00041324686,0.00006872621,0.0034043384,0.0013814376,0.000008477969],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017368578,0.0025011094,0.91196835,0.000011674217,0.000029495013,0.00000997034,0.010354059,0.0023805897,0.000024187491,0.0005189922,0.0011194618,0.07090841],"study_design_scores_gemma":[0.00025618673,0.00013788485,0.8962762,0.0000121066005,0.000041213163,0.0000055856026,0.016348053,0.0012231198,0.000016649583,0.08530403,0.0002429438,0.0001360773],"about_ca_topic_score_codex":0.0015108159,"about_ca_topic_score_gemma":0.0007979771,"teacher_disagreement_score":0.08478504,"about_ca_system_score_codex":0.000102746,"about_ca_system_score_gemma":0.00028933465,"threshold_uncertainty_score":0.99943733},"labels":[],"label_agreement":null},{"id":"W4294129810","doi":"10.1037/pha0000596","title":"Income shock increases preferences for smaller immediate rewards and reduces alcohol demand among a sample of crowd-sourced adults.","year":2022,"lang":"en","type":"article","venue":"Experimental and Clinical Psychopharmacology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"National Institute on Alcohol Abuse and Alcoholism; McMaster University; University of Kansas","keywords":"Shock (circulatory); Discounting; Economics; Demographic economics; Consumption (sociology); Delay discounting; Psychology; Sample (material); Alcohol consumption; Social psychology; Demography; Alcohol; Medicine","score_opus":0.1176602447636869,"score_gpt":0.47260267744109424,"score_spread":0.3549424326774073,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294129810","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9966136,0.0009059133,0.000034733537,0.00017070514,0.0013762616,0.0005016685,0.0002285861,0.000022905968,0.00014558068],"genre_scores_gemma":[0.99844074,0.000087941175,0.000592889,0.00038189808,0.00016224012,0.00019795376,0.000013148088,0.00001570895,0.00010746659],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9966278,0.0004694858,0.001394055,0.0008461938,0.00037984978,0.00028260387],"domain_scores_gemma":[0.99423337,0.004613796,0.0005554239,0.00024318758,0.000087326014,0.00026690034],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0023549614,0.00020977246,0.0006736674,0.00017062198,0.00034117233,0.00007266094,0.0005496152,0.000121903526,0.0014080396],"category_scores_gemma":[0.0006761035,0.0001653035,0.00021226353,0.00019065975,0.0006659577,0.00016528725,0.0005990911,0.0002545809,0.0000056689837],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.015745096,0.0037745954,0.6356653,0.000021351107,0.0002767608,0.000019986019,0.0022813552,0.00005203078,0.013450976,0.00010123419,0.011097566,0.31751373],"study_design_scores_gemma":[0.05226775,0.021170858,0.7393886,0.0001321672,0.00046527837,0.00011595086,0.036973905,0.0060734185,0.028696796,0.08942433,0.022990987,0.0022999535],"about_ca_topic_score_codex":0.00017438814,"about_ca_topic_score_gemma":0.000021250728,"teacher_disagreement_score":0.31521377,"about_ca_system_score_codex":0.000025980853,"about_ca_system_score_gemma":0.000054882465,"threshold_uncertainty_score":0.9995048},"labels":[],"label_agreement":null},{"id":"W4294834599","doi":"10.1108/s1475-148820220000025011","title":"Do You See What I See? The Effects of Dissenting Opinion on Information Acquisition and Decision Quality: An Eye-Tracking Study","year":2022,"lang":"en","type":"book-chapter","venue":"Advances in accounting behavioral research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Dissenting opinion; Decision quality; Dissent; Quality (philosophy); Cognition; Cognitive resource theory; Psychology; Information processing; Cognitive psychology; Social psychology; Computer science; Political science; Knowledge management; Law; Epistemology","score_opus":0.19624700645304616,"score_gpt":0.54455771775751,"score_spread":0.3483107113044639,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294834599","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99176306,0.0020616504,0.000037605405,0.00005455037,0.0020640627,0.0016102784,0.000033516015,0.000039925235,0.0023353498],"genre_scores_gemma":[0.99611276,0.0027050145,0.00018609384,0.000041083385,0.00017544493,0.000103128215,0.00006442351,0.00006332662,0.0005487228],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98975617,0.0005668322,0.002169224,0.0012363285,0.005616966,0.00065451144],"domain_scores_gemma":[0.98744553,0.008131086,0.0015213643,0.0016941248,0.00107802,0.0001298996],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.021993047,0.00049458706,0.00089802005,0.0020516177,0.0010653523,0.0032719516,0.0018998272,0.00032627434,0.00040959512],"category_scores_gemma":[0.0031539865,0.00037321178,0.00020151678,0.0007484781,0.00040123984,0.010138599,0.0015555794,0.0019568782,0.000087558896],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002781057,0.0002776445,0.021528926,0.000041178937,0.0000055442088,0.000020735057,0.0024495118,0.00025970218,0.000068511945,0.001299963,0.00003638556,0.9737338],"study_design_scores_gemma":[0.006416193,0.010090802,0.19212449,0.011014417,0.00019497669,0.000051423514,0.12872055,0.0012198387,0.00033059868,0.48544273,0.16068445,0.0037095384],"about_ca_topic_score_codex":0.00023480925,"about_ca_topic_score_gemma":0.00029919954,"teacher_disagreement_score":0.9700242,"about_ca_system_score_codex":0.0004070752,"about_ca_system_score_gemma":0.00013641678,"threshold_uncertainty_score":0.99987197},"labels":[],"label_agreement":null},{"id":"W4300161208","doi":"10.2139/ssrn.1938787","title":"On the Antecedents of Uncertainty Aversion","year":2012,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Ambiguity aversion; Economics; Inequity aversion; Risk aversion (psychology); Econometrics; Psychology; Social psychology; Mathematical economics; Mathematics; Computer science; Expected utility hypothesis; Ambiguity","score_opus":0.07610903075126116,"score_gpt":0.3686019340387906,"score_spread":0.2924929032875294,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4300161208","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9955473,0.00029198534,0.000974637,0.00063335005,0.0006660834,0.0000571867,0.0000027914505,0.0000063648345,0.0018202891],"genre_scores_gemma":[0.9986934,0.00020789201,0.000017618311,0.00014177692,0.00013122344,7.2310286e-7,3.3373993e-7,0.000007849825,0.0007991493],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99711,0.00018564017,0.0004985151,0.0001524062,0.00084322196,0.0012102078],"domain_scores_gemma":[0.9979642,0.001001832,0.0004132087,0.00038184653,0.00014888778,0.00009001095],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010273097,0.00010787212,0.00019353633,0.00017153016,0.0002528414,0.00009055871,0.0008963209,0.00006082923,0.0003936743],"category_scores_gemma":[0.0013083742,0.000055312885,0.00019273692,0.00029077867,0.00007006855,0.00026612685,0.000084098305,0.0009226123,0.0005223595],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021514967,0.00029511173,0.011564048,5.0895227e-7,0.000047014306,0.0000014081347,0.00040918775,0.0005421872,0.00063467515,0.15953296,0.004990168,0.82176757],"study_design_scores_gemma":[0.00027818367,0.00026606908,0.0017512242,0.000017913195,0.000014552458,0.00012845614,0.0032750631,0.00020194649,0.000206931,0.988918,0.0048410334,0.00010064704],"about_ca_topic_score_codex":0.000021999771,"about_ca_topic_score_gemma":0.000054747212,"teacher_disagreement_score":0.82938504,"about_ca_system_score_codex":0.00038952153,"about_ca_system_score_gemma":0.00040313823,"threshold_uncertainty_score":0.6714049},"labels":[],"label_agreement":null},{"id":"W4306630471","doi":"10.1111/irfi.12399","title":"Buy and buy again: The impact of unique reference points on (re)purchase decisions","year":2022,"lang":"en","type":"article","venue":"International Review of Finance","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Representativeness heuristic; Point (geometry); Business; Disposition effect; Profitability index; Reference price; Behavioral economics; Heuristic; Stock trading; Stock (firearms); Point of sale; Marketing; Actuarial science; Finance; Economics; Microeconomics; Stock market; Computer science; Psychology","score_opus":0.19146611052498674,"score_gpt":0.47310454485785297,"score_spread":0.2816384343328662,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4306630471","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98196477,0.006233279,0.00026628672,0.0043525295,0.00034133016,0.00026922012,0.00048046987,0.0000063502366,0.0060857534],"genre_scores_gemma":[0.985183,0.012860629,0.0005583233,0.0009400823,0.000018162524,0.000028799841,0.0000092566725,0.0000070771,0.0003946658],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99738896,0.00018202135,0.0009604864,0.00034774363,0.0010034544,0.00011731794],"domain_scores_gemma":[0.99575096,0.002153518,0.0008132613,0.00067890494,0.00056218565,0.000041182877],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0031744938,0.00012700404,0.00038384637,0.00016721597,0.00012053896,0.000036402747,0.0014489058,0.000026483296,0.0011257692],"category_scores_gemma":[0.0073721646,0.00007506711,0.00022896123,0.00041309567,0.00012542664,0.00013368047,0.000445192,0.00022795932,0.0000487339],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008479846,0.00018002707,0.0010254706,0.000013503701,0.000015860933,0.000010796774,0.000087193,0.00065267825,0.000065864006,0.0095535405,0.02772403,0.96058625],"study_design_scores_gemma":[0.00092728063,0.0013950415,0.08624288,0.006165225,0.000038081915,0.0001392698,0.00027941127,0.0031329975,0.0003222445,0.31054035,0.5903133,0.00050392275],"about_ca_topic_score_codex":0.0000726261,"about_ca_topic_score_gemma":0.0000067748897,"teacher_disagreement_score":0.9600823,"about_ca_system_score_codex":0.00009762993,"about_ca_system_score_gemma":0.00015890432,"threshold_uncertainty_score":0.99978733},"labels":[],"label_agreement":null},{"id":"W4307336493","doi":"10.1017/s0140525x22001054","title":"A reputational perspective on rational framing effects","year":2022,"lang":"en","type":"letter","venue":"Behavioral and Brain Sciences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Framing (construction); Irrational number; Framing effect; Irrationality; Positive economics; Psychology; Prospect theory; Social psychology; Perspective (graphical); Economics; Rationality; Political science; Microeconomics; Computer science; Law; Engineering","score_opus":0.15277223386475944,"score_gpt":0.4394477405193199,"score_spread":0.28667550665456043,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4307336493","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.49276188,0.00021639591,0.000068740796,0.5002141,0.0023413065,0.0004621805,0.0002898447,0.00007804766,0.003567524],"genre_scores_gemma":[0.21812886,0.000015077636,0.0029402452,0.7614327,0.003164035,0.00025729646,0.00021694697,0.00007239614,0.013772428],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99295276,0.00048833765,0.0007703929,0.0018272963,0.003461198,0.0005000321],"domain_scores_gemma":[0.9926354,0.0059194253,0.0005731712,0.00047106037,0.00028245672,0.00011845818],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003352373,0.0004149433,0.00058862,0.00092148385,0.0015563121,0.0015628362,0.0013904476,0.00036280422,0.001981503],"category_scores_gemma":[0.001792493,0.00030409422,0.00027883172,0.0010209688,0.0009391253,0.00055857154,0.00044016071,0.0013655409,0.00018699082],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025578296,0.000112884074,0.00076446246,0.0000035906264,0.000005753447,0.00033375766,0.0006087744,0.00008706791,0.000028814187,0.001530413,0.89780235,0.098696575],"study_design_scores_gemma":[0.00039167897,0.0017431814,0.0031100782,0.000064894695,0.000046559428,0.00014427865,0.0022491252,0.00034895568,0.00002370018,0.20293103,0.788152,0.00079450756],"about_ca_topic_score_codex":0.00020175491,"about_ca_topic_score_gemma":0.000025289699,"teacher_disagreement_score":0.27463302,"about_ca_system_score_codex":0.00026318594,"about_ca_system_score_gemma":0.0004541946,"threshold_uncertainty_score":0.9999411},"labels":[],"label_agreement":null},{"id":"W4307338787","doi":"10.1017/s0140525x22001030","title":"Reframing rationality: Exogenous constraints on controlled information search","year":2022,"lang":"en","type":"letter","venue":"Behavioral and Brain Sciences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"Canada Research Chairs","keywords":"Framing (construction); Rationality; Cognitive reframing; Frame problem; Ecological rationality; Framing effect; Selection (genetic algorithm); Computer science; Economics; Psychology; Social psychology; Epistemology; Artificial intelligence; Engineering; Persuasion; Philosophy","score_opus":0.2101946881051097,"score_gpt":0.4225328666471056,"score_spread":0.2123381785419959,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4307338787","genre_codex":"empirical","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.65948254,0.00007961851,0.00009752208,0.3303973,0.0018624449,0.0010022502,0.00077125576,0.000090756774,0.006216294],"genre_scores_gemma":[0.44343147,0.000025857295,0.0010059191,0.54925007,0.001151642,0.00020758131,0.0004940067,0.000036523572,0.004396959],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9920896,0.0006951179,0.001537972,0.0010645585,0.003961296,0.0006514245],"domain_scores_gemma":[0.9943686,0.0037432774,0.0007784643,0.0006214077,0.0003372105,0.00015103788],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.009042007,0.00043686441,0.00094311323,0.0011354594,0.0017269162,0.0027777092,0.0016819326,0.00044408187,0.00491771],"category_scores_gemma":[0.0012646692,0.0003060659,0.0003124699,0.0009471191,0.00158271,0.0012295417,0.00047973546,0.0014163001,0.0003654966],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000095887,0.00007464366,0.0004106743,0.000004469561,0.000007103318,0.00010202049,0.00062510156,0.00007255744,0.00002165048,0.0002519955,0.43607923,0.56225467],"study_design_scores_gemma":[0.0017455121,0.0013928914,0.0006960207,0.000050619936,0.00005314347,0.00015762298,0.002928366,0.00049226085,0.000018543782,0.012842398,0.9788519,0.00077070727],"about_ca_topic_score_codex":0.0001906365,"about_ca_topic_score_gemma":0.000021941081,"teacher_disagreement_score":0.561484,"about_ca_system_score_codex":0.00015684361,"about_ca_system_score_gemma":0.0005933524,"threshold_uncertainty_score":0.99993914},"labels":[],"label_agreement":null},{"id":"W4307342167","doi":"10.1017/s0140525x22000954","title":"Framing, equivalence, and rational inference","year":2022,"lang":"en","type":"letter","venue":"Behavioral and Brain Sciences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Framing (construction); Framing effect; Logical equivalence; Rationality; Inference; Psychology; Epistemology; Extensional definition; Social psychology; Cognitive psychology; Mathematics; Equivalence (formal languages); Philosophy; Discrete mathematics","score_opus":0.26183985187687364,"score_gpt":0.4497864488482503,"score_spread":0.18794659697137667,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4307342167","genre_codex":"empirical","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7447793,0.0005819291,0.000078440484,0.25098518,0.0014216714,0.00028537188,0.00034487215,0.00006522945,0.0014580352],"genre_scores_gemma":[0.4318043,0.00025251147,0.0041439184,0.5374053,0.0023122092,0.0001774989,0.00020061313,0.00007470187,0.02362897],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99387485,0.00031856747,0.0009513675,0.0016981646,0.0025695462,0.00058749726],"domain_scores_gemma":[0.99552363,0.0030277402,0.0005783226,0.0005384156,0.00016818928,0.0001637088],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0039208885,0.00042613622,0.000639177,0.0007392943,0.0014168279,0.002264482,0.0017379269,0.00041805863,0.0034441196],"category_scores_gemma":[0.0010018554,0.00031059465,0.00015076704,0.000918955,0.0018571803,0.0008668466,0.0012125724,0.0012204184,0.00008190195],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007536867,0.000044508353,0.012121041,0.0000056411263,0.0000025687825,0.00012614622,0.00026724878,0.000007755999,0.00003638713,0.00026148945,0.7206098,0.26650986],"study_design_scores_gemma":[0.00016561137,0.00053659064,0.0039952295,0.000033681266,0.000028669117,0.000108677676,0.000520028,0.00024756847,0.0000062890463,0.056489084,0.9373019,0.0005667104],"about_ca_topic_score_codex":0.0002159237,"about_ca_topic_score_gemma":0.000069731,"teacher_disagreement_score":0.312975,"about_ca_system_score_codex":0.000049898095,"about_ca_system_score_gemma":0.00038115837,"threshold_uncertainty_score":0.9999346},"labels":[],"label_agreement":null},{"id":"W4307697007","doi":"10.1093/oxfordhb/9780197501061.013.2","title":"Uncertainty Definitions and Their Problems","year":2022,"lang":"en","type":"book-chapter","venue":"Oxford University Press eBooks","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Appeal; Epistemology; Uncertainty quantification; Management science; Computer science; Political science; Economics; Philosophy; Law","score_opus":0.18864019421376857,"score_gpt":0.2850304944203758,"score_spread":0.09639030020660724,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4307697007","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0027712171,0.00007937729,0.00016219543,0.000056748915,0.00030387682,0.0002987771,0.0009695362,0.00008327519,0.995275],"genre_scores_gemma":[0.010400565,0.0004367935,0.00019448886,0.000095036296,0.000046238685,0.0000021073054,0.000049936603,0.000038922837,0.9887359],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9979708,0.00007010774,0.00040742813,0.00081152096,0.0004913591,0.00024878915],"domain_scores_gemma":[0.9976054,0.00075309124,0.00044258207,0.0008462888,0.00017183392,0.00018080659],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00059265835,0.0003431609,0.0005253516,0.0004040952,0.0006477904,0.00024273215,0.0010798747,0.00026087038,0.0008544931],"category_scores_gemma":[0.000056315734,0.00030289634,0.0002825933,0.00002291518,0.00030687943,0.00017815946,0.0012401077,0.0005550546,0.000008075316],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000058537502,0.000018864674,0.000009574406,0.000006229415,0.000046504243,0.00006228051,0.0004220766,0.00029815082,0.0000027430667,0.74714893,0.004860745,0.24706534],"study_design_scores_gemma":[0.00023047697,0.000071021015,0.000004484068,0.000031122177,0.000047039208,0.000020180194,0.00024172242,0.0001487513,0.000001474441,0.1602501,0.8386575,0.0002961312],"about_ca_topic_score_codex":0.00007839807,"about_ca_topic_score_gemma":0.00010612049,"teacher_disagreement_score":0.83379674,"about_ca_system_score_codex":0.00017066982,"about_ca_system_score_gemma":0.0001291019,"threshold_uncertainty_score":0.9999423},"labels":[],"label_agreement":null},{"id":"W4307764679","doi":"10.31234/osf.io/3rcvj","title":"Blind to Bias? Young Children Do Not Anticipate that Sunk Costs Lead to Irrational Choices","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Sunk costs; Irrational number; Interpersonal communication; Economics; Microeconomics; Psychology; Social psychology; Mathematics","score_opus":0.37343658058715024,"score_gpt":0.4642055986083826,"score_spread":0.09076901802123238,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4307764679","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9758584,0.000046818644,0.0012679965,0.0027209788,0.0048493366,0.0011657211,0.0007772227,0.000131957,0.013181569],"genre_scores_gemma":[0.9785146,0.000018321643,0.0054668854,0.002433952,0.00042557155,0.0001634928,0.00015000155,0.000055752,0.012771392],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9920818,0.00029355963,0.0015691804,0.0023719533,0.0030408427,0.0006426348],"domain_scores_gemma":[0.9947658,0.0013787397,0.0006817154,0.0021878881,0.0004644248,0.0005213849],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0050160843,0.0005882786,0.0009981253,0.0014597119,0.00050421496,0.0035574627,0.0038294792,0.000336654,0.011684632],"category_scores_gemma":[0.0022257385,0.00047435443,0.00046454146,0.0009178493,0.000078595425,0.00041008135,0.005330394,0.00087050203,0.005160831],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005414614,0.00047590266,0.36608785,0.0000058152154,0.00010560523,0.000046237343,0.0015370144,0.027369026,0.00016484463,0.0008375855,0.10147342,0.50135523],"study_design_scores_gemma":[0.0013214684,0.0004683006,0.89663345,0.00021147386,0.000133134,0.00008171634,0.0017166904,0.0017335669,0.000860198,0.018714411,0.07541472,0.00271088],"about_ca_topic_score_codex":0.0013645564,"about_ca_topic_score_gemma":0.0019150255,"teacher_disagreement_score":0.5305456,"about_ca_system_score_codex":0.00040197631,"about_ca_system_score_gemma":0.00038379506,"threshold_uncertainty_score":0.9997708},"labels":[],"label_agreement":null},{"id":"W4308001699","doi":"10.31234/osf.io/dsp58","title":"Novelty preferences depend on goals","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; University of Waterloo","keywords":"Novelty; Set (abstract data type); Psychology; Social psychology; Cognitive psychology; Computer science","score_opus":0.4310131025307807,"score_gpt":0.4897052054179808,"score_spread":0.058692102887200115,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4308001699","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.81457967,0.000055666813,0.00042515434,0.0005394851,0.0040133647,0.00030683432,0.0002831165,0.00011848909,0.17967822],"genre_scores_gemma":[0.98121375,0.00003250414,0.0023321775,0.0006275864,0.00016558911,0.000073008465,0.000039513143,0.000028266863,0.015487603],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9940302,0.00027819345,0.0013432379,0.0017535998,0.0022265753,0.00036820685],"domain_scores_gemma":[0.9940796,0.00241864,0.00074736023,0.0023486034,0.00021444145,0.00019135587],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0038680097,0.00041158058,0.0008035328,0.0005965714,0.00028430478,0.0013143442,0.0037759847,0.00033304168,0.04794963],"category_scores_gemma":[0.001894319,0.0002854524,0.00044764133,0.00035483684,0.00006776245,0.00015759541,0.0040874435,0.0011514076,0.003764166],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006767673,0.00027484636,0.004211567,0.0000037140617,0.000021955484,0.000027809492,0.00017330454,0.007480133,0.000010817805,0.001928031,0.048514426,0.9372857],"study_design_scores_gemma":[0.00024928764,0.00023143459,0.0074934424,0.00004587429,0.000029429544,0.000007257217,0.00083392824,0.0011871414,0.00014704323,0.74373466,0.24530484,0.0007356586],"about_ca_topic_score_codex":0.00024185139,"about_ca_topic_score_gemma":0.00033920223,"teacher_disagreement_score":0.9365501,"about_ca_system_score_codex":0.00017859176,"about_ca_system_score_gemma":0.0003443511,"threshold_uncertainty_score":0.99995977},"labels":[],"label_agreement":null},{"id":"W4309456555","doi":"10.3390/jintelligence10040109","title":"When Type 2 Processing Misfires: The Indiscriminate Use of Statistical Thinking about Reasoning Problems","year":2022,"lang":"en","type":"article","venue":"Journal of Intelligence","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Fundação para a Ciência e a Tecnologia; Universidade de Lisboa; Alexander von Humboldt-Stiftung","keywords":"Spurious relationship; Probabilistic logic; Set (abstract data type); Base (topology); Cognitive psychology; Computer science; Sensitivity (control systems); Outcome (game theory); Process (computing); Psychology; Artificial intelligence; Machine learning; Mathematics","score_opus":0.21168252230681614,"score_gpt":0.41002459648873135,"score_spread":0.1983420741819152,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4309456555","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9299018,0.0010154042,0.06696848,0.0006202231,0.0009969488,0.00013239308,0.000020196137,0.000009038869,0.00033553079],"genre_scores_gemma":[0.98165953,0.000058632388,0.01781585,0.00020281483,0.000056594086,0.0000018270736,6.180806e-7,0.000012513499,0.00019162822],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9961815,0.0002954154,0.0014949401,0.00022762024,0.0015865416,0.00021400602],"domain_scores_gemma":[0.9952574,0.0018323836,0.0016809702,0.00034202167,0.00079986424,0.00008739157],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005798635,0.00012401791,0.00035763744,0.0002668869,0.00043905957,0.00050734344,0.0015379835,0.000038742477,0.00064582645],"category_scores_gemma":[0.005424374,0.00007260627,0.00012797811,0.0005357187,0.00018204481,0.0005595344,0.0003634954,0.00060807494,0.000016102587],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017066645,0.00013288221,0.0044127116,0.000010196288,0.000017349681,0.00007054162,0.011334218,0.03164723,0.00022556343,0.0017397134,0.0046952064,0.9455437],"study_design_scores_gemma":[0.00025599787,0.00171483,0.007443729,0.0009658282,0.00016326498,0.0013282814,0.029389745,0.03755666,0.0017820703,0.82536733,0.093486175,0.00054609904],"about_ca_topic_score_codex":0.000054304888,"about_ca_topic_score_gemma":0.000013837296,"teacher_disagreement_score":0.9449976,"about_ca_system_score_codex":0.0000990626,"about_ca_system_score_gemma":0.00033969255,"threshold_uncertainty_score":0.7071347},"labels":[],"label_agreement":null},{"id":"W4310089850","doi":"10.1037/xge0001300","title":"Arbitrary fairness in reward and punishments.","year":2022,"lang":"en","type":"article","venue":"Journal of Experimental Psychology General","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"John E. Fetzer Memorial Trust","keywords":"Salient; Interchangeability; Social psychology; PsycINFO; Unit (ring theory); Preference; Psychology; Microeconomics; Computer science; Economics; Mathematical economics; Law; Political science; Artificial intelligence","score_opus":0.14764415907768302,"score_gpt":0.4786786134730557,"score_spread":0.33103445439537266,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4310089850","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9930526,0.0012644512,0.0000379426,0.0008764609,0.0022517096,0.000061689665,0.0000066879443,0.000004188653,0.0024442768],"genre_scores_gemma":[0.9961519,0.000020489582,0.0016738849,0.0017734509,0.00012427694,0.000006154753,9.843423e-7,0.000010382955,0.00023844015],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9975448,0.0003761768,0.0009871997,0.00031860272,0.0005682759,0.00020494178],"domain_scores_gemma":[0.99894005,0.00014614244,0.00047856476,0.00027249247,0.000045725654,0.000116998825],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0024802273,0.0001222086,0.00036614892,0.0005290738,0.00015989314,0.00008186315,0.00067436945,0.00005644922,0.001060913],"category_scores_gemma":[0.000078757825,0.00010087324,0.00012704027,0.00030853116,0.000112695634,0.00029213092,0.0002743413,0.00048626674,0.000016565065],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003173262,0.004485449,0.3111188,0.000001813862,0.00009231575,0.002763938,0.0070517715,0.0010198178,0.1636927,0.0019113376,0.14013757,0.36455122],"study_design_scores_gemma":[0.018276172,0.008538753,0.28966263,0.000046128313,0.00004902067,0.01545209,0.03285812,0.0006858479,0.014231404,0.37307793,0.2455453,0.0015765917],"about_ca_topic_score_codex":0.0000093362,"about_ca_topic_score_gemma":0.0000022970387,"teacher_disagreement_score":0.37116662,"about_ca_system_score_codex":0.00010423159,"about_ca_system_score_gemma":0.000046586534,"threshold_uncertainty_score":0.99985224},"labels":[],"label_agreement":null},{"id":"W4310482589","doi":"10.1007/s11002-022-09657-0","title":"How uncertainty affects information search among consumers: a curvilinear perspective","year":2022,"lang":"en","type":"article","venue":"Marketing Letters","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada); Concordia University","funders":"Concordia University; Northwestern University","keywords":"Perspective (graphical); Contrast (vision); Product (mathematics); Econometrics; Computer science; Economics; Mathematics","score_opus":0.05428774371059829,"score_gpt":0.33202847526915497,"score_spread":0.27774073155855666,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4310482589","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9846477,0.000021757893,0.0006448737,0.011172053,0.0006916176,0.00028017448,0.000047079022,0.00008300023,0.0024117448],"genre_scores_gemma":[0.9974746,0.0000016384688,0.0005293895,0.001566271,0.000059030666,0.000034832832,0.000013108916,0.000013612872,0.00030752298],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99611896,0.0011693717,0.00040327577,0.00047310142,0.001429092,0.00040620792],"domain_scores_gemma":[0.99571395,0.0030583206,0.00032377907,0.0005593673,0.00022411505,0.00012049058],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.009936469,0.00018011522,0.00027564162,0.0005339704,0.00071397994,0.001216744,0.00085008395,0.000044852706,0.00054126594],"category_scores_gemma":[0.00518609,0.00016082697,0.00018170517,0.00081574044,0.00018920959,0.0009644258,0.0005611279,0.00049780036,0.000105045096],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00079832633,0.00011608197,0.124526225,0.000015027252,0.00005784243,0.00009549126,0.0070098266,0.023527585,0.0011527109,0.00020446714,0.1285833,0.71391314],"study_design_scores_gemma":[0.0037270014,0.00045638156,0.15987487,0.00012302204,0.00009622135,0.0001496558,0.31411207,0.12417064,0.00029816257,0.0035304972,0.3912636,0.0021978884],"about_ca_topic_score_codex":0.0002690841,"about_ca_topic_score_gemma":0.000030357669,"teacher_disagreement_score":0.7117152,"about_ca_system_score_codex":0.00049968046,"about_ca_system_score_gemma":0.00008090605,"threshold_uncertainty_score":0.9998201},"labels":[],"label_agreement":null},{"id":"W4310613873","doi":"10.1016/j.jebo.2022.11.016","title":"Comparative incompleteness: Measurement, behavioral manifestations and elicitation","year":2022,"lang":"en","type":"article","venue":"Journal of Economic Behavior & Organization","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada; Aarhus Universitets Forskningsfond; Aarhus Universitet","keywords":"Computer science","score_opus":0.28435190834990415,"score_gpt":0.42293090504320824,"score_spread":0.1385789966933041,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4310613873","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9965734,0.000042331278,0.0014412466,0.00039065717,0.0012041102,0.00020317019,0.000050018178,0.000016331318,0.00007872481],"genre_scores_gemma":[0.9988539,0.000009023896,0.0008582738,0.0000665986,0.00009962023,0.000010863321,0.000022999287,0.00002452042,0.000054169752],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9971343,0.00026905767,0.0013290936,0.00031541224,0.00076833885,0.00018377337],"domain_scores_gemma":[0.9971742,0.0001744338,0.0012205031,0.00027316815,0.0010248699,0.0001328106],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0028736286,0.00016941725,0.00045402418,0.00064650434,0.00062294607,0.0003640622,0.0005428005,0.000050793595,0.0014237756],"category_scores_gemma":[0.00019457798,0.00014626775,0.0000967777,0.00034283585,0.00007421227,0.00093108346,0.00022157413,0.0002623925,0.00009267913],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027919753,0.0024127027,0.63565916,0.000007910695,0.000114963135,0.00016338329,0.01814802,0.025201825,0.07701245,0.0028512815,0.0140614435,0.22408769],"study_design_scores_gemma":[0.0056780074,0.0029439395,0.8549051,0.000048710033,0.0011808512,0.004656844,0.046280745,0.0029012116,0.009216786,0.041630894,0.028858246,0.0016986562],"about_ca_topic_score_codex":0.000031599186,"about_ca_topic_score_gemma":0.00005407086,"teacher_disagreement_score":0.22238903,"about_ca_system_score_codex":0.0007967693,"about_ca_system_score_gemma":0.00024414505,"threshold_uncertainty_score":0.99948907},"labels":[],"label_agreement":null},{"id":"W4310641393","doi":"10.1177/17456916221134575","title":"Improving the Generalizability of Behavioral Science by Using Reality Checks: A Tool for Assessing Heterogeneity in Participants’ Consumership of Study Stimuli","year":2022,"lang":"en","type":"article","venue":"Perspectives on Psychological Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"","keywords":"Generalizability theory; Realism; Psychology; Relevance (law); External validity; Writ; Cognitive psychology; Ecological validity; Behavioural sciences; Social psychology; Nomothetic; Experimental psychology; Epistemology; Cognition; Developmental psychology; Psychotherapist","score_opus":0.48277439023773405,"score_gpt":0.5657951970758375,"score_spread":0.08302080683810342,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4310641393","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.997386,0.000041153842,0.0010639946,0.00013646304,0.00036619735,0.0008607756,0.0000825977,0.000014799578,0.000048034442],"genre_scores_gemma":[0.9985084,9.006198e-7,0.0013513643,0.000054176784,0.000009988552,0.00006545353,3.361648e-7,0.0000057580237,0.000003606734],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9936182,0.0007234253,0.0011263062,0.0017577233,0.0021279291,0.00064640015],"domain_scores_gemma":[0.9959325,0.0013279689,0.000756519,0.0012906098,0.000555446,0.00013696332],"candidate_categories":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.03311624,0.00018902012,0.0004915916,0.00034773478,0.001135418,0.00032146717,0.0028451658,0.00004298082,0.00008619465],"category_scores_gemma":[0.005914487,0.00012076805,0.00015942959,0.003373705,0.0044880854,0.0006083165,0.00072766637,0.00031230642,9.474791e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005402004,0.009901172,0.67405784,0.0000036809154,0.0000054894685,0.0000052049745,0.0097303605,0.0052678017,0.20191179,0.00044761007,0.000031867483,0.09809697],"study_design_scores_gemma":[0.0017675338,0.0029074855,0.8088639,0.000015958238,0.000044601282,0.000011594881,0.14516024,0.026040535,0.0058138133,0.008825495,0.00002265796,0.0005262304],"about_ca_topic_score_codex":0.00047644417,"about_ca_topic_score_gemma":0.00003203445,"teacher_disagreement_score":0.19609798,"about_ca_system_score_codex":0.00057947263,"about_ca_system_score_gemma":0.00030624226,"threshold_uncertainty_score":0.9982211},"labels":[],"label_agreement":null},{"id":"W4313425009","doi":"10.1017/s1930297500008603","title":"Facilitating sender-receiver agreement in communicated probabilities: Is it best to use words, numbers or both?","year":2021,"lang":"en","type":"article","venue":"Judgment and Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"Ministère de la Défense Nationale","keywords":"Communication source; Agreement; Meaning (existential); Bounded function; Computer science; Scheme (mathematics); Natural language processing; Statistics; Linguistics; Psychology; Mathematics","score_opus":0.2893744416054432,"score_gpt":0.43794357005309287,"score_spread":0.1485691284476497,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313425009","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99056184,0.00014331013,0.00463279,0.0012952753,0.00046646458,0.00044550517,0.0000608367,0.00002966189,0.0023642972],"genre_scores_gemma":[0.90759516,0.0000929514,0.085421436,0.0028831726,0.000027655784,0.0000328318,0.0000048428433,0.000023292047,0.003918658],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9948468,0.00026504198,0.0017357063,0.0011732318,0.0014312691,0.00054794986],"domain_scores_gemma":[0.98786616,0.009788013,0.0003151852,0.001433086,0.00035333127,0.00024419502],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0029215955,0.0003492203,0.0006777677,0.0005349285,0.00039374092,0.0014923376,0.00079288776,0.00016991339,0.00296871],"category_scores_gemma":[0.0062271026,0.0002684011,0.00017309771,0.0013732952,0.00010078772,0.0007378459,0.0012227694,0.0003253642,0.00061882485],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035145332,0.00027924188,0.021964252,0.00000815001,0.00001580106,0.00012388112,0.01010616,0.0011135367,0.00010216368,0.00007709438,0.022873642,0.94298464],"study_design_scores_gemma":[0.0064130398,0.0009682854,0.021690913,0.0050068484,0.00011772087,0.00019916947,0.3061371,0.036655802,0.00046467272,0.20828362,0.41089386,0.0031689678],"about_ca_topic_score_codex":0.00016762341,"about_ca_topic_score_gemma":0.002505027,"teacher_disagreement_score":0.93981564,"about_ca_system_score_codex":0.00027570198,"about_ca_system_score_gemma":0.00015305266,"threshold_uncertainty_score":0.9999768},"labels":[],"label_agreement":null},{"id":"W4313425078","doi":"10.1017/s1930297500007920","title":"Effect of confidence interval construction on judgment accuracy","year":2020,"lang":"en","type":"article","venue":"Judgment and Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Confidence interval; Univariate; Statistics; Range (aeronautics); Interval (graph theory); Expert elicitation; Skepticism; Psychology; Mathematics; Social psychology; Multivariate statistics; Engineering; Epistemology","score_opus":0.10031021409711671,"score_gpt":0.408698774410091,"score_spread":0.3083885603129743,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313425078","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.980232,0.00010816463,0.0164894,0.0004875514,0.0008561691,0.00031548354,0.000014763641,0.000042427302,0.0014540392],"genre_scores_gemma":[0.9941151,0.000033069136,0.004975166,0.0007297912,0.00010704117,0.000008262741,0.0000010458292,0.0000149204225,0.000015559863],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9962112,0.00018727628,0.0012294226,0.00080109894,0.0013191248,0.00025190573],"domain_scores_gemma":[0.9899012,0.00855609,0.0006669978,0.0005217568,0.0001606791,0.00019327433],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002555722,0.00027184756,0.0006673851,0.0002946615,0.0001697836,0.000401878,0.0006141129,0.00012053275,0.00059032027],"category_scores_gemma":[0.005618567,0.00018811008,0.00022478758,0.00045955312,0.00015432127,0.0003768791,0.00040170478,0.00023422446,0.00035284387],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010868659,0.000029671639,0.0035258015,0.000008717788,0.000009046158,0.000014236354,0.00021164365,0.00030059234,0.000555896,0.0008431009,0.0026525664,0.9907619],"study_design_scores_gemma":[0.0152448015,0.023297757,0.018985614,0.004860465,0.0004916291,0.00029547492,0.005301521,0.11841484,0.066997126,0.68164766,0.060998317,0.0034647868],"about_ca_topic_score_codex":0.0000041981325,"about_ca_topic_score_gemma":0.0000021455985,"teacher_disagreement_score":0.98729706,"about_ca_system_score_codex":0.000050446433,"about_ca_system_score_gemma":0.00003332727,"threshold_uncertainty_score":0.7670906},"labels":[],"label_agreement":null},{"id":"W4313429046","doi":"10.1017/s1930297500008159","title":"Coherence of probability judgments from uncertain evidence: Does ACH help?","year":2020,"lang":"en","type":"article","venue":"Judgment and Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Probabilistic logic; Credibility; Coherence (philosophical gambling strategy); Weighting; Psychology; Bayesian probability; Empirical evidence; Reliability (semiconductor); Cognitive psychology; Social psychology; Inter-rater reliability; Computer science; Statistics; Econometrics; Mathematics; Artificial intelligence; Medicine; Rating scale","score_opus":0.27471690520012837,"score_gpt":0.41853323124620895,"score_spread":0.14381632604608058,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313429046","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98676705,0.00058649044,0.01020529,0.000968569,0.0005725029,0.00042201378,0.0000665796,0.00004897081,0.0003625103],"genre_scores_gemma":[0.9619377,0.000047703343,0.03709251,0.00072980893,0.00011998453,0.000014818855,0.000002212146,0.000015935484,0.000039296472],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.994666,0.00017895506,0.0016685132,0.0012588017,0.0018865917,0.00034118473],"domain_scores_gemma":[0.99150604,0.006241347,0.00075248233,0.0008746084,0.0003525057,0.00027301876],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002569813,0.00030861355,0.0007608943,0.00018610254,0.00021441255,0.0005380169,0.0011613405,0.00017274098,0.0013964068],"category_scores_gemma":[0.0065645794,0.00019568265,0.00021385068,0.0007026511,0.00018975491,0.0007136144,0.0008442696,0.0002474351,0.00022214696],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005006103,0.000095650576,0.09104511,0.000010059586,0.000013904363,0.000014518564,0.000736005,0.0003620766,0.0015489936,0.00010555009,0.0050702253,0.9004973],"study_design_scores_gemma":[0.0011168055,0.00043425677,0.041754935,0.0010222377,0.000073608964,0.000003984824,0.0018873682,0.012528921,0.0020538657,0.93431,0.004174553,0.00063942804],"about_ca_topic_score_codex":0.000059463124,"about_ca_topic_score_gemma":0.000033040724,"teacher_disagreement_score":0.93420446,"about_ca_system_score_codex":0.00007598035,"about_ca_system_score_gemma":0.00009940219,"threshold_uncertainty_score":0.9995164},"labels":[],"label_agreement":null},{"id":"W4313429049","doi":"10.1017/s1930297500008652","title":"Denotative and connotative management of uncertainty: A computational dual-process model","year":2021,"lang":"en","type":"article","venue":"Judgment and Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph; University of Waterloo","funders":"Deutsche Forschungsgemeinschaft","keywords":"Computer science; Rationality; Artificial intelligence; Dual (grammatical number); Management science; Epistemology","score_opus":0.11985350020386008,"score_gpt":0.42750152347370346,"score_spread":0.30764802326984336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313429049","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8930243,0.00033522362,0.10434004,0.00013605958,0.00013121516,0.00013900326,0.00003869117,0.000014439071,0.0018409857],"genre_scores_gemma":[0.9216931,0.000056408244,0.077848285,0.00023381662,0.00001256024,0.0000088805355,0.000004119426,0.000010911091,0.0001319354],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9970624,0.00006811248,0.00087927625,0.0007106558,0.0010749206,0.00020462101],"domain_scores_gemma":[0.9960786,0.0025306377,0.00040038125,0.00028944644,0.0005996521,0.00010129005],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012141069,0.0001949061,0.00044579082,0.00025471734,0.0002163149,0.0003226922,0.00020022846,0.00007069452,0.0001399769],"category_scores_gemma":[0.000385417,0.00015623347,0.00008654398,0.0004923379,0.0001589732,0.0002976002,0.00040788166,0.00011040177,0.00002205974],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018314911,0.000090866284,0.0009863637,0.000013640826,0.000039528855,0.000084936335,0.001602684,0.13472272,0.000036057867,0.010645281,0.00046947482,0.8511253],"study_design_scores_gemma":[0.00065672817,0.000037516496,0.0023765615,0.00020068098,0.000029967912,0.000019566856,0.005262042,0.2967065,0.00004161012,0.69441867,0.00009637485,0.0001537846],"about_ca_topic_score_codex":0.0000018162365,"about_ca_topic_score_gemma":0.000008081473,"teacher_disagreement_score":0.8509715,"about_ca_system_score_codex":0.000039988354,"about_ca_system_score_gemma":0.000074254036,"threshold_uncertainty_score":0.6371016},"labels":[],"label_agreement":null},{"id":"W4315434499","doi":"10.1017/9781009362627","title":"Estimation of Structural Models Using Experimental Data From the Lab and the Field","year":2023,"lang":"en","type":"book","venue":"Cambridge University Press eBooks","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Replicate; Structural estimation; Set (abstract data type); Computer science; Estimation; Field (mathematics); Experimental data; Element (criminal law); Machine learning; Software; Management science; Artificial intelligence; Econometrics; Data mining; Engineering; Mathematics; Statistics; Systems engineering","score_opus":0.2350825782111147,"score_gpt":0.3681970900039012,"score_spread":0.13311451179278652,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4315434499","genre_codex":"empirical","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.59098166,0.00091821956,0.007918293,0.00021562332,0.0020205413,0.0012784419,0.006364952,0.00011419254,0.3901881],"genre_scores_gemma":[0.22854763,0.000023369836,0.00061642757,0.00015965122,0.0001606689,5.157918e-7,0.00015016376,0.000032442505,0.77030915],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983162,0.00016921788,0.00035065835,0.00052748766,0.0005082117,0.00012818708],"domain_scores_gemma":[0.9941962,0.003706598,0.000452005,0.0015063623,0.00009059531,0.000048289803],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00070850464,0.0001849712,0.00038963038,0.000084291816,0.0003026118,0.0002292621,0.0022644121,0.00017229264,0.000006069361],"category_scores_gemma":[0.00027116927,0.00011406139,0.000108263135,0.00002785457,0.00046557916,0.00030269584,0.0023655163,0.0002635114,0.000004825627],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014564121,0.000024156645,0.000027898133,0.000019761048,0.00031322424,0.00011131461,0.0024245814,0.010577137,0.00006978643,0.18859185,0.6416133,0.15477054],"study_design_scores_gemma":[0.0012900286,0.00003341929,0.000033762928,0.00015906726,0.0002959226,0.000009050986,0.0013878327,0.95585185,0.00019919661,0.005865631,0.034538954,0.00033527624],"about_ca_topic_score_codex":0.0011972701,"about_ca_topic_score_gemma":0.000015662674,"teacher_disagreement_score":0.9452747,"about_ca_system_score_codex":0.0000724687,"about_ca_system_score_gemma":0.00015529584,"threshold_uncertainty_score":0.46512887},"labels":[],"label_agreement":null},{"id":"W4315752886","doi":"10.1186/s41235-022-00459-6","title":"A value accumulation account of unhealthy food choices: testing the influence of outcome salience under varying time constraints","year":2023,"lang":"en","type":"article","venue":"Cognitive Research Principles and Implications","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Trinity College","funders":"Vlaamse regering; KU Leuven; Fonds Wetenschappelijk Onderzoek","keywords":"Salience (neuroscience); Outcome (game theory); Value (mathematics); Economics; Psychology; Econometrics; Social psychology; Microeconomics; Cognitive psychology; Mathematics; Statistics","score_opus":0.7063597554522417,"score_gpt":0.5698500877862237,"score_spread":0.13650966766601802,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4315752886","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99605775,0.000044324817,0.0008846656,0.0008141391,0.00001827278,0.0005542753,0.00020468309,0.000026208512,0.001395687],"genre_scores_gemma":[0.99939656,0.00003240383,0.0003369306,0.000072316514,0.00001835746,0.00006484796,0.000008386149,0.000009362188,0.000060822913],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9971421,0.000333815,0.0009085184,0.00044546314,0.0008285269,0.00034157818],"domain_scores_gemma":[0.9762966,0.020212168,0.0004613504,0.00052275765,0.0023841641,0.00012297554],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0066222376,0.000104916086,0.0002545951,0.00045772022,0.0005961314,0.00017850487,0.00068844325,0.00006608854,0.000031983865],"category_scores_gemma":[0.020535892,0.000071572875,0.00005843713,0.002321112,0.0010823929,0.00036057553,0.0005685466,0.00024866912,0.00011804163],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005929106,0.00020675504,0.3762098,0.00005909792,0.000052742907,0.0000012330902,0.0016033527,0.013754235,0.020336378,0.025354372,0.00007022031,0.5622925],"study_design_scores_gemma":[0.00019843008,0.0001333605,0.93069875,0.0001262399,0.000011603747,0.0000060565603,0.0010830626,0.0057895742,0.00023646298,0.06146952,0.00016371834,0.00008323494],"about_ca_topic_score_codex":0.0000902862,"about_ca_topic_score_gemma":0.000019242641,"teacher_disagreement_score":0.5622093,"about_ca_system_score_codex":0.000043488937,"about_ca_system_score_gemma":0.00030690545,"threshold_uncertainty_score":0.9877145},"labels":[],"label_agreement":null},{"id":"W4317464635","doi":"10.48550/arxiv.2301.06930","title":"Risk-averse mean field games: exploitability and non-asymptotic analysis","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Hong Kong University of Science and Technology","keywords":"Regret; Uniqueness; Mathematical economics; Mathematics; Mean field theory; Perspective (graphical); Action (physics); Field (mathematics); Construct (python library); Applied mathematics; Mathematical optimization; Computer science; Mathematical analysis; Statistics; Pure mathematics; Physics","score_opus":0.23284196438567797,"score_gpt":0.29173817799019747,"score_spread":0.05889621360451949,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4317464635","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96763617,0.000016681903,0.02996177,0.00008918365,0.00081798324,0.00025367396,0.00015192258,0.00015131748,0.000921287],"genre_scores_gemma":[0.9969649,0.000267775,0.00027192596,0.00006192107,0.000062123065,0.0000013054217,0.000016859578,0.00002609808,0.0023270936],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99571925,0.0003784952,0.0007513004,0.002379627,0.00034421156,0.00042709935],"domain_scores_gemma":[0.99259514,0.0032947166,0.0008103705,0.0026282899,0.00031527813,0.00035619686],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0029820707,0.00043446152,0.0010334234,0.0013966606,0.00029337758,0.000456847,0.001741341,0.0005591726,0.0005478037],"category_scores_gemma":[0.0020934553,0.0004159232,0.0008670472,0.002253201,0.00023670802,0.00036394328,0.002420681,0.00089965237,0.00089202257],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015611929,0.0001878408,0.7473384,0.000020797368,0.0006527953,0.00035157538,0.0010937577,0.22366819,0.0000043566592,0.00045666224,0.002171954,0.023897568],"study_design_scores_gemma":[0.00082562026,0.00018730701,0.20818439,0.00008666332,0.0031473387,0.0000029371288,0.0065330276,0.33011052,0.000038724236,0.44875813,0.0008347057,0.0012906358],"about_ca_topic_score_codex":0.0017368026,"about_ca_topic_score_gemma":0.0028011107,"teacher_disagreement_score":0.539154,"about_ca_system_score_codex":0.00020351826,"about_ca_system_score_gemma":0.00014426194,"threshold_uncertainty_score":0.9998859},"labels":[],"label_agreement":null},{"id":"W4318672180","doi":"10.1177/17470218231155897","title":"Interpretation of ambiguous trials along with reasoning strategy is related to causal judgements in zero-contingency learning","year":2023,"lang":"en","type":"article","venue":"Quarterly Journal of Experimental Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Contingency; Psychology; Counterexample; Interpretation (philosophy); Cognitive psychology; Replicate; Computer science; Statistics; Mathematics; Linguistics","score_opus":0.129037561609868,"score_gpt":0.4848448086591169,"score_spread":0.3558072470492489,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4318672180","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9964557,0.00014799448,0.001264024,0.00017546164,0.0009825806,0.0001774595,0.0000035587984,0.000014901117,0.0007782839],"genre_scores_gemma":[0.998895,0.0000061359647,0.00079766137,0.000103101826,0.00003085277,0.000005825687,0.000002043098,0.000019825575,0.00013956749],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9952902,0.00070197735,0.0026742204,0.00041276548,0.00062128005,0.00029953703],"domain_scores_gemma":[0.99712795,0.00046044597,0.0017585811,0.00028347038,0.00023997443,0.00012960336],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006518958,0.00018434148,0.00086745643,0.0011525293,0.00006424199,0.00012323429,0.0005417401,0.00012580944,0.0002988102],"category_scores_gemma":[0.00057499437,0.0001396557,0.00019157978,0.0009309349,0.00007401898,0.0004520637,0.00003348668,0.00033711264,0.00016372032],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022871315,0.00038770327,0.026035087,0.0000019964366,0.00009294731,0.00028427294,0.027028063,0.001503013,0.06747953,0.000057477762,0.0020547698,0.872788],"study_design_scores_gemma":[0.03561123,0.11402186,0.44237137,0.0025503838,0.00029404683,0.0023313668,0.26807418,0.010982615,0.036532477,0.08277997,0.001811145,0.0026393451],"about_ca_topic_score_codex":0.000062425155,"about_ca_topic_score_gemma":0.000016898866,"teacher_disagreement_score":0.87014866,"about_ca_system_score_codex":0.00006947957,"about_ca_system_score_gemma":0.000054818167,"threshold_uncertainty_score":0.56949943},"labels":[],"label_agreement":null},{"id":"W4319232666","doi":"10.31234/osf.io/dm8xn","title":"An aberrant abundance of Cronbach’s alpha values at .70","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada; Deutsche Forschungsgemeinschaft; SHRM Foundation; University of Bern; Virginia Commonwealth University; National Science Foundation","keywords":"Cronbach's alpha; Rule of thumb; Reliability (semiconductor); Transparency (behavior); Psychology; Computer science; Econometrics; Clinical psychology; Psychometrics; Mathematics; Algorithm","score_opus":0.31215825820456417,"score_gpt":0.47327763584986177,"score_spread":0.1611193776452976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4319232666","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98482347,0.00013790763,0.0024525549,0.0004425164,0.0042086258,0.00030850398,0.00029444386,0.00023569228,0.00709629],"genre_scores_gemma":[0.9662409,0.00010519479,0.005684446,0.00013810603,0.00019910123,0.000024337429,0.000038306793,0.000062913314,0.027506685],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99393004,0.00023402894,0.0020048984,0.0017250652,0.0016712784,0.0004346721],"domain_scores_gemma":[0.99335986,0.001420017,0.0010970763,0.0033335364,0.00053436786,0.00025516094],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.004737457,0.0004344464,0.0011805623,0.0005640335,0.0001883247,0.0005855478,0.0033855585,0.00049556064,0.00254387],"category_scores_gemma":[0.0010785515,0.0003210434,0.000577102,0.00038493727,0.0003138729,0.00029453757,0.002524433,0.00047078877,0.0032761607],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022495203,0.000622696,0.025809892,0.000051775904,0.000097681674,0.000070967,0.0019074947,0.025301412,0.002820667,0.0012183125,0.15566784,0.7862063],"study_design_scores_gemma":[0.00057305006,0.000312312,0.039013103,0.00028832466,0.000102712664,0.00001673384,0.0011043174,0.023326147,0.004892803,0.90482485,0.02423209,0.0013135433],"about_ca_topic_score_codex":0.0005762732,"about_ca_topic_score_gemma":0.0007623366,"teacher_disagreement_score":0.90360653,"about_ca_system_score_codex":0.00017747868,"about_ca_system_score_gemma":0.00024152992,"threshold_uncertainty_score":0.9999242},"labels":[],"label_agreement":null},{"id":"W4320084643","doi":"10.1007/978-3-030-90913-0_157","title":"Decision-Making","year":2022,"lang":"en","type":"book-chapter","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Rational planning model; Management science; Process (computing); Decision-making; Affect (linguistics); Decision field theory; Rational analysis; Rational choice theory (criminology); Rationality; Decision maker; Computer science; Psychology; Business decision mapping; Epistemology; Decision engineering; Engineering; Economics; Artificial intelligence; Decision support system; Management; Operations management; Cognition","score_opus":0.14628789702286696,"score_gpt":0.40258602998072274,"score_spread":0.25629813295785575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4320084643","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011051268,0.00025806352,0.001371648,0.00020769387,0.003943559,0.00023971673,0.00013682828,0.00015585533,0.9925815],"genre_scores_gemma":[0.02634359,0.00008645209,0.008466975,0.0010674673,0.00032514878,0.00001175,0.000010549107,0.00012925877,0.9635588],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9929958,0.00004548801,0.0019175768,0.0015973878,0.0030437396,0.00040003116],"domain_scores_gemma":[0.9883092,0.007841534,0.00093615486,0.002394849,0.00032095856,0.0001972768],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.003142388,0.00055128196,0.0010291071,0.0011626135,0.0004917227,0.0007872236,0.002926141,0.0004240287,0.32275736],"category_scores_gemma":[0.0024118836,0.00042812357,0.0008267255,0.00018121045,0.00013887502,0.00036563788,0.0017505895,0.0008901398,0.01749498],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030071102,0.000014519758,0.000016194583,5.3241655e-7,0.000011887829,0.00011269851,0.00002505791,0.00009682127,4.2543186e-7,0.084580995,0.11823154,0.79687923],"study_design_scores_gemma":[0.00006339673,0.000041672956,0.000010031482,0.000036370187,0.000016872342,0.000035564768,0.000027379077,0.00007588851,2.73591e-7,0.48783517,0.5115622,0.00029513135],"about_ca_topic_score_codex":0.000008412373,"about_ca_topic_score_gemma":0.00006956884,"teacher_disagreement_score":0.7965841,"about_ca_system_score_codex":0.0003035248,"about_ca_system_score_gemma":0.00025082973,"threshold_uncertainty_score":0.9998171},"labels":[],"label_agreement":null},{"id":"W4320726359","doi":"10.1093/jcr/ucac055","title":"Beyond Numbers: An Ambiguity–Accessibility–Applicability Framework to Explain the Attraction Effect","year":2023,"lang":"en","type":"article","venue":"Journal of Consumer Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Ambiguity; Attraction; CLARITY; Perception; Set (abstract data type); Cognitive psychology; Conceptual framework; Psychology; Phenomenon; Process (computing); Social psychology; Computer science; Epistemology; Linguistics","score_opus":0.4113208688973397,"score_gpt":0.6004679743157054,"score_spread":0.1891471054183657,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4320726359","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99228245,0.000075355834,0.0007749995,0.0045510842,0.00094079523,0.00046770612,0.000012502027,0.00002866827,0.0008664203],"genre_scores_gemma":[0.9984766,0.000028873355,0.0007032852,0.00015296167,0.0002750845,0.000026219814,9.168903e-7,0.00001970557,0.00031633693],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9909273,0.002768577,0.0014269367,0.0006031158,0.0036686077,0.00060550624],"domain_scores_gemma":[0.973793,0.021753494,0.0004592119,0.0016470228,0.0017959136,0.00055135676],"candidate_categories":["metaresearch","scholarly_communication","insufficient_payload"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.0705363,0.00017657886,0.0005398865,0.0009214244,0.0006671736,0.0014258508,0.0025628782,0.00020056857,0.00068975094],"category_scores_gemma":[0.027347492,0.00009990454,0.00029957807,0.0032596518,0.00039696236,0.0008996706,0.00048697277,0.0017084284,0.0025200332],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006204887,0.00020460198,0.07095216,0.000006247532,0.000023901606,0.000064467786,0.00080119644,0.00016092228,0.0010302227,0.00020131594,0.032690812,0.8932437],"study_design_scores_gemma":[0.0007352234,0.0015816987,0.22490436,0.00014030402,0.000039777424,0.0001429351,0.0039328006,0.0006271566,0.0022030906,0.64283687,0.12250066,0.00035512671],"about_ca_topic_score_codex":0.00008594139,"about_ca_topic_score_gemma":0.00014497129,"teacher_disagreement_score":0.89288855,"about_ca_system_score_codex":0.0002238818,"about_ca_system_score_gemma":0.00031746615,"threshold_uncertainty_score":0.9996108},"labels":[],"label_agreement":null},{"id":"W4321103083","doi":"10.31234/osf.io/2b4jv","title":"Can the Prosocial Benefits of Episodic Simulation Transfer to Different People and Situational Contexts?","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"University of Auckland; Strong; Pennington Biomedical Research Foundation","keywords":"Prosocial behavior; Situational ethics; Context (archaeology); Psychology; Social psychology; Transferability; Cognitive psychology; Computer science; Geography; Machine learning","score_opus":0.18888571384297995,"score_gpt":0.40295194146741203,"score_spread":0.2140662276244321,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4321103083","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.988264,0.000027953147,0.0045500784,0.0050387452,0.00079203636,0.00070592837,0.0004225776,0.000036593032,0.0001620617],"genre_scores_gemma":[0.9987528,0.000011774613,0.00009291552,0.00015968012,0.0001225219,0.000048726175,0.00002933195,0.000018068122,0.00076419755],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99708074,0.000121179764,0.00092942524,0.0006610613,0.0010260136,0.0001815834],"domain_scores_gemma":[0.9959741,0.0028303156,0.00013453649,0.0005434012,0.00041038374,0.000107245076],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014051015,0.00022053054,0.00053902454,0.00025385094,0.00017314617,0.00034451496,0.00065211486,0.00020464473,0.00021654554],"category_scores_gemma":[0.0010753582,0.00012946948,0.00019111997,0.00025471652,0.00007702749,0.000061526356,0.0005281194,0.00023965906,0.00007136912],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012339464,0.00014704758,0.034701087,0.000016925884,0.00004138722,8.4545985e-7,0.0076417266,0.2654969,0.0000744645,0.0052687693,0.001843824,0.6846436],"study_design_scores_gemma":[0.00040047083,0.00010255181,0.71874905,0.00008738938,0.00006103707,9.367662e-7,0.00077454967,0.023407528,0.00017553163,0.25562033,0.0002755433,0.00034510845],"about_ca_topic_score_codex":0.00033816698,"about_ca_topic_score_gemma":0.010024157,"teacher_disagreement_score":0.6842985,"about_ca_system_score_codex":0.000056529792,"about_ca_system_score_gemma":0.000119005366,"threshold_uncertainty_score":0.5593715},"labels":[],"label_agreement":null},{"id":"W4322487098","doi":"10.1097/ede.0000000000001591","title":"Mindel C. Sheps: Counted, Dead or Alive","year":2023,"lang":"en","type":"article","venue":"Epidemiology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Generalizability theory; Psychology; Measure (data warehouse); Computer science; Developmental psychology; Data mining","score_opus":0.6506561001732234,"score_gpt":0.5616319595836654,"score_spread":0.08902414058955799,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4322487098","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98307467,0.00011750733,0.0031453632,0.0068744775,0.0024238238,0.00014871896,0.0000607564,0.00019662747,0.0039580604],"genre_scores_gemma":[0.9705517,0.000119134456,0.0039472035,0.0066393525,0.00042046592,0.000038024005,0.00002856761,0.00003112099,0.01822443],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99581426,0.0009760127,0.0014087161,0.00085291656,0.000318585,0.00062952854],"domain_scores_gemma":[0.96586293,0.032389704,0.00042782474,0.00092620595,0.00019662405,0.00019671644],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.015531209,0.00019722444,0.0008176164,0.0004340047,0.00022181767,0.00005377977,0.0010914895,0.00022772046,0.00264908],"category_scores_gemma":[0.056824844,0.00012402084,0.00021660411,0.00094073,0.00024685496,0.00018193806,0.00031419966,0.00030712772,0.027376067],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009345612,0.000030233734,0.05116449,0.0000011214112,0.000013057616,0.00009298963,0.00020920068,0.0008413259,0.00003001163,0.0014449162,0.57720035,0.36887887],"study_design_scores_gemma":[0.00036457236,0.00015823459,0.03534511,0.000016986374,0.000014834488,0.00008279761,0.0009881756,0.012547205,0.000020393485,0.43528265,0.5148925,0.00028651548],"about_ca_topic_score_codex":0.00015360986,"about_ca_topic_score_gemma":0.00030707612,"teacher_disagreement_score":0.43383774,"about_ca_system_score_codex":0.00006369999,"about_ca_system_score_gemma":0.00012341846,"threshold_uncertainty_score":0.99826264},"labels":[],"label_agreement":null},{"id":"W4323267236","doi":"10.1016/j.cortex.2023.02.005","title":"Stabilizing expectations when shifting from analytical to intuitive reasoning: The role of prediction errors in reasoning","year":2023,"lang":"en","type":"article","venue":"Cortex","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Psychology; Cognitive psychology; Cognitive science","score_opus":0.08232481763744136,"score_gpt":0.37784651131974223,"score_spread":0.29552169368230086,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323267236","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9959079,0.000045884488,0.00065364514,0.00027192224,0.00026754406,0.00016609464,0.00006769207,0.000060606948,0.0025587147],"genre_scores_gemma":[0.9983526,0.0000024280876,0.0014136271,0.000033789365,0.00006251008,0.000020589972,0.000013846666,0.000013352108,0.00008724646],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99773616,0.00015324904,0.00077000755,0.0005053279,0.00058784685,0.00024738305],"domain_scores_gemma":[0.99662185,0.0023609244,0.00022700125,0.00051474775,0.0001772206,0.00009824274],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001720644,0.000114256836,0.00027659404,0.00027769397,0.0001625657,0.00016101295,0.000539604,0.00007306409,0.00017950147],"category_scores_gemma":[0.0073596034,0.00008395386,0.00009975168,0.0013838005,0.000078937344,0.00025017874,0.00024248453,0.00019508647,0.0002681678],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007436338,0.000070830945,0.43730378,8.073759e-7,0.00001752947,0.000014902725,0.03699302,0.0025187542,0.0014998092,0.002134949,0.0013292778,0.51804197],"study_design_scores_gemma":[0.0002126484,0.000083659936,0.61465394,0.00015344347,0.000024575455,0.0000019703325,0.1188618,0.16498585,0.00032542506,0.099218026,0.0013132448,0.00016539259],"about_ca_topic_score_codex":0.00033482155,"about_ca_topic_score_gemma":0.00048298523,"teacher_disagreement_score":0.51787657,"about_ca_system_score_codex":0.000099956815,"about_ca_system_score_gemma":0.00008555041,"threshold_uncertainty_score":0.88106644},"labels":[],"label_agreement":null},{"id":"W4323521535","doi":"10.7202/1097014ar","title":"AFFECTIVE STATES, HAPPINESS, AND WELL-BEING","year":2023,"lang":"fr","type":"article","venue":"Les ateliers de l éthique","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Happiness; Psychology; Social psychology; Political science","score_opus":0.04490411582684148,"score_gpt":0.34883248711962395,"score_spread":0.3039283712927825,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323521535","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9672262,0.0024737427,0.002574293,0.008274854,0.0024504948,0.00031125225,0.00005065332,0.00021498237,0.016423503],"genre_scores_gemma":[0.9747644,0.0062414445,0.002186184,0.0016194922,0.00032107817,0.00002903391,0.000024433655,0.00007275375,0.014741201],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9965692,0.00048079804,0.0007015313,0.0009258424,0.00047436066,0.0008482246],"domain_scores_gemma":[0.9961716,0.0024014506,0.00025941775,0.00056665996,0.00023361466,0.0003672437],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0036820883,0.00037268986,0.0005533206,0.00046159097,0.00049418974,0.0008144245,0.0006142694,0.00062231737,0.0005730494],"category_scores_gemma":[0.0012498681,0.00035014283,0.00018802434,0.0011779265,0.00056810444,0.0005194525,0.00045353884,0.00075228093,0.0030093193],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000061649385,0.00006295053,0.009859367,0.000043330965,0.000039776838,0.0004991129,0.0048029954,0.0025149328,0.00020247872,0.011190604,0.021281442,0.9494414],"study_design_scores_gemma":[0.0005338608,0.00017644664,0.0071012015,0.00034662115,0.000059745307,0.00015242971,0.006004356,0.029387582,0.0005674132,0.7201352,0.23492071,0.00061444443],"about_ca_topic_score_codex":0.0013959989,"about_ca_topic_score_gemma":0.00046562677,"teacher_disagreement_score":0.9488269,"about_ca_system_score_codex":0.00028823855,"about_ca_system_score_gemma":0.00019798655,"threshold_uncertainty_score":0.99989504},"labels":[],"label_agreement":null},{"id":"W4323793439","doi":"10.2139/ssrn.4380365","title":"A Manager and an AI Walk into a Bar: Does ChatGPT Make Biased Decisions Like We Do?","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":76,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Queen's University; Western University","funders":"","keywords":"Salience (neuroscience); Heuristics; Regret; Computer science; Probabilistic logic; Optimism bias; Overconfidence effect; Cognitive psychology; Cognitive bias; Decision aids; Weighting; Artificial intelligence; Optimism; Psychology; Data science; Machine learning; Social psychology; Cognition","score_opus":0.054837994182220344,"score_gpt":0.38383335592718854,"score_spread":0.3289953617449682,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323793439","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9885218,0.0010456942,0.0026179329,0.006129375,0.0010592267,0.00016907393,0.000012737943,0.000117630705,0.00032649838],"genre_scores_gemma":[0.989152,0.0056124576,0.00042128557,0.00050825934,0.00034353638,0.000010608661,0.000004525658,0.000047669553,0.00389964],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9943998,0.0002883569,0.0010432054,0.0008599147,0.001222071,0.002186649],"domain_scores_gemma":[0.99686694,0.001181509,0.0003594772,0.0008895446,0.0002712238,0.00043129188],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00977611,0.00032387208,0.00052005035,0.0012160992,0.00082071597,0.0015362467,0.0013599324,0.00019531666,0.000312262],"category_scores_gemma":[0.0012865731,0.00020476175,0.00027058355,0.0012992753,0.0001506646,0.00081431906,0.0002902,0.00166688,0.0010446397],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008459875,0.000073732124,0.0018634677,8.8190376e-7,0.00003438186,0.0000670018,0.0006414185,0.00007156292,0.0001689142,0.0054383627,0.002075463,0.9894802],"study_design_scores_gemma":[0.00068540726,0.00035333898,0.0016969938,0.000048218022,0.000036446378,0.0003666692,0.0070318035,0.0015644869,0.000019771369,0.93539554,0.052479222,0.00032207824],"about_ca_topic_score_codex":0.0000664439,"about_ca_topic_score_gemma":0.003078634,"teacher_disagreement_score":0.98915815,"about_ca_system_score_codex":0.00039619664,"about_ca_system_score_gemma":0.0010406242,"threshold_uncertainty_score":0.99973315},"labels":[],"label_agreement":null},{"id":"W4324141783","doi":"10.1002/bdm.2322","title":"Demand for information about potential wins and losses: Does it matter if information matters?","year":2023,"lang":"en","type":"article","venue":"Journal of Behavioral Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Outcome (game theory); Psychology; Action (physics); Chose; Instrumental variable; Social psychology; Economics; Microeconomics; Econometrics","score_opus":0.05207263000074558,"score_gpt":0.3937826926659199,"score_spread":0.34171006266517434,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4324141783","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92578113,0.000019048983,0.069713935,0.0015124799,0.0024358442,0.00031899457,0.00010694718,0.000031139065,0.00008047313],"genre_scores_gemma":[0.98360515,0.000042164727,0.01429478,0.0017419453,0.00018782966,0.000009880241,0.000011823578,0.000019182855,0.00008723398],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9946274,0.000085791464,0.0029445866,0.00025714672,0.0016703594,0.00041467947],"domain_scores_gemma":[0.994753,0.0012316181,0.0021375923,0.00044646685,0.0012305361,0.00020078551],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004512706,0.00028298658,0.0006279767,0.0019941295,0.00039777614,0.0026094443,0.00084782933,0.00029587312,0.00041912496],"category_scores_gemma":[0.00084534806,0.00018707772,0.00039358585,0.00076797034,0.000100262354,0.008098995,0.00032496592,0.00039356656,0.00088422716],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045546924,0.00004845578,0.008082543,0.000013509356,0.00001155759,0.000025766105,0.001728381,0.0031493648,0.00010212897,0.000029509016,0.070435375,0.91591793],"study_design_scores_gemma":[0.0075565493,0.0015362509,0.40258262,0.0018970583,0.0005607246,0.001570521,0.026609238,0.02402565,0.00024282256,0.18160698,0.35002902,0.0017825525],"about_ca_topic_score_codex":0.000008602563,"about_ca_topic_score_gemma":0.000011652777,"teacher_disagreement_score":0.9141354,"about_ca_system_score_codex":0.000109857225,"about_ca_system_score_gemma":0.00010051801,"threshold_uncertainty_score":0.9998937},"labels":[],"label_agreement":null},{"id":"W4328114234","doi":"10.31234/osf.io/c9jq6","title":"Scarcity Captures Attention and Induces Neglect: Eyetracking and Behavoral Evidence","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Canada Research Chairs; Alfred P. Sloan Foundation; National Science Foundation","keywords":"Scarcity; Neglect; Economics; Psychology; Microeconomics; Psychiatry","score_opus":0.457928043024434,"score_gpt":0.4728088798442774,"score_spread":0.014880836819843368,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4328114234","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.994787,0.0010006722,0.0006187073,0.0011182924,0.0016970251,0.00029691609,0.000033702596,0.00015305265,0.00029466153],"genre_scores_gemma":[0.9963879,0.0003945991,0.001659476,0.0001181138,0.00015974804,0.000018960063,0.0000072305124,0.000027625305,0.0012263637],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9959468,0.00020019188,0.0009691688,0.0015481369,0.0010006727,0.00033501297],"domain_scores_gemma":[0.9960431,0.0020706777,0.00052016374,0.00084435573,0.0003139084,0.00020781273],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0031991105,0.0003560589,0.00064125034,0.0006179929,0.00029349167,0.0025557415,0.00084776833,0.00049590704,0.00013495621],"category_scores_gemma":[0.0030827494,0.00027270828,0.00016920068,0.00034429558,0.00026884425,0.0006174635,0.0026378748,0.0007476115,0.00014608346],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033789223,0.00004478008,0.19200738,0.000032872715,0.000020902837,0.000042834577,0.00056498265,0.00017233138,0.0008459384,0.00015937348,0.004557972,0.80151683],"study_design_scores_gemma":[0.00016380327,0.00007527589,0.7673541,0.00067029014,0.000084321706,0.000034398934,0.0009400099,0.00218444,0.00015640949,0.22743015,0.00031058784,0.0005962131],"about_ca_topic_score_codex":0.0015302472,"about_ca_topic_score_gemma":0.0011536063,"teacher_disagreement_score":0.80092067,"about_ca_system_score_codex":0.00006404221,"about_ca_system_score_gemma":0.000117627074,"threshold_uncertainty_score":0.9999725},"labels":[],"label_agreement":null},{"id":"W4352976756","doi":"10.1007/978-3-031-28719-0_24","title":"Value Cores for Inner and Outer Alignment: Simulating Personality Formation via Iterated Policy Selection and Preference Learning with Self-World Modeling Active Inference Agents","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Iterated function; Selection (genetic algorithm); Inference; Preference; Value (mathematics); Artificial intelligence; Computer science; Personality; Machine learning; Psychology; Mathematics; Statistics; Social psychology","score_opus":0.24261878147536317,"score_gpt":0.41469309620417333,"score_spread":0.17207431472881016,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4352976756","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.28925523,0.000062851366,0.69335324,0.0008478591,0.00022887337,0.0016726177,0.00010206459,0.00023437855,0.014242872],"genre_scores_gemma":[0.97682816,0.0002903705,0.022166887,0.00019971372,0.000027638189,0.000033511096,0.0000650068,0.000011984341,0.0003767174],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977628,0.00007376463,0.00093466224,0.00040813768,0.0005876723,0.00023293494],"domain_scores_gemma":[0.9966346,0.0011715806,0.00065769523,0.0005470189,0.00088170776,0.000107410255],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.002165758,0.0002452346,0.0003231417,0.0015471869,0.001000849,0.0013919112,0.0007282541,0.00011654087,0.0000043090936],"category_scores_gemma":[0.00039814928,0.00020447987,0.000032451353,0.0007113084,0.00032856874,0.006294458,0.00090677175,0.00038053727,0.000009797568],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000054314554,0.000023739165,0.0013625663,0.000046680678,0.000016210106,2.0782694e-7,0.014088472,0.09711016,0.000006673912,0.03330194,0.000024319672,0.8539647],"study_design_scores_gemma":[0.00033946856,0.00008980078,0.0014083992,0.00021819066,0.000013969248,0.000010216715,0.00017817657,0.96611845,0.0000045894926,0.028994836,0.002386372,0.0002375327],"about_ca_topic_score_codex":0.00006730992,"about_ca_topic_score_gemma":0.00011840065,"teacher_disagreement_score":0.8690083,"about_ca_system_score_codex":0.00020391037,"about_ca_system_score_gemma":0.00019265515,"threshold_uncertainty_score":0.99964476},"labels":[],"label_agreement":null},{"id":"W4353094034","doi":"10.1016/j.qref.2023.03.006","title":"Satiation, habit formation, and other temporal anomalies: Extending the choice theory to multiple neighborhoods of time","year":2023,"lang":"en","type":"article","venue":"The Quarterly Review of Economics and Finance","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Roads University","funders":"Royal Roads University","keywords":"Habit; Consumption (sociology); Economics; Preference; Time preference; Set (abstract data type); Revealed preference; Taste; Choice set; Certainty; Mathematical economics; Microeconomics; Econometrics; Welfare economics; Psychology; Mathematics; Computer science; Social psychology","score_opus":0.06348378303080629,"score_gpt":0.3409173135543807,"score_spread":0.27743353052357445,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4353094034","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9911369,0.005750129,0.00051156356,0.001729616,0.00011048591,0.00040597748,0.0000742244,0.000008536352,0.0002725614],"genre_scores_gemma":[0.9876429,0.010641064,0.0004591988,0.00087759347,0.000043725136,0.000028509801,0.000003437248,0.000013274588,0.00029028533],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984702,0.00013114078,0.0009277217,0.00024318612,0.0000907753,0.00013696693],"domain_scores_gemma":[0.996881,0.0017566215,0.0006681329,0.0005707557,0.00009487907,0.00002858646],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0043723295,0.000120719094,0.00041023723,0.000088972,0.00015513891,0.00009172355,0.00048478873,0.000033932796,0.0000336151],"category_scores_gemma":[0.00036896887,0.00006811198,0.00008745048,0.00029160903,0.00014142382,0.00027314096,0.00007071808,0.000057135578,0.00009525544],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019385407,0.000015251429,0.0036761581,0.00008060469,0.000009902053,1.6694278e-7,0.001571922,0.00015791293,0.00002233488,0.011979916,0.0019862093,0.98048025],"study_design_scores_gemma":[0.00072846527,0.00069624756,0.06116147,0.0019824815,0.00008039816,0.000029741537,0.0017001597,0.049213193,0.00007259315,0.3544451,0.52935004,0.0005401098],"about_ca_topic_score_codex":0.000028487731,"about_ca_topic_score_gemma":0.00003864964,"teacher_disagreement_score":0.9799401,"about_ca_system_score_codex":0.000011905564,"about_ca_system_score_gemma":0.000026196545,"threshold_uncertainty_score":0.27775258},"labels":[],"label_agreement":null},{"id":"W4362470251","doi":"10.1371/journal.pone.0282876","title":"The reference dependence roots of inaction inertia: A query theory account","year":2023,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Mount Royal University; University of Calgary","funders":"","keywords":"Inertia; Loss aversion; Work (physics); Point (geometry); Economics; Focus (optics); Discounting; Econometrics; Positive economics; Microeconomics; Mathematics; Physics","score_opus":0.29994342934063767,"score_gpt":0.38210448504601985,"score_spread":0.08216105570538218,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362470251","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9956659,0.00007924306,0.00010966542,0.00043122337,0.00018531716,0.000115572366,0.000012965698,0.00006648436,0.0033335963],"genre_scores_gemma":[0.9976607,0.00014186873,0.00019128625,0.000055213906,0.00004593394,0.000019013209,0.0000020462398,0.0000095903,0.0018743337],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99760723,0.00016642695,0.0005865223,0.00034384136,0.0010791057,0.00021686255],"domain_scores_gemma":[0.9953135,0.0031764153,0.00031175264,0.00077888975,0.00036246577,0.00005694392],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0040045897,0.000101097765,0.00024869313,0.00019539852,0.00021601761,0.00019294994,0.0008901784,0.00008746081,0.0001528166],"category_scores_gemma":[0.0045638746,0.00006113331,0.00006425401,0.0007815752,0.000120562036,0.00032697277,0.0002457902,0.00019607875,0.0015409174],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039819826,0.00088441913,0.023681205,0.000014836001,0.000090978574,0.000023289254,0.00039632389,0.00014418314,0.053335827,0.012662668,0.0045696297,0.90379846],"study_design_scores_gemma":[0.00043465436,0.0002856531,0.14512064,0.0002958826,0.00010881402,0.000007858613,0.00462708,0.0047406955,0.02526859,0.8143885,0.0042932634,0.00042837218],"about_ca_topic_score_codex":0.00006664441,"about_ca_topic_score_gemma":0.00024636774,"teacher_disagreement_score":0.9033701,"about_ca_system_score_codex":0.000070289294,"about_ca_system_score_gemma":0.000084373896,"threshold_uncertainty_score":0.9992365},"labels":[],"label_agreement":null},{"id":"W4362563190","doi":"10.2139/ssrn.4406177","title":"Who Will Like Me? Individual Differences in the Sources of Meta-Liking Judgments at Zero-Acquaintance","year":2023,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Zero (linguistics); Psychology; Meta-analysis; Social psychology; Philosophy; Linguistics; Medicine","score_opus":0.2184026690568351,"score_gpt":0.3777045001599617,"score_spread":0.1593018311031266,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362563190","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99042326,0.0049218284,0.0015038681,0.0011819339,0.0013751965,0.00030870672,0.000075151416,0.000028470331,0.00018159444],"genre_scores_gemma":[0.99407315,0.003296084,0.00012985065,0.00017463593,0.00019739856,0.00003318437,0.000007798039,0.000045106084,0.002042789],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9905301,0.0010128482,0.0022848693,0.0010249803,0.0029520688,0.0021951748],"domain_scores_gemma":[0.9936462,0.0023527977,0.0024724687,0.0011609447,0.0002528028,0.00011480642],"candidate_categories":["metaepi_narrow","open_science","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.023332639,0.0005617576,0.0016243649,0.0009221591,0.00042911593,0.0009427537,0.005542181,0.00039349927,0.00017826867],"category_scores_gemma":[0.0011088473,0.00032596497,0.0010017153,0.00078728364,0.00026018597,0.00038336794,0.0018202782,0.004522235,0.00009549541],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006073236,0.0009904748,0.38978523,0.000056494326,0.006210561,0.00021164988,0.019586252,0.009333069,0.000110488465,0.015405105,0.0072753807,0.550428],"study_design_scores_gemma":[0.00038671176,0.00022518834,0.013539918,0.00015512126,0.0005695029,0.00018914543,0.0055742497,0.0002484907,0.000028376513,0.97739077,0.0012777224,0.00041482635],"about_ca_topic_score_codex":0.00024144573,"about_ca_topic_score_gemma":0.004315267,"teacher_disagreement_score":0.96198565,"about_ca_system_score_codex":0.0008317373,"about_ca_system_score_gemma":0.0015754986,"threshold_uncertainty_score":0.99991924},"labels":[],"label_agreement":null},{"id":"W4362730598","doi":"10.3819/ccbr.2023.180002","title":"Theoretical Mechanisms of Paradoxical Choices Involving Information","year":2023,"lang":"en","type":"article","venue":"Comparative Cognition & Behavior Reviews","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Comparative cognition; Psychology; Animal behavior; Cognitive science; Cognitive psychology; Neuroscience; Cognition; Biology; Zoology","score_opus":0.3607511729184733,"score_gpt":0.47583913722168936,"score_spread":0.11508796430321605,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362730598","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9783381,0.0004884546,0.012628485,0.00018969904,0.0008568187,0.0014470576,0.0001547246,0.00015522589,0.0057413895],"genre_scores_gemma":[0.9976541,0.00029130347,0.0013711046,0.00019814564,0.00005080762,0.00023302113,0.00012769073,0.000009044878,0.00006479594],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9959346,0.00050045544,0.0019951542,0.00040341294,0.00088211935,0.00028424343],"domain_scores_gemma":[0.99660826,0.0011316204,0.00091075856,0.0005389295,0.0006457456,0.00016469427],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0036280227,0.00025941545,0.0009419427,0.0005302312,0.00019565952,0.00028131274,0.0006532368,0.00012494097,0.0026139698],"category_scores_gemma":[0.0017884729,0.00018159168,0.00035922613,0.0013842015,0.00034517882,0.0011330144,0.0002030764,0.00023057322,0.0083364],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008723807,0.00037233878,0.0013496245,0.00003204497,0.000013948663,0.000010493815,0.0014397983,0.000025664245,0.0051555173,0.13448991,0.015766105,0.84125733],"study_design_scores_gemma":[0.0012110139,0.0005021778,0.02672005,0.000561362,0.0003312779,0.000032377513,0.0031888424,0.0042397967,0.009886587,0.84925807,0.1031762,0.00089226925],"about_ca_topic_score_codex":0.0000025312067,"about_ca_topic_score_gemma":0.0000044905028,"teacher_disagreement_score":0.84036505,"about_ca_system_score_codex":0.00003543925,"about_ca_system_score_gemma":0.00005064624,"threshold_uncertainty_score":0.99829775},"labels":[],"label_agreement":null},{"id":"W4362738479","doi":"10.1017/s1930297500004873","title":"Limited resources or limited luck? Why people perceive an illusory negative correlation between the outcomes of choice options despite unequivocal evidence for independence","year":2019,"lang":"en","type":"article","venue":"Judgment and Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Azrieli Foundation; Agence Nationale de la Recherche","keywords":"Luck; Independence (probability theory); Psychology; Correlation; Negative correlation; Social psychology; Medicine; Statistics; Mathematics; Epistemology; Philosophy","score_opus":0.20895790583398827,"score_gpt":0.42773231928231853,"score_spread":0.21877441344833026,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362738479","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9616336,0.00015881448,0.035980064,0.00044690352,0.000570881,0.0010047976,0.00006535654,0.000045270084,0.00009431743],"genre_scores_gemma":[0.98766977,0.000047143018,0.011392272,0.00044424032,0.00010220328,0.00003895461,0.000006590681,0.00002765596,0.0002711964],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9951628,0.00030459548,0.0014710582,0.000985243,0.001684564,0.0003917356],"domain_scores_gemma":[0.9564748,0.040572107,0.0009958711,0.0010699488,0.0007310901,0.00015619291],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.004481262,0.00033568227,0.0007651658,0.00060527684,0.00058368297,0.000696343,0.0010255097,0.0002687366,0.00032314425],"category_scores_gemma":[0.010822426,0.00019616925,0.0002596566,0.001030835,0.00018588631,0.0014631053,0.00047177853,0.00034203223,0.0001074445],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009533206,0.00010734356,0.53844285,0.000008632554,0.00004190308,0.0000022664344,0.003732665,0.005098417,0.00016511306,0.00017177996,0.000691774,0.4505839],"study_design_scores_gemma":[0.0011430535,0.0007408447,0.90598834,0.00044039983,0.00013170321,0.000008528047,0.004820382,0.050231233,0.00003231448,0.0346463,0.0014260064,0.00039089168],"about_ca_topic_score_codex":0.00009481152,"about_ca_topic_score_gemma":0.0005452336,"teacher_disagreement_score":0.45019302,"about_ca_system_score_codex":0.00010457182,"about_ca_system_score_gemma":0.00009880567,"threshold_uncertainty_score":0.99750984},"labels":[],"label_agreement":null},{"id":"W4365143226","doi":"10.1016/j.cognition.2023.105451","title":"The paradoxical effects of time pressure on base rate neglect","year":2023,"lang":"en","type":"article","venue":"Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Neglect; Psychology; Base (topology); Cognitive psychology; Social psychology; Developmental psychology; Mathematics; Psychiatry","score_opus":0.07666941855958741,"score_gpt":0.3720754682145374,"score_spread":0.29540604965495,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4365143226","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9952452,0.00004658004,0.00012506587,0.00046375536,0.00043886976,0.00019318105,0.000022768538,0.000060220977,0.0034043358],"genre_scores_gemma":[0.9979593,0.000028564244,0.000016462855,0.00012916456,0.000052291685,0.000016334674,0.000009896243,0.000007960044,0.0017800182],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986058,0.00024202235,0.0003236821,0.00026184885,0.00040847133,0.00015820858],"domain_scores_gemma":[0.99250126,0.006813781,0.00014572314,0.0003495885,0.00013478455,0.000054875676],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0014215686,0.000083735846,0.0001609855,0.00012649427,0.00018310329,0.00014371033,0.00030084534,0.00006487179,0.00013293819],"category_scores_gemma":[0.004338341,0.000049500046,0.000103578815,0.0004962588,0.000082505794,0.00009859749,0.00006300062,0.00009976693,0.005753212],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019992219,0.00009335618,0.00011013957,0.000006551467,0.000014738189,0.000028151744,0.000075060394,0.00028498078,0.011162355,0.00019703654,0.05276155,0.93506616],"study_design_scores_gemma":[0.0021378552,0.0013637347,0.04535529,0.00039505752,0.00022118031,0.000013221774,0.00020961683,0.037973944,0.135984,0.67269605,0.10308846,0.0005616091],"about_ca_topic_score_codex":0.000001018567,"about_ca_topic_score_gemma":0.0000018228326,"teacher_disagreement_score":0.93450457,"about_ca_system_score_codex":0.0000067112096,"about_ca_system_score_gemma":0.000024662586,"threshold_uncertainty_score":0.9950209},"labels":[],"label_agreement":null},{"id":"W4365519323","doi":"10.54254/2753-7048/3/2022450","title":"A Study of Weight Management Based on Intrinsic Incentives","year":2023,"lang":"en","type":"article","venue":"Lecture Notes in Education Psychology and Public Media","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Incentive; Honor; Intrinsic motivation; Control (management); Public economics; Business; Economics; Microeconomics; Psychology; Social psychology; Computer science; Management; Internet privacy","score_opus":0.097325633729937,"score_gpt":0.43440880664847487,"score_spread":0.33708317291853784,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4365519323","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9901673,0.00007774482,0.0005933823,0.004458938,0.002705662,0.0002559567,0.0000034858574,0.000024073037,0.0017134233],"genre_scores_gemma":[0.99808913,0.000050056446,0.00041690771,0.001280374,0.00007724216,0.00004733892,0.000012668845,0.0000067575306,0.000019521143],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99820215,0.00028035836,0.0004894952,0.00050195394,0.0003422169,0.00018382461],"domain_scores_gemma":[0.9970013,0.0020908804,0.00018164921,0.00054772553,0.000102208905,0.00007621732],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001591257,0.00011411539,0.00023017841,0.0014329412,0.0000636488,0.000064541884,0.00040449298,0.00011098404,0.00030711986],"category_scores_gemma":[0.0019736805,0.00008556491,0.00003238851,0.0017237697,0.00010163698,0.000100025405,0.000060352562,0.0001840841,0.00010746417],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000038216993,0.00089667505,0.13476704,0.000001849362,0.00000503544,0.0000048234438,0.0015959915,0.000045385324,0.0000024778105,0.00026132946,0.0016862176,0.86069494],"study_design_scores_gemma":[0.0009792919,0.00023253531,0.8437181,0.00002392972,0.000009781935,0.0000033394233,0.0021928991,0.00013222035,0.000010607784,0.14358875,0.0089756055,0.00013293087],"about_ca_topic_score_codex":0.000008096233,"about_ca_topic_score_gemma":0.00013134012,"teacher_disagreement_score":0.860562,"about_ca_system_score_codex":0.000019517614,"about_ca_system_score_gemma":0.000073808835,"threshold_uncertainty_score":0.3489236},"labels":[],"label_agreement":null},{"id":"W4366086793","doi":"10.3846/tede.2023.18551","title":"NONPARAMETRIC NUMERICAL APPROACHES TO PROBABILITY WEIGHTING FUNCTION CONSTRUCT FOR MANIFESTATION AND PREDICTION OF RISK PREFERENCES","year":2023,"lang":"en","type":"article","venue":"Technological and Economic Development of Economy","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Social Science Fund of China; National Natural Science Foundation of China; City University of Hong Kong","keywords":"Weighting; Nonparametric statistics; Construct (python library); Function (biology); Econometrics; Computer science; A-weighting; Mathematics; Statistics; Medicine; Biology","score_opus":0.30294977102701076,"score_gpt":0.31691030689014743,"score_spread":0.01396053586313667,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4366086793","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98597723,0.000016742768,0.012677364,0.000108317785,0.00011116216,0.00044171567,0.000063216714,0.000075838965,0.00052840775],"genre_scores_gemma":[0.9643932,0.000011955534,0.03546381,0.000005643089,0.0000111508,0.00008712248,0.00001159745,0.000004712106,0.000010815338],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99808854,0.0000308914,0.0010494973,0.00057387317,0.0000808164,0.00017637337],"domain_scores_gemma":[0.99807566,0.0011267659,0.00048489074,0.00019290675,0.000048713227,0.00007108067],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022575592,0.00013490541,0.00041446285,0.0005106157,0.00013749233,0.00007080502,0.00021744194,0.00014550761,0.000041259715],"category_scores_gemma":[0.0007962353,0.0001040001,0.00005015202,0.00030784722,0.00020046745,0.00021545574,0.00019792364,0.00008102886,0.000030302434],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000058524747,0.0000325682,0.12950782,0.0000138452815,0.000015021138,6.7598485e-8,0.00013390374,0.00018130789,0.000018692052,0.004143967,0.0000388619,0.8658554],"study_design_scores_gemma":[0.00040685124,0.000266057,0.3322885,0.000019190999,0.000020196074,0.0000038616986,0.0010526682,0.013435288,0.0007908022,0.64920247,0.0023299137,0.00018421195],"about_ca_topic_score_codex":0.000007693824,"about_ca_topic_score_gemma":0.000012664875,"teacher_disagreement_score":0.8656712,"about_ca_system_score_codex":0.000053175678,"about_ca_system_score_gemma":0.00006107715,"threshold_uncertainty_score":0.4241001},"labels":[],"label_agreement":null},{"id":"W4366115122","doi":"10.1561/105.00000169","title":"Rationality and Emotionality Interplay and Economic Contributions: A Neuroeconomics Experiment","year":2023,"lang":"en","type":"article","venue":"Review of Behavioral Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Neuroeconomics; Rationality; Emotionality; Psychology; Economics; Positive economics; Social psychology; Cognitive psychology; Epistemology; Philosophy","score_opus":0.12316385771438725,"score_gpt":0.473738574037869,"score_spread":0.35057471632348175,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4366115122","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9920269,0.0041069994,0.000052171563,0.0017950446,0.0005456223,0.0004642452,0.00076394016,0.000043977252,0.000201067],"genre_scores_gemma":[0.96191794,0.03652169,0.0005013887,0.0006676449,0.00008346093,0.000059182337,0.00010635074,0.000025044703,0.00011731557],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99665934,0.00017769984,0.0019417463,0.0007894678,0.00015603688,0.00027573988],"domain_scores_gemma":[0.9973668,0.00073004817,0.00081501045,0.0007036056,0.00016044837,0.00022410613],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0035162258,0.00026517207,0.0009501665,0.0002548716,0.00015718692,0.00021878345,0.00044721607,0.00011072098,0.00039913077],"category_scores_gemma":[0.00034156302,0.0002489453,0.00024072854,0.00016213616,0.0002998774,0.0005881343,0.0004463443,0.00015053069,0.0003086846],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000094353905,0.00032758748,0.051544152,0.00040241025,0.000059449907,0.00001010007,0.0003264121,0.00030308706,0.00019095742,0.03143624,0.015033293,0.90027195],"study_design_scores_gemma":[0.004752259,0.0010560089,0.27260944,0.0034908738,0.00060422765,0.00046578376,0.0020734367,0.021962726,0.0017181819,0.27893263,0.4091461,0.0031883565],"about_ca_topic_score_codex":0.00009168308,"about_ca_topic_score_gemma":0.000055683868,"teacher_disagreement_score":0.8970836,"about_ca_system_score_codex":0.00021632054,"about_ca_system_score_gemma":0.00019522737,"threshold_uncertainty_score":0.9999963},"labels":[],"label_agreement":null},{"id":"W4366489390","doi":"10.1002/jcpy.1354","title":"Mental accounting of product returns","year":2023,"lang":"en","type":"article","venue":"Journal of Consumer Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Mental accounting; Product (mathematics); Lottery; Purchasing; Economics; Revenue; Value (mathematics); Monetary economics; Business; Fungibility; Time value of money; Microeconomics; Marketing; Accounting; Finance","score_opus":0.2204257693242787,"score_gpt":0.5006127997533809,"score_spread":0.2801870304291022,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4366489390","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99180293,0.00033499207,0.000055302506,0.002290116,0.0038449373,0.000056795438,0.0000097901975,0.000011222549,0.001593886],"genre_scores_gemma":[0.99849796,0.00013814942,0.00068411743,0.0002459112,0.00015553237,6.027906e-7,6.399191e-7,0.000010265826,0.00026684086],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99731064,0.0001438638,0.0014528426,0.00025035403,0.00062882673,0.00021347245],"domain_scores_gemma":[0.9968887,0.0006855119,0.0013722166,0.0004513281,0.0005222459,0.00008002514],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0046891198,0.00010314284,0.00047089698,0.0007691582,0.000057233443,0.000065057444,0.00081611535,0.00007835785,0.0004425866],"category_scores_gemma":[0.0018726805,0.00007264791,0.00022003693,0.00077602157,0.00017086722,0.0002829794,0.000093139024,0.00025819146,0.00048738287],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017288835,0.0001183404,0.122153364,0.0000021467902,0.000044903703,0.000072031115,0.00057891896,0.000016757853,0.009617715,0.00004233916,0.1931283,0.6740523],"study_design_scores_gemma":[0.002666405,0.0006419327,0.3640683,0.000121464596,0.00009837862,0.0021100051,0.00198143,0.0001451448,0.002692057,0.09947154,0.5255918,0.00041153588],"about_ca_topic_score_codex":0.000002440156,"about_ca_topic_score_gemma":0.0000059049567,"teacher_disagreement_score":0.6736407,"about_ca_system_score_codex":0.000018069459,"about_ca_system_score_gemma":0.00008593585,"threshold_uncertainty_score":0.62644833},"labels":[],"label_agreement":null},{"id":"W4366963360","doi":"10.2139/ssrn.4427474","title":"Selten's Horse an Experiment on Sequential Rationality∗","year":2023,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Rationality; Horse; Computer science; Mathematical economics; Economics; Philosophy; Biology; Epistemology","score_opus":0.24655878919601093,"score_gpt":0.46377665526933753,"score_spread":0.2172178660733266,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4366963360","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9847463,0.0003068106,0.0069510834,0.0019903432,0.0050282613,0.0002817676,0.00005515871,0.00012170197,0.00051859376],"genre_scores_gemma":[0.99334925,0.00058312574,0.00048538827,0.0001780231,0.0014224906,0.000029869985,0.00005570044,0.000077290635,0.003818869],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99200773,0.000646835,0.0015901743,0.0012539787,0.0023380234,0.0021632751],"domain_scores_gemma":[0.9963131,0.0004718235,0.0010598451,0.0013408508,0.00049962103,0.00031479166],"candidate_categories":["metaepi_narrow","scholarly_communication","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.014843407,0.00047703666,0.0006986513,0.00076705863,0.0004999124,0.0016455346,0.0024018288,0.00044735114,0.0004226081],"category_scores_gemma":[0.0009236524,0.00037724845,0.00061536784,0.00032594544,0.00010362698,0.00039097734,0.000709842,0.0050061485,0.0018292223],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007545864,0.0013331608,0.0012849603,0.000006725234,0.00048798523,0.00020013236,0.0015488901,0.045083303,0.0009022029,0.10793466,0.010243393,0.83022],"study_design_scores_gemma":[0.000391848,0.00041330795,0.00022815619,0.000047389356,0.000041536972,0.00016399563,0.0021298223,0.0013723349,0.00017684087,0.9911869,0.003402902,0.0004449615],"about_ca_topic_score_codex":0.00012497997,"about_ca_topic_score_gemma":0.00080706633,"teacher_disagreement_score":0.88325226,"about_ca_system_score_codex":0.002418247,"about_ca_system_score_gemma":0.0060420106,"threshold_uncertainty_score":0.9998679},"labels":[],"label_agreement":null},{"id":"W4367554874","doi":"10.31234/osf.io/3f5nh","title":"When Half is At Least 50%: Effect of “Framing” and Probability Level on Frequency Estimates","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University; Defence Research and Development Canada","funders":"Government of Canada; Mercyhurst University","keywords":"Framing effect; Framing (construction); Psychology; Numeracy; Bounding overwatch; Statistics; Cognition; Inference; Social psychology; Econometrics; Mathematics; Computer science; Artificial intelligence; Persuasion; Geography","score_opus":0.27520398021952475,"score_gpt":0.42046077545699595,"score_spread":0.1452567952374712,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4367554874","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9925334,0.00010054502,0.00077386096,0.0009782806,0.001169439,0.0007456688,0.00041080834,0.0001378557,0.0031501767],"genre_scores_gemma":[0.9811262,0.000021034879,0.013487527,0.00008979794,0.000060879953,0.00005873424,0.000024795667,0.000048292255,0.00508277],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99497503,0.000235267,0.0014509534,0.0018051977,0.0011662424,0.00036728012],"domain_scores_gemma":[0.9909633,0.0057616876,0.0007446592,0.0020467837,0.0002913097,0.00019226255],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.005185486,0.0005211938,0.0012952946,0.00044462233,0.00016923196,0.00046286246,0.0013695813,0.00052843156,0.0012348639],"category_scores_gemma":[0.005481556,0.00034381624,0.0003936868,0.0002068155,0.00037256946,0.00015423121,0.002535338,0.0005264893,0.001248022],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000323128,0.00026177897,0.3055218,0.0003234153,0.00009101242,0.000029417943,0.0011629696,0.0008779225,0.00051342713,0.00061817083,0.028564036,0.66171294],"study_design_scores_gemma":[0.0004943363,0.0006514209,0.060868524,0.0005029764,0.0000972129,0.0000131869965,0.000067826266,0.002986528,0.004424752,0.9280993,0.001119065,0.0006748708],"about_ca_topic_score_codex":0.0013756225,"about_ca_topic_score_gemma":0.000503849,"teacher_disagreement_score":0.9274811,"about_ca_system_score_codex":0.00019383917,"about_ca_system_score_gemma":0.00013699305,"threshold_uncertainty_score":0.9999014},"labels":[],"label_agreement":null},{"id":"W4375934455","doi":"10.1017/s0140525x22002746","title":"The wisdom in the story: Clarifying assumptions about radical uncertainty and reasonableness in narrative judgment","year":2023,"lang":"en","type":"letter","venue":"Behavioral and Brain Sciences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Narrative; Irrational number; Epistemology; Psychology; Social psychology; Sociology; Philosophy; Mathematics; Linguistics","score_opus":0.2434699376193632,"score_gpt":0.43891038566082125,"score_spread":0.19544044804145805,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4375934455","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6460291,0.0005103358,0.0000057947127,0.35228384,0.0006539445,0.00036769474,0.0000499915,0.000019525545,0.000079748206],"genre_scores_gemma":[0.8494547,0.00085047126,0.0004339344,0.14256437,0.0012881599,0.00052763766,0.000063574815,0.0000642217,0.0047529317],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99369097,0.001476982,0.0009171538,0.0012880918,0.0018904235,0.0007363989],"domain_scores_gemma":[0.99085283,0.007955625,0.0004064749,0.00059482123,0.00009748221,0.00009278918],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":["sts"],"category_scores_codex":[0.016977454,0.0003832252,0.00059447717,0.0005622766,0.0019489316,0.0023882461,0.0020348034,0.000526587,0.00003589639],"category_scores_gemma":[0.0011117005,0.0001885877,0.00013193859,0.0016385483,0.0030333176,0.0004833664,0.00042669574,0.002056059,0.00003114216],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027846156,0.000096562144,0.02014383,0.0000070406977,0.0000043535088,0.00035031713,0.0078026005,0.00010915351,0.000012893835,0.00032344498,0.5692905,0.40183145],"study_design_scores_gemma":[0.0006031089,0.0003320743,0.08129202,0.00031593733,0.00003504576,0.00008397362,0.03881979,0.0010106037,0.000001443339,0.043048233,0.8337511,0.0007067131],"about_ca_topic_score_codex":0.0011729087,"about_ca_topic_score_gemma":0.006257816,"teacher_disagreement_score":0.40112475,"about_ca_system_score_codex":0.00013069715,"about_ca_system_score_gemma":0.00032244975,"threshold_uncertainty_score":0.99967986},"labels":[],"label_agreement":null},{"id":"W4375934458","doi":"10.1017/s0140525x22003223","title":"Narratives, probabilities, and the currency of thought","year":2023,"lang":"en","type":"article","venue":"Behavioral and Brain Sciences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Economic and Social Research Council","keywords":"Narrative; Currency; Centrality; Cognition; Positive economics; Epistemology; Psychology; Sociology; Economics; Philosophy; Monetary economics; Neuroscience; Mathematics; Linguistics","score_opus":0.23046363334700126,"score_gpt":0.4444988259929796,"score_spread":0.2140351926459783,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4375934458","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.992779,0.000366155,0.000016750222,0.005355919,0.00032252917,0.00021243413,0.00003503032,0.000032297183,0.00087988726],"genre_scores_gemma":[0.9978819,0.000049066137,0.00057522295,0.00009821757,0.000034592736,0.000017189132,0.0000014419636,0.0000038392564,0.0013385143],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99765414,0.0002299865,0.0005755309,0.0005298766,0.00075942295,0.00025101745],"domain_scores_gemma":[0.9975755,0.0017008221,0.00022879192,0.00029537993,0.000115563395,0.00008393045],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0064421287,0.00013513265,0.0003312266,0.00022802879,0.0005270128,0.00039956742,0.0006882468,0.000053874945,0.000085239226],"category_scores_gemma":[0.0007994046,0.00006520909,0.0000813137,0.0013535345,0.003420604,0.00044573785,0.0003390388,0.00010202626,0.000030143938],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000053525964,0.00008834818,0.056782227,0.000005603872,0.000002604113,0.000004855007,0.00914241,0.0000122214815,0.00036850947,0.029928591,0.0103429025,0.8932682],"study_design_scores_gemma":[0.0011864562,0.0005384547,0.06758139,0.000063892796,0.00002083004,0.000040328247,0.039131317,0.0008943147,0.00018130409,0.8561093,0.033872418,0.00037997524],"about_ca_topic_score_codex":0.00011629497,"about_ca_topic_score_gemma":0.00010084552,"teacher_disagreement_score":0.89288825,"about_ca_system_score_codex":0.0000068291906,"about_ca_system_score_gemma":0.00009053594,"threshold_uncertainty_score":0.99929154},"labels":[],"label_agreement":null},{"id":"W4378717534","doi":"10.3390/jcm12113740","title":"Clinical Assessment of Judgment in Adults and the Elderly: Development and Validation of the Three Domains of Judgment Test—Clinical Version (3DJT-CV)","year":2023,"lang":"en","type":"article","venue":"Journal of Clinical Medicine","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut national de psychiatrie légale Philippe-Pinel; Centre intégré de santé et de services sociaux de Chaudière-Appalaches; Centre Hospitalier de l’Université de Montréal; Centre intégré universitaire de santé et de services sociaux de l'Est-de-l'Île-de-Montréal; Institut Universitaire de Gériatrie de Montréal; Centre intégré universitaire de santé et de services sociaux de la Capitale-Nationale; Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Université de Montréal; Université Laval","funders":"","keywords":"Concurrent validity; Test (biology); Medicine; Relevance (law); Context (archaeology); Clinical judgment; Cognition; Applied psychology; Consistency (knowledge bases); Psychometrics; Internal consistency; Clinical psychology; Cognitive psychology; Medical physics; Artificial intelligence; Psychology; Computer science; Psychiatry","score_opus":0.2473022152251285,"score_gpt":0.5221287755712625,"score_spread":0.27482656034613395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4378717534","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9900735,0.0001481216,0.00026323088,0.0071494076,0.0018106197,0.0003206296,0.0000060282528,0.0000031348093,0.0002253358],"genre_scores_gemma":[0.9963237,0.0011946883,0.002001856,0.00019447402,0.00023751466,0.0000022520856,0.0000010276952,0.000008112369,0.000036350306],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9874637,0.0010595284,0.009010563,0.0003769031,0.001904526,0.00018476255],"domain_scores_gemma":[0.95660037,0.036806583,0.005122397,0.0006042635,0.00064919674,0.00021718939],"candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.056430083,0.00016504743,0.0017168197,0.00027236211,0.00007244449,0.000019987358,0.0007846864,0.00021658163,0.00006226214],"category_scores_gemma":[0.030552069,0.00007357182,0.00038672105,0.00059452275,0.0013636996,0.00012884593,0.0004464605,0.0007271171,0.0000036198664],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00070678664,0.00041146742,0.5949145,0.000014634368,0.00003923142,0.0000069854495,0.00019219791,0.00003801251,0.000013846535,0.00008249047,0.0012443574,0.40233546],"study_design_scores_gemma":[0.010665538,0.0029782555,0.9701774,0.0013298856,0.000120562596,0.000011092179,0.0010450653,0.0011704739,0.00006678159,0.010704274,0.001651,0.00007967934],"about_ca_topic_score_codex":0.000020449554,"about_ca_topic_score_gemma":0.00005315414,"teacher_disagreement_score":0.4022558,"about_ca_system_score_codex":0.00003536145,"about_ca_system_score_gemma":0.0004380632,"threshold_uncertainty_score":0.977614},"labels":[],"label_agreement":null},{"id":"W4380079881","doi":"10.31234/osf.io/ravsp","title":"Nudges for People who Think","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Response Biomedical (Canada)","funders":"Australian Research Council","keywords":"Nudge theory; Metaphor; Choice architecture; Cognition; Psychology; Agency (philosophy); Cognitive science; Psychological intervention; Cognitive psychology; Balance (ability); Social psychology; Sociology; Social science","score_opus":0.3343739601529925,"score_gpt":0.46697911083793725,"score_spread":0.13260515068494477,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4380079881","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90788275,0.00011423939,0.05084904,0.009562729,0.012840569,0.0013060125,0.00067610206,0.0007403005,0.016028257],"genre_scores_gemma":[0.7043661,0.00015610697,0.034455515,0.0015920934,0.0012165798,0.0003387978,0.00014925191,0.00019403655,0.25753155],"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9961106,0.00007015537,0.0011600392,0.0013632394,0.0009169863,0.00037897815],"domain_scores_gemma":[0.9929485,0.0040302463,0.0004902851,0.0018692908,0.0005057882,0.00015589395],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.004024064,0.00032095416,0.0009845213,0.0004829764,0.00019898827,0.0014740903,0.0024018262,0.00047742602,0.0010352711],"category_scores_gemma":[0.004254993,0.00022738105,0.0006426792,0.00033811288,0.0000546957,0.00016003421,0.0021107423,0.00039457803,0.004550971],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027533588,0.000049961993,0.0016844812,0.000013757874,0.000019517942,0.0000045218517,0.0008216279,0.001455479,0.0000048432985,0.0019922135,0.6308643,0.36306176],"study_design_scores_gemma":[0.00018190438,0.000047196685,0.0045189727,0.000052856703,0.000027812468,0.0000023607238,0.0010529152,0.009491787,0.00005221074,0.9171665,0.06701306,0.00039243608],"about_ca_topic_score_codex":0.00021553208,"about_ca_topic_score_gemma":0.00085297605,"teacher_disagreement_score":0.91517425,"about_ca_system_score_codex":0.00007381963,"about_ca_system_score_gemma":0.00023434922,"threshold_uncertainty_score":0.9998779},"labels":[],"label_agreement":null},{"id":"W4380371887","doi":"10.31234/osf.io/7ru58","title":"Pre-decisional information search adaptively reduces three types of uncertainty","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Banco Bilbao Vizcaya Argentaria; Max-Planck-Gesellschaft; Saskatoon City Hospital Foundation; Agencia Estatal de Investigación; Ministerio de Ciencia, Innovación y Universidades; Ministerio de Ciencia e Innovación; Fundación BBVA; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Computer science; Task (project management); Information seeking; Selection (genetic algorithm); Information needs; Data science; Information retrieval; Machine learning; World Wide Web; Economics","score_opus":0.31863190425034527,"score_gpt":0.44562220596521945,"score_spread":0.1269903017148742,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4380371887","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9773474,0.000050153496,0.0125203235,0.0006553293,0.0021834027,0.0004895241,0.00052024424,0.00013971407,0.006093957],"genre_scores_gemma":[0.990615,0.00004464448,0.006525454,0.00006374771,0.00013267314,0.000028624363,0.00008900326,0.000024261288,0.0024765637],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.993675,0.00015704278,0.0022162537,0.00079070864,0.0028061569,0.00035484202],"domain_scores_gemma":[0.9924719,0.0033458802,0.000958907,0.0013541378,0.0017001156,0.00016909529],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.006014292,0.00034545254,0.00084533734,0.0011695538,0.00013753121,0.000703768,0.002566387,0.0004926771,0.0014531277],"category_scores_gemma":[0.0039889477,0.00024231008,0.0004439274,0.0007436239,0.0002440772,0.0007416512,0.0029115917,0.0006731098,0.0030972832],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022393557,0.00006819871,0.0013064422,0.000011622637,0.000040903917,0.0000031949742,0.0005969772,0.17863686,0.000029287949,0.0013545635,0.018497502,0.7992305],"study_design_scores_gemma":[0.00044044678,0.00022560339,0.05390878,0.00033101634,0.00004773285,0.0000069804028,0.0017094659,0.11419564,0.0004820765,0.8180359,0.009924144,0.0006922256],"about_ca_topic_score_codex":0.00087524345,"about_ca_topic_score_gemma":0.00036197042,"teacher_disagreement_score":0.8166813,"about_ca_system_score_codex":0.00013556815,"about_ca_system_score_gemma":0.00085754495,"threshold_uncertainty_score":0.9994597},"labels":[],"label_agreement":null},{"id":"W4380997685","doi":"10.1080/13546783.2023.2220971","title":"Verbal and numeric probabilities differentially shape decisions","year":2023,"lang":"en","type":"article","venue":"Thinking & Reasoning","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Psychology; Vagueness; Cognitive psychology; Nonverbal communication; Outcome (game theory); Social psychology; Statistics; Mathematics; Artificial intelligence; Computer science; Developmental psychology; Mathematical economics","score_opus":0.11305609871285237,"score_gpt":0.3700312167534983,"score_spread":0.25697511804064593,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4380997685","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9942806,0.00012965457,0.0009998253,0.00033073415,0.00089595787,0.00015555337,0.000013581798,0.00038741028,0.0028067066],"genre_scores_gemma":[0.99310726,0.000051011477,0.0054301703,0.000114471986,0.00013053714,0.000014332008,0.000008822637,0.000032482585,0.0011108932],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9965992,0.00015628502,0.0007669811,0.00080559886,0.0011681027,0.00050384493],"domain_scores_gemma":[0.99515253,0.0034931593,0.00026609204,0.0007287431,0.0001708304,0.00018861999],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00327484,0.00024795125,0.00046143754,0.00044408688,0.00074580655,0.0012807748,0.00093889213,0.00013231084,0.00041166547],"category_scores_gemma":[0.0056728595,0.00019057194,0.00016703416,0.0010731702,0.00017416904,0.00047804313,0.00071918935,0.00028215762,0.00096797786],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003496433,0.00003551291,0.023281131,0.0000026956438,0.000014003416,0.00003835961,0.0038052069,0.00024712677,0.00015809914,0.0049598995,0.001929178,0.9654938],"study_design_scores_gemma":[0.00052784395,0.00013585703,0.10337524,0.00035032668,0.00004308372,0.00007632692,0.0034001598,0.033201754,0.000056480923,0.84871805,0.009557139,0.0005577335],"about_ca_topic_score_codex":0.000052551924,"about_ca_topic_score_gemma":0.00003150874,"teacher_disagreement_score":0.9649361,"about_ca_system_score_codex":0.000060558446,"about_ca_system_score_gemma":0.00008033392,"threshold_uncertainty_score":0.99980986},"labels":[],"label_agreement":null},{"id":"W4381616548","doi":"10.31234/osf.io/azp37","title":"Rare and extreme outcomes in risky choice","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Economic and Social Research Council","keywords":"Rare events; Outcome (game theory); Actuarial science; Psychology; Sample (material); Economics; Statistics","score_opus":0.43401020526417283,"score_gpt":0.4620397567998276,"score_spread":0.028029551535654784,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4381616548","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99132043,0.000096966614,0.00025515867,0.0017406754,0.0020054048,0.00025432327,0.000079496574,0.00013367843,0.0041138805],"genre_scores_gemma":[0.97094774,0.00008540568,0.0021537836,0.0002582943,0.00008357851,0.00003095971,0.000009892035,0.000034481247,0.026395865],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99638015,0.00012255732,0.0011783319,0.0012467563,0.000769878,0.00030229814],"domain_scores_gemma":[0.9946128,0.0034769513,0.00035049862,0.0012877681,0.00013121124,0.00014075202],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0026516619,0.0003057636,0.0008463686,0.00081053795,0.00007229518,0.0008885358,0.0012651557,0.00037968069,0.0007391406],"category_scores_gemma":[0.004538598,0.00021314454,0.00020449163,0.00035313587,0.000083362975,0.00018517903,0.0025922877,0.00059736735,0.0015804876],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006720747,0.00004508235,0.6999039,0.0000041946732,0.000006442022,0.000038441256,0.0001394944,0.0003139163,0.0000033195315,0.000082464496,0.009160841,0.29029515],"study_design_scores_gemma":[0.00032390005,0.000018113229,0.6918584,0.00007354853,0.000012785543,0.00000330143,0.0004014364,0.0019601649,0.00000722917,0.29206535,0.012868624,0.00040713148],"about_ca_topic_score_codex":0.0012731391,"about_ca_topic_score_gemma":0.0046941508,"teacher_disagreement_score":0.2919829,"about_ca_system_score_codex":0.000072085895,"about_ca_system_score_gemma":0.00009985311,"threshold_uncertainty_score":0.9991969},"labels":[],"label_agreement":null},{"id":"W4382244648","doi":"10.11647/obp.0361.03","title":"Preferences under uncertainty","year":2023,"lang":"en","type":"book-chapter","venue":"Open Book Publishers","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science","score_opus":0.3407427498451363,"score_gpt":0.4178540672739322,"score_spread":0.0771113174287959,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382244648","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0004960033,0.00014374465,0.000032254608,0.0027191367,0.0032610318,0.00077076524,0.00016775957,0.00016410676,0.9922452],"genre_scores_gemma":[0.0012298769,0.000068592104,0.00023759322,0.002088426,0.00022967206,0.000041520634,0.00011788101,0.00013026933,0.99585617],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9938303,0.00009744085,0.0015797586,0.0018943165,0.0020383354,0.0005598104],"domain_scores_gemma":[0.993499,0.0020423084,0.001081502,0.0022970012,0.00067274435,0.00040747758],"candidate_categories":["metaepi_narrow","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0046196138,0.0006259432,0.0011830865,0.00076612947,0.00035098472,0.01782057,0.0077956547,0.0007751972,0.026211517],"category_scores_gemma":[0.001307251,0.00047537067,0.00046135255,0.00026440222,0.00035539875,0.004813874,0.0026912785,0.0008154655,0.019371543],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003095761,0.0000132652285,0.000013736124,0.0000015114884,0.00004062564,0.00001647754,0.00004770562,0.00038545986,3.4078872e-7,0.029520527,0.6952843,0.2746451],"study_design_scores_gemma":[0.00017827725,0.000045322497,0.0000249365,0.00006954601,0.000025626165,0.0000035592934,0.00019254784,0.00004593918,4.337609e-7,0.45500365,0.54404473,0.00036544187],"about_ca_topic_score_codex":0.0003555126,"about_ca_topic_score_gemma":0.0010368794,"teacher_disagreement_score":0.4254831,"about_ca_system_score_codex":0.00028860068,"about_ca_system_score_gemma":0.0009777099,"threshold_uncertainty_score":0.9997698},"labels":[],"label_agreement":null},{"id":"W4382244795","doi":"10.11647/obp.0362.03","title":"Preferences under uncertainty","year":2023,"lang":"en","type":"book-chapter","venue":"Open Book Publishers","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Mathematics","score_opus":0.3407427498451363,"score_gpt":0.4178540672739322,"score_spread":0.0771113174287959,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382244795","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0004960033,0.00014374465,0.000032254608,0.0027191367,0.0032610318,0.00077076524,0.00016775957,0.00016410676,0.9922452],"genre_scores_gemma":[0.0012298769,0.000068592104,0.00023759322,0.002088426,0.00022967206,0.000041520634,0.00011788101,0.00013026933,0.99585617],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9938303,0.00009744085,0.0015797586,0.0018943165,0.0020383354,0.0005598104],"domain_scores_gemma":[0.993499,0.0020423084,0.001081502,0.0022970012,0.00067274435,0.00040747758],"candidate_categories":["metaepi_narrow","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0046196138,0.0006259432,0.0011830865,0.00076612947,0.00035098472,0.01782057,0.0077956547,0.0007751972,0.026211517],"category_scores_gemma":[0.001307251,0.00047537067,0.00046135255,0.00026440222,0.00035539875,0.004813874,0.0026912785,0.0008154655,0.019371543],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003095761,0.0000132652285,0.000013736124,0.0000015114884,0.00004062564,0.00001647754,0.00004770562,0.00038545986,3.4078872e-7,0.029520527,0.6952843,0.2746451],"study_design_scores_gemma":[0.00017827725,0.000045322497,0.0000249365,0.00006954601,0.000025626165,0.0000035592934,0.00019254784,0.00004593918,4.337609e-7,0.45500365,0.54404473,0.00036544187],"about_ca_topic_score_codex":0.0003555126,"about_ca_topic_score_gemma":0.0010368794,"teacher_disagreement_score":0.4254831,"about_ca_system_score_codex":0.00028860068,"about_ca_system_score_gemma":0.0009777099,"threshold_uncertainty_score":0.9997698},"labels":[],"label_agreement":null},{"id":"W4382999365","doi":"10.2139/ssrn.4499212","title":"Rationalization of Indecisive Choice Behavior By Pluralist Ballots","year":2023,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Rationalization (economics); Economics; Psychology; Social psychology; Microeconomics","score_opus":0.12201261400958437,"score_gpt":0.41605233779714745,"score_spread":0.2940397237875631,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382999365","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9695257,0.001206097,0.02431143,0.0010448523,0.0028433194,0.0004479593,0.00030127406,0.00006409968,0.00025528859],"genre_scores_gemma":[0.9909253,0.0015332495,0.00023921565,0.000085217944,0.0004449347,0.000038850267,0.00017662311,0.00007644931,0.0064801313],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99254847,0.00033829157,0.0023070483,0.00091357715,0.00232948,0.0015631515],"domain_scores_gemma":[0.9936433,0.0013483914,0.0025151318,0.0009157906,0.001398135,0.00017928355],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.008395232,0.00042118033,0.00085542176,0.00082403206,0.00031255948,0.000724501,0.0024525342,0.0005341166,0.00029306745],"category_scores_gemma":[0.0037763475,0.00035396026,0.0005701156,0.00068621157,0.00014670141,0.00043114682,0.00073907524,0.0033274272,0.0003283826],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023949075,0.00091849075,0.061235465,0.000019288223,0.00046361744,0.000036826314,0.0007247683,0.0107053,0.0012964214,0.025728576,0.07137727,0.8272545],"study_design_scores_gemma":[0.0005834937,0.00018532341,0.005616343,0.00009362427,0.00014514932,0.000111588895,0.0008426134,0.00055220525,0.0001228369,0.9845645,0.006723399,0.0004589664],"about_ca_topic_score_codex":0.0003383396,"about_ca_topic_score_gemma":0.0019158678,"teacher_disagreement_score":0.9588359,"about_ca_system_score_codex":0.0014207778,"about_ca_system_score_gemma":0.0045347046,"threshold_uncertainty_score":0.9998912},"labels":[],"label_agreement":null},{"id":"W4384297663","doi":"10.1177/00222437231190851","title":"The Agent's Impatience: A Self–Other Decision Model of Intertemporal Choices","year":2023,"lang":"en","type":"article","venue":"Journal of Marketing Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Booth University College","funders":"","keywords":"Intertemporal choice; Interpersonal communication; Anticipation (artificial intelligence); Psychology; Value (mathematics); Economics; Dynamic inconsistency; Social psychology; Microeconomics; Computer science","score_opus":0.3637555493676284,"score_gpt":0.5272688989097731,"score_spread":0.16351334954214475,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4384297663","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99629015,0.00018495694,0.00027825744,0.0006842017,0.0005191332,0.000113559334,0.000005675705,0.00001327812,0.0019108023],"genre_scores_gemma":[0.9968412,0.00034783897,0.0013258336,0.000021523178,0.00012784527,0.000002692944,1.3874383e-7,0.00001734838,0.0013156097],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9918338,0.0015793677,0.0017517046,0.0002968692,0.0039877947,0.0005504598],"domain_scores_gemma":[0.9639841,0.03201581,0.0010114048,0.00064402726,0.002162979,0.00018169328],"candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.12511753,0.000119095785,0.00036578084,0.0010623655,0.00044987292,0.0006064269,0.0024470421,0.00009449275,0.00010655089],"category_scores_gemma":[0.04116583,0.0000630018,0.00029377334,0.0016952065,0.00024812753,0.00042429473,0.0006565296,0.00069444714,0.00015266796],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013836599,0.00010523784,0.024784697,0.000006180263,0.000023433726,0.000023205443,0.00091953354,0.0019188492,0.00068124244,0.000040106945,0.037513394,0.93260044],"study_design_scores_gemma":[0.0023821413,0.0015354165,0.1077318,0.0013895386,0.000040825176,0.0001270697,0.02031056,0.4282558,0.000766799,0.29511884,0.14178857,0.0005526251],"about_ca_topic_score_codex":0.000016491384,"about_ca_topic_score_gemma":0.000026527972,"teacher_disagreement_score":0.93204784,"about_ca_system_score_codex":0.00011989234,"about_ca_system_score_gemma":0.0004280768,"threshold_uncertainty_score":0.96691084},"labels":[],"label_agreement":null},{"id":"W4384572568","doi":"10.1214/23-ba1397","title":"Defining a Credible Interval Is Not Always Possible with “Point-Null” Priors: A Lesser-Known Correlate of the Jeffreys-Lindley Paradox (with Discussion)","year":2023,"lang":"en","type":"article","venue":"Bayesian Analysis","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek; National Science Foundation","keywords":"Prior probability; Mathematics; Interval (graph theory); Mathematical economics; Point estimation; Applied mathematics; Null (SQL); Bayesian probability; Econometrics; Statistics; Computer science; Combinatorics; Data mining","score_opus":0.04654015112076346,"score_gpt":0.33527572829360824,"score_spread":0.2887355771728448,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4384572568","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.975388,0.000034008634,0.018266924,0.0038789657,0.00023283817,0.00026177638,0.00012631807,0.00011232689,0.0016988748],"genre_scores_gemma":[0.99047863,0.000014064043,0.003295965,0.00023157684,0.000032722335,0.00002158123,0.000015254395,0.000041473326,0.005868701],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9950728,0.00025281767,0.0013319254,0.0010938752,0.001681067,0.0005675256],"domain_scores_gemma":[0.99558353,0.0008235438,0.0010111457,0.00197368,0.0003633935,0.00024470597],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002253932,0.00039332034,0.0011134063,0.001347417,0.00043465893,0.0005717473,0.0017501408,0.0001695121,0.00092202565],"category_scores_gemma":[0.00052139885,0.00015694139,0.00082534004,0.00903379,0.00032718762,0.0004966872,0.000490204,0.00037835698,0.00064281345],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010563907,0.00045224896,0.6682098,0.000023442897,0.0016058122,0.00015670032,0.007932261,0.017174551,0.00015361917,0.0009403194,0.01102678,0.29126808],"study_design_scores_gemma":[0.0049842666,0.001671772,0.6166052,0.0016359439,0.008430952,0.00014967684,0.027865866,0.28896987,0.004106325,0.03239815,0.010384115,0.0027978448],"about_ca_topic_score_codex":0.00026671906,"about_ca_topic_score_gemma":0.0018589036,"teacher_disagreement_score":0.28847024,"about_ca_system_score_codex":0.00007214402,"about_ca_system_score_gemma":0.00026947717,"threshold_uncertainty_score":0.99999124},"labels":[],"label_agreement":null},{"id":"W4384625931","doi":"10.1017/s0140525x22003089","title":"Not feeling right about uncertainty monitoring","year":2023,"lang":"en","type":"letter","venue":"Behavioral and Brain Sciences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan; Saskatchewan Health Authority","funders":"","keywords":"Feeling; Metacognition; Process (computing); Dual (grammatical number); Dual process theory (moral psychology); Psychology; Epistemology; Cognitive science; Cognitive psychology; Computer science; Cognition; Social psychology; Philosophy; Neuroscience","score_opus":0.2751635275266549,"score_gpt":0.4442015482417352,"score_spread":0.16903802071508028,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4384625931","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7601745,0.00018871245,0.000018504888,0.2331993,0.005256975,0.00026089427,0.00021392887,0.00021562482,0.000471534],"genre_scores_gemma":[0.6240391,0.00031731595,0.004195929,0.29766813,0.017255953,0.00020594885,0.00015670474,0.00028210328,0.055878825],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99164706,0.0003002167,0.0015066927,0.0022766415,0.003164625,0.0011047879],"domain_scores_gemma":[0.99433804,0.0033951695,0.0007685767,0.0009297793,0.00032550553,0.0002429474],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0061348216,0.0006517569,0.0010295442,0.001099881,0.001450036,0.0034863749,0.002879002,0.0008785884,0.0003492939],"category_scores_gemma":[0.0011041808,0.00044230334,0.00040639352,0.0017471126,0.0013451821,0.00080267293,0.0008098184,0.0014969758,0.001008383],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008563623,0.00003193077,0.006068155,0.0000072856383,0.000005023556,0.00042741018,0.00029837963,0.00007404548,0.00013135395,0.00002111225,0.6911978,0.3017289],"study_design_scores_gemma":[0.00031267936,0.0003432338,0.005959467,0.0003379085,0.00007754985,0.00008959837,0.0009485816,0.00053884165,0.00017714304,0.031056289,0.9588709,0.0012878143],"about_ca_topic_score_codex":0.000741586,"about_ca_topic_score_gemma":0.00011040216,"teacher_disagreement_score":0.30044112,"about_ca_system_score_codex":0.0001124563,"about_ca_system_score_gemma":0.00029046205,"threshold_uncertainty_score":0.9998499},"labels":[],"label_agreement":null},{"id":"W4384626377","doi":"10.1017/s0140525x22002904","title":"A good architecture for fast and slow thinking, but exclusivity is exclusively in the past","year":2023,"lang":"en","type":"letter","venue":"Behavioral and Brain Sciences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University; University of Toronto","funders":"","keywords":"Dual (grammatical number); Architecture; Process (computing); Function (biology); Dual function; Cognitive science; Cognitive psychology; Computer science; Thinking processes; Psychology; Work (physics); Epistemology; History; Engineering; Philosophy; Mathematics education; Linguistics; Programming language","score_opus":0.1688517641540118,"score_gpt":0.40508308594803993,"score_spread":0.23623132179402814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4384626377","genre_codex":"empirical","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.56110424,0.00013375931,0.00015424097,0.43641782,0.0006747962,0.0006650375,0.00059743045,0.000045168425,0.00020752681],"genre_scores_gemma":[0.2200114,0.00010211949,0.004592812,0.7566012,0.0042356914,0.000465765,0.00012028899,0.00013492137,0.013735767],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99385345,0.00038347108,0.0009620665,0.0018567956,0.0020985093,0.00084568904],"domain_scores_gemma":[0.9936181,0.0048291236,0.00056978175,0.00070298294,0.00016335372,0.00011667027],"candidate_categories":["metaepi_narrow","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0073527093,0.0005560383,0.00082911854,0.000839796,0.0013271769,0.0028532473,0.0027928636,0.0006430062,0.000050951796],"category_scores_gemma":[0.00068360067,0.00031206207,0.00028595026,0.0013070123,0.0015260081,0.00044761266,0.00088295044,0.0012214945,0.000043817185],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000147967385,0.00005821403,0.00688326,0.0000149743355,0.0000032263758,0.0001382799,0.003529627,0.000006506682,0.000025551866,0.000050103685,0.6701413,0.3191342],"study_design_scores_gemma":[0.0006722355,0.0008358047,0.021475896,0.00019476074,0.000078748395,0.00024557806,0.004716604,0.00028984196,0.000010108004,0.18913428,0.78134793,0.0009981872],"about_ca_topic_score_codex":0.0005817314,"about_ca_topic_score_gemma":0.0008754876,"teacher_disagreement_score":0.34109282,"about_ca_system_score_codex":0.000041218515,"about_ca_system_score_gemma":0.00018737795,"threshold_uncertainty_score":0.99997294},"labels":[],"label_agreement":null},{"id":"W4384626957","doi":"10.1017/s0140525x2200303x","title":"Correction, uncertainty, and anchoring effects","year":2023,"lang":"en","type":"letter","venue":"Behavioral and Brain Sciences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Anchoring; Heuristic; Psychology; Noise (video); Cognitive psychology; Computer science; Social psychology; Artificial intelligence","score_opus":0.16981545685415336,"score_gpt":0.4181655745018714,"score_spread":0.24835011764771805,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4384626957","genre_codex":"empirical","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7577403,0.00031409104,0.00004214629,0.23054303,0.009976625,0.00039261745,0.00006993094,0.00021436454,0.0007069],"genre_scores_gemma":[0.3918278,0.00048990006,0.0019732653,0.49383286,0.012657582,0.0002800785,0.00014188953,0.00026404875,0.098532595],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9948772,0.0002694895,0.0008241903,0.0017470364,0.0015976746,0.0006844072],"domain_scores_gemma":[0.9936761,0.0049855635,0.00044513211,0.00052528095,0.00018142647,0.00018649276],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.003655289,0.0004651188,0.0007620479,0.0008543634,0.000990981,0.0022989179,0.0011260688,0.0005877989,0.000103213104],"category_scores_gemma":[0.0015893502,0.00032391632,0.00016951733,0.0013407767,0.0012956167,0.00058982434,0.00063000375,0.0009878678,0.00029879893],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000023960356,0.0000119731785,0.0039305915,0.000005805819,0.0000019576607,0.000109347166,0.000114806106,0.000008057913,0.00002514206,0.0000070641627,0.6665496,0.32923326],"study_design_scores_gemma":[0.00031994242,0.0006998017,0.010354081,0.00030122462,0.000074476964,0.00016558259,0.0006483414,0.0009112525,0.000042023876,0.03566888,0.94985706,0.00095734233],"about_ca_topic_score_codex":0.0005710143,"about_ca_topic_score_gemma":0.00024429127,"teacher_disagreement_score":0.3659125,"about_ca_system_score_codex":0.000056356093,"about_ca_system_score_gemma":0.0001515635,"threshold_uncertainty_score":0.99992126},"labels":[],"label_agreement":null},{"id":"W4384756320","doi":"10.48550/arxiv.2307.08542","title":"Anticomonotonicity for Preference Axioms: The Natural Counterpart to Comonotonicity","year":2023,"lang":"en","type":"preprint","venue":"EUR Research Repository (Erasmus University Rotterdam)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Axiom; Ambiguity; Mathematical economics; Preference; Expected utility hypothesis; Ambiguity aversion; Mathematics; Risk aversion (psychology); Variation (astronomy); Subjective expected utility; Arbitrage; Econometrics; Economics; Computer science; Financial economics; Statistics","score_opus":0.49324705576098443,"score_gpt":0.47168622251699655,"score_spread":0.021560833243987887,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4384756320","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98116153,0.00006394026,0.0028684055,0.004941845,0.0046547763,0.0035126114,0.0004074244,0.00025396858,0.002135464],"genre_scores_gemma":[0.9787887,0.00004628971,0.0005924895,0.00023558241,0.000421612,0.00006439051,0.000034995348,0.000067767054,0.01974822],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9895421,0.0021157921,0.001149994,0.0025810443,0.0032836716,0.0013273497],"domain_scores_gemma":[0.98527265,0.007338687,0.0005955289,0.0037932259,0.002444856,0.00055503706],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","open_science","research_integrity","insufficient_payload"],"consensus_categories":["open_science"],"category_scores_codex":[0.010751802,0.000594272,0.0010256532,0.0014350875,0.0027354604,0.002572867,0.008461851,0.00051741727,0.00003876751],"category_scores_gemma":[0.002956652,0.0004662772,0.00075055583,0.0014020986,0.00078979356,0.0004682793,0.008396121,0.003002619,0.000926474],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0121293655,0.0021770503,0.03434812,0.00042094258,0.0010654948,0.0032093357,0.016871989,0.018649984,0.009084547,0.0052139238,0.7779104,0.11891884],"study_design_scores_gemma":[0.004533382,0.0016266102,0.07148917,0.0014915084,0.00029047162,0.00014016815,0.010609771,0.08967595,0.0063052126,0.05671907,0.75359833,0.003520349],"about_ca_topic_score_codex":0.0020623833,"about_ca_topic_score_gemma":0.0009804296,"teacher_disagreement_score":0.1153985,"about_ca_system_score_codex":0.0012825922,"about_ca_system_score_gemma":0.0013049594,"threshold_uncertainty_score":0.9998514},"labels":[],"label_agreement":null},{"id":"W4384827856","doi":"10.31219/osf.io/apc26","title":"The robustness of mental accounting: a global perspective","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Robustness (evolution); Mental accounting; Accounting; Psychology; Perspective (graphical); Business; Computer science; Actuarial science; Artificial intelligence; Biology","score_opus":0.2367439942955789,"score_gpt":0.4664540749030524,"score_spread":0.2297100806074735,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4384827856","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.967457,0.00015238735,0.0021758685,0.0031744028,0.007549005,0.00038976123,0.00025584392,0.000117325246,0.018728437],"genre_scores_gemma":[0.9948946,0.000046408848,0.00091933727,0.000036329715,0.00020206739,0.000020082354,0.000005320087,0.000019505995,0.0038563083],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9962324,0.00012027934,0.0010729897,0.0008988218,0.0013783353,0.00029720878],"domain_scores_gemma":[0.995326,0.0014928656,0.0008008053,0.0014082718,0.0008953122,0.00007673604],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036484702,0.0002546897,0.00053097337,0.00014025393,0.00027189203,0.000996731,0.0027755173,0.00025023447,0.00021098074],"category_scores_gemma":[0.0026349376,0.00014347283,0.00045799417,0.0005485438,0.00028822958,0.0001285907,0.0033068378,0.00035299626,0.00046330967],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002887462,0.00035800424,0.024227452,0.000011553131,0.0002298073,0.000026113301,0.0016621844,0.034848183,0.000016392049,0.031145068,0.22592232,0.68126416],"study_design_scores_gemma":[0.00034899666,0.000060330425,0.01710917,0.00010996341,0.000059946822,0.000016277669,0.034317866,0.02625704,0.000046391608,0.9113965,0.009742031,0.00053547166],"about_ca_topic_score_codex":0.00068740937,"about_ca_topic_score_gemma":0.0010280468,"teacher_disagreement_score":0.88025147,"about_ca_system_score_codex":0.00042242484,"about_ca_system_score_gemma":0.0003467441,"threshold_uncertainty_score":0.96115005},"labels":[],"label_agreement":null},{"id":"W4385191668","doi":"10.3758/s13421-023-01439-x","title":"Option similarity modulates the link between choice and memory","year":2023,"lang":"en","type":"article","venue":"Memory & Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Similarity (geometry); Psychology; Cognitive psychology; Encoding (memory); Variable (mathematics); Social psychology; Computer science; Artificial intelligence","score_opus":0.21608904997014555,"score_gpt":0.4073662493391805,"score_spread":0.19127719936903492,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385191668","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.992025,0.00005430813,0.000453935,0.004354396,0.00046563626,0.00024756583,0.000059340116,0.00016088758,0.002178943],"genre_scores_gemma":[0.9979542,0.00003760489,0.00012051788,0.00029569023,0.0007181566,0.000018425704,0.000059407157,0.000015942143,0.0007800511],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9978447,0.00021340369,0.00052877225,0.0005306744,0.00063091994,0.00025153017],"domain_scores_gemma":[0.99647707,0.0024882802,0.00020766073,0.0004901394,0.00023608399,0.00010077906],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0032365394,0.00015894468,0.0002547453,0.00026180595,0.00048625993,0.00045109953,0.0003981429,0.0001414584,0.00014961505],"category_scores_gemma":[0.0018959009,0.00010880562,0.00010478077,0.00068746833,0.00016347175,0.00047631565,0.00021270849,0.0002495746,0.0015073082],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008571742,0.000008728633,0.0024818515,0.0000027182227,0.000007766574,0.0000042757456,0.00020470728,0.0001872396,0.000637503,0.000021775548,0.0012752706,0.99515957],"study_design_scores_gemma":[0.000786088,0.00014361381,0.51638895,0.00006423908,0.00014291483,0.000015697991,0.0015348408,0.010648572,0.0022881764,0.44803375,0.019514296,0.00043889196],"about_ca_topic_score_codex":0.000037255428,"about_ca_topic_score_gemma":0.000043404652,"teacher_disagreement_score":0.9947207,"about_ca_system_score_codex":0.000027324419,"about_ca_system_score_gemma":0.000029346955,"threshold_uncertainty_score":0.99927014},"labels":[],"label_agreement":null},{"id":"W4385269243","doi":"10.1101/2023.07.20.23292967","title":"Delay Discounting and Family History of Psychopathology in Children Ages 9-11: Results from the ABCD Study","year":2023,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"The Scarborough Hospital; University of Toronto; Centre for Addiction and Mental Health","funders":"National Institute of Mental Health; National Institutes of Health","keywords":"Delay discounting; Psychopathology; Discounting; Psychology; Family history; Developmental psychology; Clinical psychology; Impulsivity; Medicine","score_opus":0.1798392415251144,"score_gpt":0.3907426400221034,"score_spread":0.210903398496989,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385269243","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9947672,0.00070158625,0.000036964062,0.00039143665,0.0030220093,0.00050171197,0.00032317382,0.00003927697,0.00021666528],"genre_scores_gemma":[0.99879676,0.000100476194,0.00023734373,0.000088185974,0.00014445628,0.000027637092,0.00002610895,0.000030524672,0.0005485301],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9951855,0.0006354709,0.0017562438,0.001395489,0.00076466426,0.00026265834],"domain_scores_gemma":[0.9935632,0.0033741903,0.0010380185,0.0018399435,0.0001239409,0.000060741655],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008482619,0.00029376562,0.0007957359,0.00041687675,0.000068984424,0.00015125737,0.0019107895,0.00025030927,0.00002113577],"category_scores_gemma":[0.003662128,0.00018928865,0.00015482516,0.0002700985,0.0002980435,0.00010400227,0.0016871652,0.0006728811,0.000078634],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005437407,0.00012950397,0.9565077,9.440988e-7,0.000015163198,0.00003801962,0.003685084,0.00024434525,0.00004465689,0.000004243217,0.0035353838,0.03574063],"study_design_scores_gemma":[0.0005772623,0.000046430872,0.9844407,0.000078985446,0.000035221536,0.0000036242818,0.0013632069,0.0001968794,0.0000013929293,0.011915628,0.0011450832,0.00019558433],"about_ca_topic_score_codex":0.0049107727,"about_ca_topic_score_gemma":0.0036611825,"teacher_disagreement_score":0.035545044,"about_ca_system_score_codex":0.00012007334,"about_ca_system_score_gemma":0.00014325583,"threshold_uncertainty_score":0.7718967},"labels":[],"label_agreement":null},{"id":"W4385450060","doi":"10.2139/ssrn.4526931","title":"Eliciting Stopping Times","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Computer science; Statistics; Mathematics","score_opus":0.09845034831975613,"score_gpt":0.4005181453126801,"score_spread":0.30206779699292396,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385450060","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9897406,0.00029688352,0.003104179,0.0015099307,0.0006592383,0.00005097865,0.000002249338,0.000106046245,0.0045298655],"genre_scores_gemma":[0.99392,0.0004441321,0.0001246273,0.00013853241,0.0003845206,0.000001867474,0.0000013903668,0.000021391023,0.0049634916],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9958608,0.00012716847,0.0007212597,0.00035438407,0.00083069195,0.0021057078],"domain_scores_gemma":[0.99827665,0.00073354895,0.00034021493,0.00034553636,0.00018626435,0.00011780975],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.011810303,0.00014432799,0.00026774933,0.00057823164,0.0004986191,0.0005326193,0.000935086,0.000078243786,0.00026767407],"category_scores_gemma":[0.0017362876,0.000109258,0.00021886783,0.0010344739,0.000043869295,0.00041772315,0.00015178305,0.0012632374,0.003976112],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010256115,0.000011717523,0.0013451,2.340143e-7,0.000014589279,0.000012772208,0.00011303429,0.00039249338,0.00020086355,0.010535677,0.002345304,0.98501796],"study_design_scores_gemma":[0.00021322058,0.00008643288,0.00046447953,0.000014414215,0.000008871405,0.00031971137,0.0046518315,0.0017177811,0.00003664076,0.9774564,0.014879588,0.00015064485],"about_ca_topic_score_codex":0.000017376304,"about_ca_topic_score_gemma":0.00012595164,"teacher_disagreement_score":0.98486733,"about_ca_system_score_codex":0.00042869934,"about_ca_system_score_gemma":0.0010419954,"threshold_uncertainty_score":0.9967994},"labels":[],"label_agreement":null},{"id":"W4385698187","doi":"10.1287/moor.2022.0317","title":"(No-)Betting Pareto Optima Under Rank-Dependent Utility","year":2023,"lang":"en","type":"article","venue":"Mathematics of Operations Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Generality; Pareto principle; Ambiguity; Expected utility hypothesis; Economics; Mathematical economics; Aggregate (composite); Weighting; Rank (graph theory); Matching (statistics); Preference; Probabilistic logic; Econometrics; Mathematics; Mathematical optimization; Microeconomics; Computer science; Statistics","score_opus":0.5542620435669947,"score_gpt":0.5590239752768249,"score_spread":0.004761931709830192,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385698187","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97632307,0.00002222448,0.0059205345,0.00086325576,0.00022241243,0.00041447993,0.00005473888,0.00006693095,0.016112346],"genre_scores_gemma":[0.9750861,0.000019297415,0.015259496,0.000020341995,0.000055859324,0.000047182137,0.000010505439,0.00002158891,0.009479622],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99502605,0.00033326063,0.0012024107,0.00050154247,0.0024787302,0.0004579771],"domain_scores_gemma":[0.9929485,0.0035396644,0.000090555084,0.0013290283,0.0019477907,0.00014451455],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.017073086,0.00013522072,0.00038693662,0.00081107643,0.0005906793,0.0007639343,0.0012888589,0.000111991474,0.0017263998],"category_scores_gemma":[0.011421842,0.000102707214,0.00013711592,0.0016968953,0.00026090257,0.00036564306,0.00066407607,0.0003524466,0.0074826097],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016146491,0.003701296,0.005961074,0.00027233936,0.00019870551,0.000099200006,0.013595947,0.20379797,0.026160166,0.09305188,0.10692675,0.5460732],"study_design_scores_gemma":[0.0005478982,0.00016264827,0.0016354371,0.0001201659,0.000013540223,0.000012523395,0.011246825,0.703334,0.0032342763,0.27527505,0.004098548,0.0003190926],"about_ca_topic_score_codex":0.00007967896,"about_ca_topic_score_gemma":0.000115969335,"teacher_disagreement_score":0.54575413,"about_ca_system_score_codex":0.00007149939,"about_ca_system_score_gemma":0.00025794268,"threshold_uncertainty_score":0.99918616},"labels":[],"label_agreement":null},{"id":"W4385839849","doi":"10.1007/s42113-023-00178-1","title":"Humans Adopt Different Exploration Strategies Depending on the Environment","year":2023,"lang":"en","type":"article","venue":"Computational Brain & Behavior","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institute for Advanced Research","keywords":"Task (project management); Heuristic; Probabilistic logic; Cognitive psychology; Artificial intelligence; Reinforcement learning; Computer science; Machine learning; Trait; Contrast (vision); Softmax function; Cognition; Flexibility (engineering); Psychology; Statistics; Mathematics; Deep learning; Engineering","score_opus":0.26391598024537366,"score_gpt":0.4076021962323015,"score_spread":0.14368621598692782,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385839849","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98686033,0.0000074515406,0.007873315,0.003776183,0.00051532354,0.00033889667,0.00004729442,0.00011512959,0.00046608332],"genre_scores_gemma":[0.99825174,0.0000032846515,0.00033688577,0.00038887034,0.00008710214,0.00014273227,0.00009554292,0.00002164724,0.00067222444],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99697065,0.00020245883,0.000647893,0.0005739869,0.001336076,0.00026896037],"domain_scores_gemma":[0.99546427,0.003644265,0.00023573595,0.0004848831,0.000079791986,0.00009105528],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0013387272,0.00021373518,0.00022534576,0.00032141592,0.00055977824,0.0008109174,0.000691063,0.00007417491,0.0009001438],"category_scores_gemma":[0.00033780542,0.0001380312,0.00016576721,0.0003680121,0.00011938178,0.00044957877,0.00018789995,0.00020233108,0.0037277564],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000039159346,0.000522746,0.009325353,0.000001825963,0.000017582612,0.00007730433,0.0021304137,0.2849042,0.001081766,0.049751833,0.032576226,0.61957157],"study_design_scores_gemma":[0.00061680895,0.00032022005,0.47740623,0.000043935903,0.000044269145,0.000008281003,0.0091304565,0.026402555,0.0002296806,0.47368643,0.011517918,0.0005932199],"about_ca_topic_score_codex":0.000004408378,"about_ca_topic_score_gemma":0.00001024389,"teacher_disagreement_score":0.6189784,"about_ca_system_score_codex":0.00011178804,"about_ca_system_score_gemma":0.000054050543,"threshold_uncertainty_score":0.99704796},"labels":[],"label_agreement":null},{"id":"W4386271874","doi":"10.1017/s0140525x23000857","title":"Nudges, regulations, and behavioral public choice","year":2023,"lang":"en","type":"letter","venue":"Behavioral and Brain Sciences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Nudge theory; Psychology; Social psychology","score_opus":0.3885912200096558,"score_gpt":0.4611049836902284,"score_spread":0.07251376368057261,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386271874","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6184269,0.00031877507,0.000011458794,0.37875375,0.0014216432,0.00031557042,0.00028819713,0.00017996173,0.00028370312],"genre_scores_gemma":[0.4969908,0.00036304988,0.0048841326,0.41693726,0.007343499,0.00033369428,0.0007141387,0.00035916537,0.072074234],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9921561,0.0003926259,0.00143014,0.0023802524,0.0025889,0.0010519689],"domain_scores_gemma":[0.99470514,0.0028222825,0.000767652,0.0010016148,0.0003508927,0.00035239864],"candidate_categories":["metaepi_narrow","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00468028,0.00066766294,0.0009941357,0.0014688289,0.0014804837,0.0047481423,0.0020704519,0.0009829857,0.0003865319],"category_scores_gemma":[0.0011398813,0.00049240806,0.0002652954,0.0020558287,0.002364837,0.0014782769,0.0010190259,0.0012314263,0.00037861863],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000023077243,0.000053386302,0.017802129,0.000004380269,0.000002782612,0.000093493596,0.00012264069,8.6211816e-7,0.000025798412,0.00006030386,0.6892965,0.29253542],"study_design_scores_gemma":[0.0002960914,0.0004236911,0.024438137,0.00006613081,0.000075348966,0.00012942802,0.00060860126,0.00013342402,0.000006584123,0.022162165,0.9507768,0.0008835659],"about_ca_topic_score_codex":0.0009789709,"about_ca_topic_score_gemma":0.000726439,"teacher_disagreement_score":0.29165184,"about_ca_system_score_codex":0.000079210964,"about_ca_system_score_gemma":0.00033169927,"threshold_uncertainty_score":0.99981946},"labels":[],"label_agreement":null},{"id":"W4386578390","doi":"10.1093/jeea/jvad036","title":"Past and Future: Backward and Forward Discounting","year":2023,"lang":"en","type":"article","venue":"Journal of the European Economic Association","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Simons Institute for the Theory of Computing, University of California Berkeley; Social Sciences and Humanities Research Council of Canada; Zhejiang University; Queen's University; Erasmus Universiteit Rotterdam; Agence Nationale de la Recherche; National Science Foundation","keywords":"Regret; Anticipation (artificial intelligence); Time preference; Economics; Discounting; Consumption (sociology); Dynamic inconsistency; Set (abstract data type); Preference; Hyperbolic discounting; Microeconomics; Positive economics; Computer science","score_opus":0.04201173345269537,"score_gpt":0.31921471735623425,"score_spread":0.27720298390353887,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386578390","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9874875,0.000045902438,0.000026714732,0.0062698633,0.0021584672,0.00004128149,0.000010048306,0.000009448511,0.0039507565],"genre_scores_gemma":[0.99681187,0.00015590961,0.00011085563,0.00013088023,0.0016038402,1.6269108e-7,4.1689322e-7,0.000014315451,0.0011717231],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99834865,0.0003255661,0.0007553479,0.00016489529,0.00026064838,0.00014486864],"domain_scores_gemma":[0.9974439,0.000640156,0.0015744282,0.00017922497,0.00009754828,0.0000647086],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009212359,0.00008659073,0.00023221782,0.00015525587,0.0001925532,0.00055149937,0.0003947607,0.000036619324,0.000023891347],"category_scores_gemma":[0.00084671535,0.000054548826,0.00012920873,0.0001326471,0.000030673193,0.0005370769,0.00023819339,0.00017124572,0.00028176807],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014524589,0.000009351221,0.2978868,0.000001285853,0.00003457236,0.0000058469504,0.0006524704,0.00028272186,0.000059472837,0.00011542658,0.05885797,0.6420796],"study_design_scores_gemma":[0.00046382128,0.000037145222,0.8356186,0.000019642257,0.000037183363,0.00003981438,0.0012727529,0.00082793616,0.000012285491,0.016666377,0.14488596,0.00011848784],"about_ca_topic_score_codex":0.0000019602146,"about_ca_topic_score_gemma":0.000008617953,"teacher_disagreement_score":0.6419611,"about_ca_system_score_codex":0.00018743852,"about_ca_system_score_gemma":0.000029291064,"threshold_uncertainty_score":0.5318121},"labels":[],"label_agreement":null},{"id":"W4386639396","doi":"10.54254/2754-1169/13/20230670","title":"Behavioral Economics: The Decoy Effect","year":2023,"lang":"en","type":"article","venue":"Advances in Economics Management and Political Sciences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Nudge theory; Decoy; Behavioral economics; Consumption (sociology); Revenue; Prospect theory; Economics; Marketing; Consumer behaviour; Public economics; Advertising; Psychology; Microeconomics; Social psychology; Business; Sociology; Medicine; Social science","score_opus":0.07883848371310988,"score_gpt":0.4260058056611917,"score_spread":0.34716732194808186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386639396","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95537394,0.0002210273,0.000029654004,0.0019777783,0.0009786321,0.00026517833,0.000017716793,0.000045994104,0.041090105],"genre_scores_gemma":[0.9966036,0.001731739,0.00033816218,0.0005009333,0.000095002295,0.000042850555,0.000002875103,0.00001020107,0.00067464996],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99728304,0.00012369291,0.00075359363,0.00083316915,0.00020615794,0.00080035394],"domain_scores_gemma":[0.99697644,0.0021869855,0.00016449485,0.00047285898,0.000019159033,0.00018007035],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004374458,0.00021719017,0.00036434332,0.0004965503,0.00044201978,0.0007948733,0.0013360822,0.00006434203,0.00008192898],"category_scores_gemma":[0.000185927,0.00013949515,0.00011310502,0.00065380184,0.0009767734,0.0011536432,0.0006116674,0.00013878066,0.000546917],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013304105,0.000022708371,0.054201666,0.0000027000465,0.0000033496256,0.0000066206667,0.000053817927,0.0015721387,2.5162288e-7,0.26849037,0.00022633663,0.67540675],"study_design_scores_gemma":[0.00034674417,0.0001896376,0.018560832,0.000012942939,0.000015232311,0.000006978899,0.001499727,0.008213835,0.000018504665,0.82153445,0.14932954,0.00027156973],"about_ca_topic_score_codex":0.00005314634,"about_ca_topic_score_gemma":0.00044555546,"teacher_disagreement_score":0.67513514,"about_ca_system_score_codex":0.00008981249,"about_ca_system_score_gemma":0.000026819003,"threshold_uncertainty_score":0.76649815},"labels":[],"label_agreement":null},{"id":"W4386641068","doi":"10.54254/2754-1169/11/20230513","title":"The Anchoring Effect and Related Applications: Cognitive Inertia and Habitual Thinking","year":2023,"lang":"en","type":"article","venue":"Advances in Economics Management and Political Sciences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Anchoring; Subconscious; Irrational number; Psychology; Tian; Cognition; Limiting; Cognitive psychology; Social psychology; Economics; Mathematics; Engineering; Neuroscience","score_opus":0.03533087621799814,"score_gpt":0.3795166858489186,"score_spread":0.3441858096309205,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386641068","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97750676,0.0015129176,0.00009377337,0.0010427478,0.00023899134,0.00030935364,0.000005826201,0.00003184038,0.019257765],"genre_scores_gemma":[0.9948595,0.0044716336,0.0002152216,0.00013244861,0.000037020374,0.000051025767,0.0000012237203,0.000004792504,0.00022713623],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9983325,0.000075594944,0.00044640744,0.000566958,0.0001675417,0.00041097327],"domain_scores_gemma":[0.9955279,0.0040880586,0.0001066043,0.0001484521,0.000018564684,0.00011040615],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003389086,0.00012588399,0.00019806084,0.00024078804,0.0006951455,0.0007486292,0.00035848748,0.000040784544,0.0000050388426],"category_scores_gemma":[0.00036931172,0.000081555125,0.000025697005,0.00045884465,0.0010379667,0.00074114965,0.00045606252,0.0001027292,0.000034175842],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008110134,0.00000478655,0.0459524,0.0000036798851,0.0000036046272,0.0000021041246,0.000076590724,0.000059222784,3.2690372e-7,0.2816045,0.000013067997,0.6722716],"study_design_scores_gemma":[0.00028973666,0.0000873867,0.032761976,0.000034436547,0.000012298141,0.0000057929337,0.0026004903,0.0054030376,0.000007329494,0.9428719,0.015774833,0.00015074253],"about_ca_topic_score_codex":0.000012617615,"about_ca_topic_score_gemma":0.00008199771,"teacher_disagreement_score":0.67212087,"about_ca_system_score_codex":0.000024387395,"about_ca_system_score_gemma":0.00000958589,"threshold_uncertainty_score":0.7219049},"labels":[],"label_agreement":null},{"id":"W4386686232","doi":"10.54254/2754-1169/15/20230878","title":"Loss Aversion and Protectionism","year":2023,"lang":"en","type":"article","venue":"Advances in Economics Management and Political Sciences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Loss aversion; Economics; Prospect theory; Protectionism; Grossman; Behavioral economics; Microeconomics; Empirical research; Risk aversion (psychology); Commercial policy; Positive economics; International economics; Financial economics; Expected utility hypothesis; Keynesian economics","score_opus":0.06986783919150553,"score_gpt":0.3896250657973704,"score_spread":0.31975722660586486,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386686232","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9634565,0.00013743504,0.00014026497,0.001833238,0.00043364166,0.00016463206,0.0000064717997,0.000034843753,0.03379297],"genre_scores_gemma":[0.9962308,0.0018463095,0.00083934993,0.00025333927,0.000040308776,0.0000137510015,8.7885405e-7,0.000004146879,0.0007711194],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99835193,0.000041141568,0.000399124,0.00059398793,0.0001869273,0.0004268718],"domain_scores_gemma":[0.9990578,0.0005324833,0.00008247291,0.00017560083,0.000015935946,0.00013567148],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018604797,0.000111684436,0.00019025047,0.00045881514,0.0003096069,0.00041155983,0.00036461244,0.00004300547,0.000037166366],"category_scores_gemma":[0.00015181962,0.00008832613,0.000031663076,0.00050694885,0.00065867935,0.000982865,0.00038095308,0.00007425948,0.00016198028],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008399386,0.000014117125,0.042823676,0.0000046362206,0.0000016118005,0.000008577842,0.00004674294,0.00044136107,6.6623977e-7,0.3710387,0.00008685284,0.5855246],"study_design_scores_gemma":[0.0002006537,0.00006380353,0.022482518,0.000013358758,0.000003333363,0.000006256359,0.0012044231,0.0066295685,0.00001165849,0.89562374,0.07361867,0.00014203256],"about_ca_topic_score_codex":0.000029636605,"about_ca_topic_score_gemma":0.00008067165,"teacher_disagreement_score":0.58538264,"about_ca_system_score_codex":0.00003990481,"about_ca_system_score_gemma":0.00001203236,"threshold_uncertainty_score":0.39686808},"labels":[],"label_agreement":null},{"id":"W4386928383","doi":"10.31234/osf.io/y2fdh","title":"Probabilistic models of delay discounting: improving plausibility and performance","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Discounting; Probabilistic logic; Range (aeronautics); Econometrics; Statistical model; Delay discounting; Mathematics; Regression; Series (stratigraphy); Computer science; Statistics; Economics; Engineering","score_opus":0.28239138885275744,"score_gpt":0.3993078294059782,"score_spread":0.11691644055322076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386928383","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9904448,0.000043215354,0.006315626,0.00009628838,0.00086849235,0.00042751772,0.00008856173,0.00009032771,0.0016251862],"genre_scores_gemma":[0.9946382,0.000025311834,0.003979971,0.000018065608,0.00004951131,0.000024630128,0.00000791577,0.000026092708,0.0012302729],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9957353,0.000078741454,0.0016196844,0.0013372097,0.00093050423,0.00029858726],"domain_scores_gemma":[0.9956544,0.0013612999,0.00084877753,0.0015705344,0.00044931707,0.000115684685],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00530183,0.00030186411,0.00077424565,0.00032583636,0.00012474413,0.00048746978,0.0011306697,0.00029785495,0.00008951279],"category_scores_gemma":[0.0021972577,0.00021216582,0.00018400293,0.00027332373,0.00025883844,0.00041958477,0.0029723512,0.00047102608,0.000069467904],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012710983,0.0001857164,0.038562823,0.0003392862,0.000026722239,0.000009524569,0.0009864104,0.09971872,0.00007013692,0.0014094018,0.000721134,0.85784304],"study_design_scores_gemma":[0.000111649824,0.00006099805,0.010038319,0.00011474673,0.000029849814,0.0000048036213,0.00023361198,0.5625399,0.00004464529,0.426511,0.00003811105,0.0002724326],"about_ca_topic_score_codex":0.00043792877,"about_ca_topic_score_gemma":0.00028436398,"teacher_disagreement_score":0.8575706,"about_ca_system_score_codex":0.000083379746,"about_ca_system_score_gemma":0.0002765449,"threshold_uncertainty_score":0.8651871},"labels":[],"label_agreement":null},{"id":"W4386967128","doi":"10.1080/13546783.2023.2259548","title":"Open-minded and reflective thinking predicts reasoning and meta-reasoning: evidence from a ratio-bias conflict task","year":2023,"lang":"en","type":"article","venue":"Thinking & Reasoning","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Okanagan College","funders":"","keywords":"Psychology; Critical thinking; Analytic reasoning; Task (project management); Cognition; Cognitive psychology; Semantic reasoner; Verbal reasoning; Numeracy; Dual process theory (moral psychology); Reflection (computer programming); Social psychology; Confirmation bias; Debiasing; Epistemology; Mathematics education; Moral reasoning; Deductive reasoning; Artificial intelligence; Computer science; Pedagogy","score_opus":0.2915215675014313,"score_gpt":0.4302327762172313,"score_spread":0.1387112087158,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386967128","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9887065,0.002648744,0.0032984267,0.0010046907,0.0005906714,0.0007743872,0.00006548065,0.0005457873,0.0023652993],"genre_scores_gemma":[0.9645267,0.00029261163,0.0326642,0.0006695649,0.00022888328,0.00009559813,0.000027666083,0.00009900335,0.0013957333],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99199235,0.000911174,0.0015117617,0.0024273272,0.0021884586,0.0009689096],"domain_scores_gemma":[0.98651636,0.009911739,0.0012997608,0.0012868076,0.00050219137,0.00048316625],"candidate_categories":["metaresearch","metaepi_narrow","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.01490689,0.0007323755,0.0017265158,0.00067849696,0.0021347057,0.007153654,0.002697302,0.00039495213,0.0002635022],"category_scores_gemma":[0.022498908,0.0005800091,0.0002801585,0.0017148437,0.0003687479,0.0031338525,0.0033104883,0.00096057955,0.00019671317],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001776612,0.00031357733,0.24420632,0.00006565458,0.0036657301,0.0015957599,0.21875046,0.003868044,0.008653854,0.024126062,0.020162258,0.47281566],"study_design_scores_gemma":[0.0046530496,0.0010878337,0.21069883,0.0054884064,0.0059447405,0.0006765708,0.017665874,0.15001923,0.0024212042,0.5823831,0.014911004,0.004050184],"about_ca_topic_score_codex":0.0019863686,"about_ca_topic_score_gemma":0.00039231562,"teacher_disagreement_score":0.558257,"about_ca_system_score_codex":0.00018540985,"about_ca_system_score_gemma":0.0002864184,"threshold_uncertainty_score":0.99966514},"labels":[],"label_agreement":null},{"id":"W4387186156","doi":"10.1093/oxfordhb/9780197541302.013.10","title":"Perceiving Threat","year":2023,"lang":"en","type":"book-chapter","venue":"Oxford University Press eBooks","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Psychology; Computer science","score_opus":0.2017885427189906,"score_gpt":0.325604451188001,"score_spread":0.12381590846901042,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387186156","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0036285126,0.00001607407,0.00018835347,0.000034483586,0.0009020453,0.00021847592,0.00020438332,0.0002527572,0.99455494],"genre_scores_gemma":[0.0026863506,0.000115890885,0.00023347531,0.00004523052,0.00013182,3.7021198e-7,0.000012981081,0.00006804167,0.99670583],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.997104,0.000045769637,0.000500452,0.0010163907,0.0009776059,0.00035576406],"domain_scores_gemma":[0.9968687,0.00086722954,0.00045572134,0.0013138233,0.00027179782,0.00022272255],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00074747927,0.0004088058,0.0006699633,0.0006042246,0.00037383006,0.0003612403,0.0019364655,0.0005441157,0.00038047956],"category_scores_gemma":[0.00013181331,0.00038961304,0.0005217747,0.000028162607,0.00023343135,0.00021254022,0.0012005949,0.00053745275,0.00022830725],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008926136,0.000012609942,0.000037490652,0.000008211735,0.00006889899,0.0006113061,0.00047465577,0.000056130968,0.0000072350313,0.33860525,0.027536262,0.6324927],"study_design_scores_gemma":[0.00020642282,0.00004260668,0.000059178783,0.000102347476,0.00008530503,0.000010903486,0.00013444012,0.00010989213,0.0000048464317,0.06449042,0.9343398,0.00041383234],"about_ca_topic_score_codex":0.000063084444,"about_ca_topic_score_gemma":0.000113998394,"teacher_disagreement_score":0.90680355,"about_ca_system_score_codex":0.00019371636,"about_ca_system_score_gemma":0.00012025663,"threshold_uncertainty_score":0.9998556},"labels":[],"label_agreement":null},{"id":"W4387894662","doi":"10.1002/bdm.2361","title":"Preference for quicker offers: The critical roles of temporal reference points and evaluation mode","year":2023,"lang":"en","type":"article","venue":"Journal of Behavioral Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Natural Science Foundation of China","keywords":"Preference; Mode (computer interface); Point (geometry); Salient; Feeling; Cognitive psychology; Computer science; Psychology; Joint (building); Social psychology; Artificial intelligence; Human–computer interaction; Mathematics; Statistics","score_opus":0.39145312597477916,"score_gpt":0.524278844454063,"score_spread":0.13282571847928387,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387894662","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9898777,0.00016555128,0.008109759,0.0005397597,0.00083992176,0.0003286984,0.00006553513,0.000015848742,0.000057216286],"genre_scores_gemma":[0.98403436,0.00003449556,0.01569925,0.000062838844,0.0001035429,0.000013298457,0.000002411265,0.000021647991,0.000028130118],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9940299,0.0003488071,0.0022200693,0.0004613573,0.0025946237,0.000345243],"domain_scores_gemma":[0.98808527,0.007191706,0.001350111,0.00064213015,0.0025765686,0.0001542357],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0115430765,0.00023273635,0.0006792863,0.0007624645,0.0002886683,0.0004617581,0.0011620438,0.00018849375,0.00016340564],"category_scores_gemma":[0.007569799,0.00013993074,0.0003093733,0.0007739161,0.00026436197,0.00087152846,0.00032863024,0.0003632797,0.000034817418],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005446819,0.00012889616,0.0114220735,0.0000055187593,0.000008234431,0.000013167078,0.0006819144,0.0005828563,0.00079165446,0.0004938905,0.0028350845,0.982492],"study_design_scores_gemma":[0.0020089105,0.0014631965,0.08489515,0.0010183026,0.00039062093,0.00021615029,0.006675794,0.052951828,0.0005211486,0.8461867,0.0031851623,0.00048706483],"about_ca_topic_score_codex":0.000010408702,"about_ca_topic_score_gemma":0.00008069297,"teacher_disagreement_score":0.98200494,"about_ca_system_score_codex":0.00008815377,"about_ca_system_score_gemma":0.00025463957,"threshold_uncertainty_score":0.90623033},"labels":[],"label_agreement":null},{"id":"W4387898335","doi":"10.1111/caje.12687","title":"Random choice and market demand","year":2023,"lang":"en","type":"article","venue":"Canadian Journal of Economics/Revue canadienne d économique","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Irrational number; Economics; Outcome (game theory); Preference; Rationality; Consumption (sociology); Mathematical economics; Set (abstract data type); Econometrics; Microeconomics; Expected utility hypothesis; Choice set; Revealed preference; Mathematics; Computer science","score_opus":0.28457399598492716,"score_gpt":0.2783140668538818,"score_spread":0.006259929131045339,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387898335","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9916511,0.00021297632,0.00004775304,0.0027600962,0.0024890879,0.00018132511,0.0001704493,0.000012517983,0.0024747013],"genre_scores_gemma":[0.9959205,0.00017081195,0.00028607127,0.00053268106,0.00056458794,0.0000067477868,0.000004827133,0.000044579363,0.0024691878],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9967756,0.00015709961,0.0016578425,0.0005753232,0.000010221326,0.0008238948],"domain_scores_gemma":[0.99326164,0.002336979,0.00094427745,0.00064041815,0.00033306595,0.0024836292],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.005444877,0.00029796394,0.0009341143,0.0019977991,0.00031811243,0.0007559243,0.0011499868,0.00022483175,0.0009990386],"category_scores_gemma":[0.003667203,0.00029474858,0.0003026986,0.00045723707,0.0002574021,0.00078998605,0.000071212045,0.00036314075,0.00022557972],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039884,0.000031596413,0.2081501,0.000032681575,0.00030200815,0.0012050334,0.0031752856,0.016988268,0.000037760372,0.046254557,0.13574915,0.58767474],"study_design_scores_gemma":[0.0020554587,0.00027507634,0.025991239,0.000084241285,0.000055828903,0.00094627007,0.0011015728,0.009058044,0.000024598465,0.6998457,0.25996175,0.00060022617],"about_ca_topic_score_codex":0.032998938,"about_ca_topic_score_gemma":0.9251304,"teacher_disagreement_score":0.8921315,"about_ca_system_score_codex":0.00077337865,"about_ca_system_score_gemma":0.0015937409,"threshold_uncertainty_score":0.99995047},"labels":[],"label_agreement":null},{"id":"W4388070086","doi":"10.3758/s13414-023-02811-4","title":"Correction to: Salience matters: Distractors may, or may not, speed target-absent searches","year":2023,"lang":"en","type":"erratum","venue":"Attention Perception & Psychophysics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Salience (neuroscience); Cognitive psychology; Computer science; Psychology","score_opus":0.17809435624331948,"score_gpt":0.4350421604422192,"score_spread":0.25694780419889973,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388070086","genre_codex":"empirical","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.53594697,0.000016175092,0.009371639,0.016888138,0.4228776,0.001969073,0.0011854726,0.0010886692,0.010656282],"genre_scores_gemma":[0.19429886,0.000288237,0.0010237895,0.0027057587,0.0050300895,0.00008813832,0.0013547974,0.00026307208,0.79494727],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99057704,0.00041761243,0.0021295615,0.0025200704,0.003437561,0.0009181681],"domain_scores_gemma":[0.9944469,0.0009004106,0.0012288966,0.0020264417,0.0008498187,0.0005475857],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002277537,0.00089749787,0.0011354624,0.0011324531,0.00069421204,0.0019658168,0.0019288134,0.00069798675,0.005060914],"category_scores_gemma":[0.00089718524,0.0007440043,0.0010244274,0.002530233,0.00028616755,0.0010845262,0.0004205726,0.0016020995,0.049996186],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018345244,0.00021948849,0.00042728512,0.000018859932,0.000028046055,0.000019114943,0.00046930712,0.00023941044,0.0012247503,0.000008927234,0.83406997,0.16309142],"study_design_scores_gemma":[0.00067594706,0.0005506243,0.15434995,0.00089016045,0.00014108018,0.00004345128,0.0070464914,0.0031466186,0.000026756976,0.005334836,0.8259758,0.0018182884],"about_ca_topic_score_codex":0.00036942726,"about_ca_topic_score_gemma":0.00026249597,"teacher_disagreement_score":0.78429097,"about_ca_system_score_codex":0.0007089553,"about_ca_system_score_gemma":0.0003222498,"threshold_uncertainty_score":0.9995011},"labels":[],"label_agreement":null},{"id":"W4388206746","doi":"10.11606/t.12.2023.tde-23102023-212133","title":"Essays on finance and decision theory","year":2023,"lang":"en","type":"dissertation","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Discovery Air (Canada)","funders":"","keywords":"Advice (programming); Economics; Political science; Positive economics; Computer science","score_opus":0.09943322505724449,"score_gpt":0.42469677009286677,"score_spread":0.32526354503562227,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388206746","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9186235,0.0001385355,0.0002534927,0.000043718406,0.0034538468,0.00016542425,0.00003180856,0.000103242994,0.07718645],"genre_scores_gemma":[0.75321096,0.00055559824,0.0023107391,0.0003459051,0.0002006777,0.00006233651,0.0001180195,0.000109726476,0.24308604],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9965305,0.000084202,0.00089837104,0.0011037125,0.0011163143,0.00026692025],"domain_scores_gemma":[0.9919902,0.0063048867,0.00041376002,0.00096413086,0.00023235874,0.00009463136],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0032525593,0.00032690642,0.00057515973,0.0007019852,0.00023363266,0.0006111076,0.00088246824,0.00042066711,0.0010327736],"category_scores_gemma":[0.0029043872,0.00022317916,0.00019133596,0.0005719071,0.000051556053,0.00017828488,0.000106757645,0.00035128504,0.0069694053],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020887691,0.000029230116,0.00006115489,0.0000020171492,0.000004038587,0.000019633877,0.0001698063,0.00004207068,0.0000058998576,0.01022605,0.03325749,0.95597374],"study_design_scores_gemma":[0.0002082275,0.00011119772,0.007926397,0.0001827498,0.00001725086,0.0000033532722,0.0016593051,0.0002768145,0.00007660864,0.96846074,0.020749068,0.0003282667],"about_ca_topic_score_codex":0.000018299457,"about_ca_topic_score_gemma":0.00035288223,"teacher_disagreement_score":0.9582347,"about_ca_system_score_codex":0.00004057359,"about_ca_system_score_gemma":0.00009308537,"threshold_uncertainty_score":0.99988043},"labels":[],"label_agreement":null},{"id":"W4388632251","doi":"10.3389/fpsyg.2023.1157527","title":"A normative theory of luck","year":2023,"lang":"en","type":"article","venue":"Frontiers in Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of Warwick; York University","keywords":"Luck; Normative; Psychology; Generality; Ambiguity; Heuristics; Cognitive psychology; Quality (philosophy); Social psychology; Cognition; Epistemology; Positive economics; Computer science","score_opus":0.12761496705165554,"score_gpt":0.44197947211023875,"score_spread":0.3143645050585832,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388632251","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.937045,0.0001382113,0.03360458,0.00075046695,0.005522241,0.000114107395,0.000024365698,0.00004288479,0.022758158],"genre_scores_gemma":[0.99003744,0.000057294936,0.008498981,0.0005365448,0.000038429058,0.000012062807,0.0000037088935,0.00001185593,0.0008036653],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99815327,0.00028923803,0.00067928317,0.00037280621,0.00027021277,0.00023517225],"domain_scores_gemma":[0.99854016,0.00051441026,0.0002257667,0.00059751514,0.00007491182,0.000047205678],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0034804079,0.00009265878,0.00036500572,0.0009824578,0.000032402997,0.000022468104,0.00079139543,0.00012644481,0.00028623745],"category_scores_gemma":[0.0010333959,0.00007329388,0.00009730152,0.0013525095,0.0002289392,0.00013654526,0.000102498474,0.00015210481,0.00090680044],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008907555,0.000039986724,0.03664608,5.9339135e-7,0.0000052744012,0.000014265515,0.0008543668,0.000025852023,0.000034418976,0.00052015675,0.21069698,0.75107294],"study_design_scores_gemma":[0.00040064793,0.00006947769,0.04440488,0.0000082489,0.0000031159593,0.000005422461,0.0027197292,0.0004377324,0.000028041866,0.9271331,0.024702512,0.000087083914],"about_ca_topic_score_codex":0.0000025321883,"about_ca_topic_score_gemma":0.0000041445655,"teacher_disagreement_score":0.926613,"about_ca_system_score_codex":0.00002002506,"about_ca_system_score_gemma":0.000024485616,"threshold_uncertainty_score":0.99987113},"labels":[],"label_agreement":null},{"id":"W4388677096","doi":"10.23952/asvao.5.2023.3.02","title":"Superiorization: The asymmetric roles of feasibility-seeking and objective function reduction","year":2023,"lang":"en","type":"article","venue":"Applied Set-Valued Analysis and Optimization","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Israel Science Foundation; National Natural Science Foundation of China","keywords":"Reduction (mathematics); Function (biology); Psychology; Mathematics; Biology; Evolutionary biology","score_opus":0.061918427671709124,"score_gpt":0.33868749447818397,"score_spread":0.27676906680647484,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388677096","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.76925224,0.000079566555,0.22973491,0.00012053419,0.00012462494,0.00021942056,0.0000133822205,0.000046714536,0.00040859086],"genre_scores_gemma":[0.9977414,0.00014937013,0.0018597416,0.000026877471,0.00005339517,0.000013427866,0.00007558606,0.000010428857,0.00006976474],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99795103,0.00011746318,0.0006619464,0.00057301664,0.00054925715,0.00014730514],"domain_scores_gemma":[0.99841434,0.00043285737,0.00038819143,0.0004097973,0.0002976523,0.000057136684],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025399837,0.00014103507,0.00038381675,0.0011818206,0.00042112055,0.00032121138,0.00017219334,0.00010479134,0.000052400763],"category_scores_gemma":[0.00044372198,0.00009886059,0.00011816429,0.007116319,0.00013660271,0.00026729153,0.000107426946,0.00009478636,0.0000100047255],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009737111,0.00003778719,0.016690854,0.000004086697,0.00017143594,3.1582692e-7,0.0013832181,0.7446149,0.00064519234,0.0017595064,0.00010430925,0.23449102],"study_design_scores_gemma":[0.00041580197,0.00007837408,0.06421088,0.0000069864586,0.0008687967,0.0000027513956,0.008107043,0.9073871,0.00029141514,0.018333662,0.0000893273,0.00020788384],"about_ca_topic_score_codex":0.000036531135,"about_ca_topic_score_gemma":0.00003389105,"teacher_disagreement_score":0.23428315,"about_ca_system_score_codex":0.000035027624,"about_ca_system_score_gemma":0.000028326796,"threshold_uncertainty_score":0.4031418},"labels":[],"label_agreement":null},{"id":"W4388734940","doi":"10.3758/s13423-023-02415-x","title":"Rare and extreme outcomes in risky choice","year":2023,"lang":"en","type":"article","venue":"Psychonomic Bulletin & Review","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Economic and Social Research Council","keywords":"Rare events; Psychology; Social psychology; Actuarial science; Economics; Statistics","score_opus":0.23799725236489147,"score_gpt":0.43989843817798496,"score_spread":0.2019011858130935,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388734940","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9320409,0.03223325,0.00001751464,0.028408933,0.0013551248,0.000664763,0.000033950433,0.00012675053,0.0051187896],"genre_scores_gemma":[0.6919936,0.25917885,0.0032167814,0.01902282,0.00044338772,0.00039967883,0.000033061187,0.00016696741,0.025544861],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9968797,0.00021445463,0.0013158742,0.0008680892,0.00035419266,0.00036768336],"domain_scores_gemma":[0.9965493,0.0019010274,0.00035168728,0.0009810762,0.000061733816,0.00015513753],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.004091242,0.00024821103,0.0008908713,0.00033806585,0.00009316404,0.00021040035,0.0008511825,0.00009019938,0.0032086992],"category_scores_gemma":[0.0023901095,0.00018568162,0.00021415352,0.0007052801,0.00007916354,0.0001040339,0.00023293988,0.00023004712,0.017368259],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000057162747,0.00003487142,0.06070159,0.00004091969,0.0000041425856,0.000009522649,0.000028342378,0.0000045340853,0.0000039475485,0.000034908957,0.22108193,0.7180496],"study_design_scores_gemma":[0.00035833372,0.00001923058,0.09785383,0.00064447307,0.000014339245,0.000009421825,0.00004203404,0.000038392136,6.647264e-7,0.0044688717,0.8963295,0.00022086229],"about_ca_topic_score_codex":0.00007382186,"about_ca_topic_score_gemma":0.00006586011,"teacher_disagreement_score":0.71782875,"about_ca_system_score_codex":0.000049212722,"about_ca_system_score_gemma":0.000029267281,"threshold_uncertainty_score":0.9977025},"labels":[],"label_agreement":null},{"id":"W4388962153","doi":"10.1007/978-3-031-44742-6_1","title":"Foundations of Decision","year":2023,"lang":"en","type":"book-chapter","venue":"Studies in computational intelligence","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Artificial intelligence","score_opus":0.587676120652198,"score_gpt":0.5460224639360919,"score_spread":0.0416536567161061,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388962153","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012386807,0.004998475,0.32929957,0.0015387931,0.021028928,0.0017243917,0.0009230019,0.00030737979,0.62779266],"genre_scores_gemma":[0.5496997,0.0034259132,0.058406774,0.00031512513,0.0005120877,0.000055709304,0.000117145406,0.00018708652,0.3872804],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9953955,0.000036579837,0.0021235314,0.00076220866,0.0014900356,0.0001921493],"domain_scores_gemma":[0.9809936,0.016121974,0.0007955717,0.00054522214,0.0014889787,0.00005464525],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002102268,0.00029343902,0.00080871384,0.0011362062,0.00013534786,0.0000818695,0.0010213273,0.00018691871,0.00046078305],"category_scores_gemma":[0.004770217,0.00024917198,0.00027827255,0.00041586105,0.00066153705,0.0001548179,0.0006662795,0.00032113597,0.0027824736],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023062945,0.000024980944,0.00006656759,0.000008432952,0.000044959834,0.00003647639,0.00041945846,0.13666892,1.6605591e-7,0.23150939,0.0052743,0.6259233],"study_design_scores_gemma":[0.000046514575,0.000059098376,0.000115400675,0.0004409841,0.000015013838,0.000008622011,0.0004641903,0.005083321,0.0000029841922,0.9816378,0.011906198,0.00021986722],"about_ca_topic_score_codex":0.00000847055,"about_ca_topic_score_gemma":0.00016534582,"teacher_disagreement_score":0.7501284,"about_ca_system_score_codex":0.00018105764,"about_ca_system_score_gemma":0.00018667622,"threshold_uncertainty_score":0.99999607},"labels":[],"label_agreement":null},{"id":"W4389065490","doi":"10.2139/ssrn.4616130","title":"Non-parametric Identification of Posterior and Reasoning Errors in Isolated and Social Environments","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Identification (biology); Parametric statistics; Computer science; Artificial intelligence; Data science; Cognitive psychology; Psychology; Mathematics; Statistics; Biology; Ecology","score_opus":0.03789352240665748,"score_gpt":0.34624339101094215,"score_spread":0.30834986860428465,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389065490","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99888855,0.00018955345,0.00046048532,0.00025717635,0.00011057986,0.000068850444,0.00000298291,0.0000056837807,0.000016155273],"genre_scores_gemma":[0.9992706,0.00038950163,0.000023016233,0.000016140264,0.000021300593,0.0000014353413,0.0000013331139,0.000009013226,0.00026763038],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9979995,0.00007446891,0.0006823023,0.00025838183,0.00036048915,0.00062484946],"domain_scores_gemma":[0.9992128,0.00016703318,0.00042477364,0.000121738965,0.000033286455,0.00004035928],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0050859195,0.00009024067,0.00022528213,0.000744163,0.00015126732,0.0001447914,0.00023677906,0.0000786288,0.000008758562],"category_scores_gemma":[0.00033986144,0.00007722803,0.00004832953,0.00076664356,0.00006764149,0.0002872802,0.00009271412,0.00048194558,0.0000397548],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011940562,0.00006480649,0.11326756,0.0000023807067,0.000026621266,0.000009082402,0.0012401756,0.00014130212,0.009208989,0.00054630736,0.00004658888,0.87532675],"study_design_scores_gemma":[0.0014215123,0.00041340353,0.61649024,0.00003442907,0.000037104295,0.00028079338,0.009355069,0.011962103,0.00031752462,0.35906368,0.0003313041,0.00029281294],"about_ca_topic_score_codex":0.000023506143,"about_ca_topic_score_gemma":0.00009466605,"teacher_disagreement_score":0.875034,"about_ca_system_score_codex":0.00014871635,"about_ca_system_score_gemma":0.0001723932,"threshold_uncertainty_score":0.31492677},"labels":[],"label_agreement":null},{"id":"W4389377762","doi":"10.1038/s41539-023-00206-6","title":"Deliberately making miskates: Behavioural consistency under win maximization and loss maximization conditions","year":2023,"lang":"en","type":"article","venue":"npj Science of Learning","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; University of Alberta","keywords":"Maximization; Consistency (knowledge bases); Computer science; Psychology; Cognitive psychology; Social psychology; Artificial intelligence","score_opus":0.17320499995748728,"score_gpt":0.41501985533792835,"score_spread":0.24181485538044106,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389377762","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9933917,0.00003416827,0.004134858,0.0005040216,0.0003747696,0.00012857831,0.000011441329,0.00010985418,0.0013105874],"genre_scores_gemma":[0.9969556,0.000030639665,0.002105883,0.00006120174,0.000019708106,0.0000056567314,0.000014086769,0.000014891929,0.00079237326],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.996952,0.00013015064,0.0007682776,0.0006788095,0.0010892965,0.00038149222],"domain_scores_gemma":[0.99763507,0.0006586446,0.00050610135,0.00036386691,0.0007087854,0.00012750778],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036008381,0.000155901,0.00028573518,0.00097280176,0.00095453404,0.0008850882,0.00063296803,0.00008973876,0.00023046353],"category_scores_gemma":[0.0029885059,0.00013690878,0.000071996816,0.0030100087,0.0009718563,0.001887862,0.00026830047,0.00020415528,0.00015663754],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000049831928,0.00011835494,0.4478635,0.000013370153,0.0000115206485,0.000049131355,0.003306576,0.27308145,0.012573319,0.009771372,0.00057499245,0.2525866],"study_design_scores_gemma":[0.0011778696,0.0003485198,0.59362155,0.00030547977,0.000077554,0.00017875913,0.020066135,0.26456538,0.002143637,0.11545972,0.0011459853,0.0009094054],"about_ca_topic_score_codex":0.000024580437,"about_ca_topic_score_gemma":0.000017236476,"teacher_disagreement_score":0.2516772,"about_ca_system_score_codex":0.0000713421,"about_ca_system_score_gemma":0.0002422078,"threshold_uncertainty_score":0.85349256},"labels":[],"label_agreement":null},{"id":"W4389545912","doi":"10.1038/s41598-023-49148-4","title":"Delay discounting and family history of psychopathology in children ages 9–11","year":2023,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"The Scarborough Hospital; University of Toronto; Centre for Addiction and Mental Health","funders":"National Institute on Drug Abuse; Canadian Institutes of Health Research; Department of Psychiatry, University of Toronto; National Institutes of Health; National Institute of Mental Health; University of Toronto","keywords":"Delay discounting; Psychopathology; Discounting; Mania; Psychology; Family history; Schizophrenia (object-oriented programming); Clinical psychology; Bipolar disorder; Psychiatry; Developmental psychology; Impulsivity; Cognition; Medicine","score_opus":0.08593281216593533,"score_gpt":0.3639055371786013,"score_spread":0.27797272501266596,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389545912","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99031806,0.0003138904,0.000026154796,0.000064490356,0.007964585,0.00012707559,0.0000038715357,0.000036274523,0.0011455716],"genre_scores_gemma":[0.99470586,0.00000950031,0.00025013028,0.000023723405,0.000024943789,0.000005563426,0.000009717988,0.000009146109,0.0049614045],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9968602,0.00008208359,0.0011161182,0.00097944,0.0006940615,0.00026811037],"domain_scores_gemma":[0.9980246,0.00023742966,0.0005843957,0.00094825355,0.00013260965,0.00007274932],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009007839,0.00011171661,0.00031824713,0.000975833,0.000092381735,0.00018795981,0.00032750075,0.00007791022,0.00006596753],"category_scores_gemma":[0.001291746,0.00008863485,0.00008406058,0.0009939338,0.0004995538,0.00030369108,0.00022463762,0.00009777595,0.00007757616],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003854778,0.0000401432,0.82197255,0.0000014962465,0.000001793222,0.00028054274,0.00067951455,0.00010928026,0.0043860315,0.00003038594,0.044705912,0.12778848],"study_design_scores_gemma":[0.00016704737,0.00002560683,0.87144864,0.000044616878,0.000008942613,0.00042331274,0.0004711127,0.00040785648,0.0001121814,0.084787644,0.041886616,0.00021643244],"about_ca_topic_score_codex":0.00011233925,"about_ca_topic_score_gemma":0.00012367227,"teacher_disagreement_score":0.12757206,"about_ca_system_score_codex":0.0000727423,"about_ca_system_score_gemma":0.00013865331,"threshold_uncertainty_score":0.36144242},"labels":[],"label_agreement":null},{"id":"W4389765398","doi":"10.21203/rs.3.rs-3745806/v1","title":"Semi-Supervised Machine Learning Method for Predicting Observed Individual Risk Preference Using Gallup Data","year":2023,"lang":"en","type":"preprint","venue":"Research Square","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Preference; Random forest; Ordinary least squares; Regression; Index (typography); Covariate; Econometrics; Machine learning; Computer science; Actuarial science; Psychology; Artificial intelligence; Statistics; Economics; Mathematics","score_opus":0.8533571027901891,"score_gpt":0.5883198959953995,"score_spread":0.2650372067947896,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389765398","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.881744,0.0006869998,0.09841332,0.00038053186,0.0015470831,0.0026561148,0.013976763,0.00042547638,0.00016970016],"genre_scores_gemma":[0.792019,0.0005333102,0.19887125,0.00002848864,0.0011656721,0.00034396362,0.004701891,0.00030398197,0.0020324455],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.98257947,0.0047689457,0.0020974725,0.0037472912,0.0053040413,0.0015027773],"domain_scores_gemma":[0.9638695,0.027040772,0.001115223,0.005180681,0.0022702964,0.00052351475],"candidate_categories":["metaresearch","metaepi_narrow","sts","scholarly_communication","open_science","research_integrity"],"consensus_categories":["metaresearch","open_science"],"category_scores_codex":[0.07505258,0.00060158985,0.0012820023,0.0016840465,0.0016750874,0.0036427018,0.009661403,0.00087840366,0.00034625124],"category_scores_gemma":[0.089039795,0.0005063171,0.00045460428,0.0017066471,0.00021892827,0.0007245854,0.02240996,0.0051741824,0.0002821638],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003307124,0.00021669938,0.1890742,0.00034411802,0.00021245344,0.000053394746,0.0019748064,0.08112511,0.00024052043,0.00003411998,0.0054804757,0.7209134],"study_design_scores_gemma":[0.0006498086,0.00022195926,0.011596573,0.0009455599,0.00011335702,0.0000067143515,0.00238897,0.9288682,0.000054928205,0.048321318,0.006285763,0.0005468647],"about_ca_topic_score_codex":0.0044110636,"about_ca_topic_score_gemma":0.001430813,"teacher_disagreement_score":0.8477431,"about_ca_system_score_codex":0.0003514198,"about_ca_system_score_gemma":0.0014192916,"threshold_uncertainty_score":0.9997389},"labels":[],"label_agreement":null},{"id":"W4389841248","doi":"10.5267/j.dsl.2023.11.003","title":"Analyzing the interrelations among investors’ behavioral biases using an integrated DANP method","year":2023,"lang":"en","type":"article","venue":"Decision Science Letters","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Loss aversion; Overconfidence effect; Regret; Anchoring; Preference; Econometrics; Herd behavior; Behavioral economics; Prospect theory; Psychology; Risk aversion (psychology); Disposition effect; Risk-seeking; Proxy (statistics); Ambiguity; Economics; Microeconomics; Social psychology; Expected utility hypothesis; Statistics; Computer science; Mathematics; Herding; Financial economics","score_opus":0.397188947689401,"score_gpt":0.5075228894466369,"score_spread":0.11033394175723593,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389841248","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.83029354,0.000008512039,0.16649556,0.00096917,0.0017775928,0.00021143448,0.000022821207,0.00016931297,0.00005206662],"genre_scores_gemma":[0.9665573,0.0000028785828,0.032314856,0.0008912845,0.000104626684,0.000012958282,0.000010081152,0.000029860486,0.00007615135],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9931212,0.0005392334,0.001460378,0.0015275324,0.0025561398,0.0007954833],"domain_scores_gemma":[0.9911683,0.005120176,0.00060985895,0.0021323783,0.00052264496,0.000446615],"candidate_categories":["metaresearch","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.017478684,0.00034255223,0.0004826799,0.0029961795,0.0019395682,0.003121266,0.004306189,0.00012529062,0.00025609575],"category_scores_gemma":[0.008992063,0.00020994886,0.0002953688,0.012920564,0.0017001355,0.0035360113,0.0008846008,0.0005301195,0.0005947207],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023807781,0.00009362064,0.06312701,2.8969077e-7,0.0000056868594,0.000056556404,0.0020230964,0.059243403,0.018692104,0.00009306845,0.0069973734,0.849644],"study_design_scores_gemma":[0.0005607903,0.00018143897,0.17541413,0.00019249698,0.00009627814,0.000099080586,0.016353138,0.77305204,0.0017837087,0.023751445,0.0074774586,0.0010379695],"about_ca_topic_score_codex":0.00051599357,"about_ca_topic_score_gemma":0.00026362567,"teacher_disagreement_score":0.848606,"about_ca_system_score_codex":0.00029001827,"about_ca_system_score_gemma":0.0002536463,"threshold_uncertainty_score":0.9993598},"labels":[],"label_agreement":null},{"id":"W4390265114","doi":"10.1007/978-3-031-50628-4_1","title":"Conversational Reasoning in the Absence of Quantity","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Maxim; Grice; Implicature; Computer science; Numeral system; Meaning (existential); Scalar (mathematics); Context (archaeology); Utterance; Linguistics; Cooperative principle; Pragmatics; Artificial intelligence; Natural language processing; Epistemology; Mathematics; Philosophy","score_opus":0.12369875095763073,"score_gpt":0.3700944025334291,"score_spread":0.2463956515757984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390265114","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13738063,0.00014550178,0.84970754,0.0013167633,0.0044935574,0.00053627073,0.000051308994,0.000058814094,0.006309623],"genre_scores_gemma":[0.9822182,0.000016967851,0.016903631,0.00044607988,0.00014154783,0.0000026616722,0.0000028185118,0.000014030336,0.00025404466],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99584574,0.00006688859,0.0008904945,0.0009449522,0.001953656,0.0002982894],"domain_scores_gemma":[0.9929646,0.0051677204,0.0005051154,0.0010147311,0.00029716681,0.0000506649],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006949918,0.00022828078,0.00045686364,0.0009660292,0.00013481706,0.0003815521,0.0031439564,0.00019414254,0.00008437096],"category_scores_gemma":[0.002203922,0.00015138875,0.00013271726,0.0010454053,0.0009146334,0.00029645508,0.00053179875,0.0005584184,0.00018860924],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014010635,0.00002823761,0.007019549,0.0000056243575,0.000002694513,0.00007277378,0.0015510176,0.04127976,0.000027439313,0.018668575,0.00012252551,0.9312078],"study_design_scores_gemma":[0.00016302853,0.000078087025,0.013249901,0.00032589096,0.0000035232,0.000026339227,0.0000075424337,0.10059639,0.00005791781,0.88439775,0.0007936181,0.00030000758],"about_ca_topic_score_codex":0.00010324012,"about_ca_topic_score_gemma":0.0006596224,"teacher_disagreement_score":0.9309078,"about_ca_system_score_codex":0.000112007154,"about_ca_system_score_gemma":0.00042511796,"threshold_uncertainty_score":0.61734545},"labels":[],"label_agreement":null},{"id":"W4390515501","doi":"10.2196/48954","title":"Designing and Validating a Novel Method for Assessing Delay Discounting Associated With Health Behaviors: Ecological Momentary Assessment Study","year":2024,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Drug Abuse","keywords":"Delay discounting; Ecology; Discounting; Psychology; Biology; Developmental psychology","score_opus":0.38170836331185615,"score_gpt":0.6155761447913838,"score_spread":0.23386778147952764,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390515501","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7764518,0.000033870805,0.22121297,0.0004929077,0.0001577918,0.0013651651,0.00006110292,0.00006488243,0.00015946338],"genre_scores_gemma":[0.93386877,0.0000017413904,0.065433905,0.00004990952,0.000046811863,0.00048269564,0.00002204424,0.000030591353,0.00006352927],"study_design_codex":"design_other","study_design_gemma":"qualitative","domain_scores_codex":[0.99380356,0.0013879263,0.0011076824,0.00087418495,0.0019906561,0.00083597895],"domain_scores_gemma":[0.9847203,0.013777385,0.00035100375,0.00032810276,0.00060330157,0.00021990122],"candidate_categories":["metaresearch","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.04011176,0.00024736766,0.00058723334,0.0008183364,0.0014528158,0.004022924,0.0005383088,0.00010043312,0.000052896965],"category_scores_gemma":[0.0012625164,0.000157592,0.00010295436,0.0013905859,0.00016203344,0.0019585388,0.0005378578,0.00087196,0.000011728851],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009749082,0.0031369173,0.036874264,0.00007382518,0.0001840315,0.000098740995,0.033849597,0.00041030804,0.0019848617,0.00054232514,0.0023103778,0.9204373],"study_design_scores_gemma":[0.004143235,0.010506859,0.24114291,0.0019540277,0.00011552215,0.00016505462,0.36150134,0.3600925,0.00028489216,0.017846333,0.0010399516,0.001207389],"about_ca_topic_score_codex":0.000095847456,"about_ca_topic_score_gemma":0.00009421395,"teacher_disagreement_score":0.91922987,"about_ca_system_score_codex":0.00084054837,"about_ca_system_score_gemma":0.00059983676,"threshold_uncertainty_score":0.9998472},"labels":[],"label_agreement":null},{"id":"W4391313134","doi":"10.3758/s13423-024-02461-z","title":"The effects of strength and activation level of belief on belief-biased reasoning","year":2024,"lang":"en","type":"article","venue":"Psychonomic Bulletin & Review","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Psychology; Affect (linguistics); Confirmation bias; Context (archaeology); Cognition; Cognitive bias; Social psychology; Cognitive psychology; Response bias; Attentional bias; Communication","score_opus":0.12368005995967443,"score_gpt":0.40447067623327015,"score_spread":0.2807906162735957,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391313134","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8746013,0.1114685,0.0003109551,0.0070999456,0.0020525928,0.0009728057,0.000049834038,0.000044016386,0.0034000564],"genre_scores_gemma":[0.93401545,0.06271824,0.0012750643,0.0006757244,0.00011392872,0.00004575645,0.0000045148895,0.00003216003,0.0011191294],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99775016,0.00020356651,0.0010200646,0.00049735914,0.00035966627,0.00016919644],"domain_scores_gemma":[0.9924972,0.0061676293,0.00046563864,0.00070679083,0.00009643482,0.00006627755],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029391584,0.00017670267,0.00052194495,0.00012507134,0.000108225024,0.0001378856,0.0005028045,0.00006506621,0.00021280897],"category_scores_gemma":[0.0030358233,0.00010771289,0.00019692528,0.00029481537,0.00011843081,0.000061716826,0.000079293255,0.00018635918,0.00027242643],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002484328,0.00005064877,0.00006149311,0.00031417634,0.000016551661,8.803723e-7,0.00004696711,0.0000028143631,0.00022917129,0.0010211387,0.053782403,0.9444489],"study_design_scores_gemma":[0.00033859027,0.00028896332,0.0024345997,0.01556489,0.0000772126,0.000007359509,0.000053849086,0.00011631233,0.0013812898,0.0051966826,0.97433263,0.00020760267],"about_ca_topic_score_codex":0.000027330432,"about_ca_topic_score_gemma":0.0000039875154,"teacher_disagreement_score":0.9442413,"about_ca_system_score_codex":0.000036639165,"about_ca_system_score_gemma":0.000050939707,"threshold_uncertainty_score":0.43924043},"labels":[],"label_agreement":null},{"id":"W4391597751","doi":"10.3390/jrfm17020065","title":"Illusion of Control: Psychological Characteristics as Moderators in Financial Decision Making","year":2024,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Illusion of control; Illusion; Lottery; Control (management); Context (archaeology); Social psychology; Event (particle physics); Psychology; Decision-making; Process (computing); Cognitive psychology; Marketing; Computer science; Economics; Business; Management; Microeconomics","score_opus":0.033270325806179155,"score_gpt":0.3640292075294598,"score_spread":0.3307588817232806,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391597751","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91943425,0.00058808096,0.07773513,0.00006551246,0.0017547659,0.00011372991,0.000023575552,0.0000066136704,0.00027835157],"genre_scores_gemma":[0.99539316,0.0012078233,0.0030457948,0.00013061607,0.00019037396,0.0000016279779,2.856663e-7,0.000008740326,0.000021584989],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.997102,0.000104406485,0.0015345091,0.00033604706,0.0007251278,0.00019787918],"domain_scores_gemma":[0.9981402,0.0008120382,0.0005796036,0.00022323268,0.00016846045,0.000076451026],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034268696,0.00016026017,0.00057514064,0.00085152575,0.00009307278,0.00023629403,0.00041049338,0.00013815725,0.000066478184],"category_scores_gemma":[0.0021276332,0.00010951264,0.00021255553,0.00056274084,0.00007773667,0.00028439492,0.00016547582,0.0003604707,0.000029084818],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005909228,0.00012499679,0.007821978,0.0000076163037,0.0000034907057,0.000456329,0.00023856375,0.00021411268,0.0000113266915,0.0027286508,0.000645726,0.9871563],"study_design_scores_gemma":[0.0012813229,0.00064741616,0.52149767,0.00082932203,0.0000774762,0.00008915853,0.00018825622,0.0023942017,0.0000052632813,0.43527582,0.037489854,0.00022427233],"about_ca_topic_score_codex":0.0000057012808,"about_ca_topic_score_gemma":0.000013327495,"teacher_disagreement_score":0.98693204,"about_ca_system_score_codex":0.000055441145,"about_ca_system_score_gemma":0.000049523755,"threshold_uncertainty_score":0.4465796},"labels":[],"label_agreement":null},{"id":"W4391610744","doi":"10.1080/20445911.2024.2313566","title":"Reasoning strategy moderates the transition between slow and fast reasoning","year":2024,"lang":"en","type":"article","venue":"Journal of Cognitive Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Counterexample; Set (abstract data type); Psychology; Constraint (computer-aided design); Cognitive psychology; Logical reasoning; Limit (mathematics); Computer science; Artificial intelligence; Mathematics; Discrete mathematics","score_opus":0.13382975763191107,"score_gpt":0.45783166339474024,"score_spread":0.32400190576282917,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391610744","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94829047,0.001507419,0.043773692,0.002283756,0.00067031535,0.00009075824,0.00002821122,0.000013351937,0.0033420522],"genre_scores_gemma":[0.99845475,0.00013491079,0.0004486253,0.00040888018,0.00044256804,0.000002528489,0.0000018575431,0.0000140500515,0.00009181688],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99790144,0.00033653388,0.0008075655,0.00032492625,0.00040482602,0.00022473389],"domain_scores_gemma":[0.9959098,0.003040174,0.00033638978,0.00014154786,0.0004564792,0.00011562824],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003730059,0.00014423861,0.00036989342,0.00034792468,0.00017593622,0.0006452612,0.00030952532,0.00012188399,0.00014591553],"category_scores_gemma":[0.0010260057,0.00008459566,0.00016114254,0.00035690915,0.00021268282,0.00052531675,0.000030395036,0.0005517757,0.00007098381],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012524481,0.00002723272,0.0015799211,0.000001348855,0.000057217807,0.00012450606,0.0014839214,0.000079661484,0.00015870231,0.00027424068,0.0015111379,0.9945769],"study_design_scores_gemma":[0.0029168949,0.0030819476,0.20492175,0.0022701463,0.0007312517,0.006698308,0.019238738,0.013562932,0.0005318682,0.73375696,0.0114790825,0.0008101046],"about_ca_topic_score_codex":0.000003377012,"about_ca_topic_score_gemma":0.0000047057247,"teacher_disagreement_score":0.9937668,"about_ca_system_score_codex":0.000020813159,"about_ca_system_score_gemma":0.0000836794,"threshold_uncertainty_score":0.62222683},"labels":[],"label_agreement":null},{"id":"W4391765618","doi":"10.1016/j.cognition.2024.105742","title":"Distinguishing between intrinsic and instrumental sources of the value of choice","year":2024,"lang":"en","type":"article","venue":"Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Royal Society; UK Research and Innovation; Natural Sciences and Engineering Research Council of Canada; Wellcome Trust","keywords":"Psychology; Preference; Operationalization; Value (mathematics); Freedom of choice; Contingency; Intrinsic value (animal ethics); Social psychology; Task (project management); Cognitive psychology; Microeconomics; Economics; Statistics; Epistemology","score_opus":0.10496555205710945,"score_gpt":0.3802426852229569,"score_spread":0.27527713316584745,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391765618","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9973652,0.00011869129,0.00008671613,0.000120995945,0.00030104726,0.00006462759,0.000056258796,0.000012506577,0.0018739945],"genre_scores_gemma":[0.999739,0.000003936325,0.00013165048,0.000017514229,0.00006346931,0.0000011327677,0.000002791123,0.0000045007773,0.000035991463],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99903697,0.000052658634,0.00036484408,0.0001811028,0.00029970627,0.00006470374],"domain_scores_gemma":[0.99848795,0.0011249363,0.00014561144,0.00014244243,0.00007439861,0.000024642415],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00071188057,0.00005554266,0.00013824337,0.000099288816,0.00006572733,0.0001440624,0.00020180579,0.000038143753,0.00003396497],"category_scores_gemma":[0.0014234215,0.000034833796,0.00006311084,0.00027901772,0.00013667432,0.00017477757,0.00014918351,0.00008333171,0.000014351677],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003317456,0.000010956855,0.10524465,0.0000112772095,0.0000063796538,6.718166e-7,0.00028694462,0.0000029512419,0.0004125264,0.00024325706,0.00008977725,0.8936873],"study_design_scores_gemma":[0.00028501937,0.00009223318,0.7695783,0.0005881271,0.000121620804,0.000014551563,0.0010841554,0.0006989173,0.018392371,0.20463964,0.0043577,0.00014738408],"about_ca_topic_score_codex":0.0000243539,"about_ca_topic_score_gemma":0.0000105632025,"teacher_disagreement_score":0.8935399,"about_ca_system_score_codex":0.000011408892,"about_ca_system_score_gemma":0.000024403493,"threshold_uncertainty_score":0.17040713},"labels":[],"label_agreement":null},{"id":"W4391824529","doi":"10.48152/ssrp-37z6-xr67","title":"Reproduction of 'The impact of past behaviour normality on regret: replication and extension of three experiments of the exceptionality effect'","year":2024,"lang":"en","type":"report","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Regret; Normality; Reproduction; Replication (statistics); Extension (predicate logic); Statistics; Econometrics; Mathematics; Computer science; Biology; Genetics","score_opus":0.24066814752282337,"score_gpt":0.48425241449171635,"score_spread":0.243584266968893,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391824529","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9954264,0.0002511862,0.00003111094,0.00011669395,0.0012042233,0.0006952403,0.0002277959,0.00001077769,0.0020365478],"genre_scores_gemma":[0.998863,0.000043402317,0.000072392104,0.0000036312256,0.0000832242,0.000013939602,0.000011814676,0.00001907343,0.00088955567],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99385816,0.00034402523,0.002200438,0.0011625905,0.0022989,0.00013589766],"domain_scores_gemma":[0.98987764,0.0005490183,0.003288587,0.0046600914,0.0015759408,0.00004873766],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010402321,0.00027949773,0.0009357276,0.00024149628,0.00007275089,0.000035194385,0.0007811263,0.00031060475,0.00014335384],"category_scores_gemma":[0.0038828668,0.00012972199,0.00085425837,0.0006397386,0.0004528332,0.00013143818,0.0005426818,0.0003119512,0.000005011077],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003097016,0.0005348562,0.744272,0.00014193394,0.00008791599,8.2924885e-7,0.00019632066,0.00020127886,0.022806786,0.00010005989,0.009638783,0.22170952],"study_design_scores_gemma":[0.00015081797,0.00035670813,0.9443809,0.0005407013,0.00012580134,0.000031006362,0.0000542958,0.000039791754,0.046506457,0.0075668716,0.00012007416,0.00012661498],"about_ca_topic_score_codex":0.0025524683,"about_ca_topic_score_gemma":0.000070728805,"teacher_disagreement_score":0.2215829,"about_ca_system_score_codex":0.00022276094,"about_ca_system_score_gemma":0.0003989434,"threshold_uncertainty_score":0.5289909},"labels":[],"label_agreement":null},{"id":"W4392050192","doi":"10.3390/jintelligence12030025","title":"Are There Two Kinds of Reasoners?","year":2024,"lang":"en","type":"article","venue":"Journal of Intelligence","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Counterexample; Probabilistic logic; Variety (cybernetics); Construct (python library); Cognition; Psychology; Inference; Proposition; Cognitive psychology; Computer science; Contingency; Statistical model; Artificial intelligence; Mathematics","score_opus":0.22002803998214437,"score_gpt":0.47149300993891524,"score_spread":0.25146496995677087,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392050192","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9743532,0.0023985005,0.01737542,0.0005817873,0.001982954,0.00003397192,0.000009769622,0.000010041744,0.00325435],"genre_scores_gemma":[0.99718785,0.00013882319,0.0018238743,0.00008218262,0.00018913146,3.037492e-7,6.962348e-8,0.000009789529,0.0005679519],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99741465,0.00007852723,0.0012740556,0.0002075688,0.00088312937,0.00014208897],"domain_scores_gemma":[0.99657303,0.0013088755,0.001020271,0.00035334576,0.0006347676,0.000109700595],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003150592,0.00011059231,0.00037743393,0.00042435457,0.000036507583,0.000282988,0.0010335032,0.00006207461,0.0010242015],"category_scores_gemma":[0.0021854525,0.000067421235,0.00033250774,0.00063779874,0.00010814993,0.000417298,0.00008532074,0.00030673796,0.00036290425],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000048614627,0.000060353712,0.0037103554,0.000005572901,0.000021585809,0.00034306952,0.00034052908,0.0012548432,0.00049978885,0.0012399434,0.0073820776,0.98509324],"study_design_scores_gemma":[0.00023674985,0.0008330027,0.008746838,0.0025288088,0.00013043902,0.0017267285,0.012699724,0.00985589,0.035160687,0.79252446,0.13498984,0.00056682416],"about_ca_topic_score_codex":0.000011011325,"about_ca_topic_score_gemma":0.000015270449,"teacher_disagreement_score":0.98452646,"about_ca_system_score_codex":0.000051025225,"about_ca_system_score_gemma":0.00012565409,"threshold_uncertainty_score":0.999889},"labels":[],"label_agreement":null},{"id":"W4392082513","doi":"10.1007/978-3-031-50947-6_1","title":"Consumer Decision-Making Strategies","year":2024,"lang":"en","type":"book-chapter","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Business; Computer science","score_opus":0.1257670528963534,"score_gpt":0.4126132145957136,"score_spread":0.28684616169936017,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392082513","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001738933,0.0019683505,0.0025793507,0.00018074687,0.004371224,0.00025044254,0.00014698338,0.0002929344,0.98847103],"genre_scores_gemma":[0.09794965,0.00016873957,0.004163386,0.000351985,0.00037522713,0.000006886896,0.000008504405,0.00014479594,0.89683086],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99361104,0.000021110849,0.0020593975,0.0017800492,0.0020795858,0.00044883534],"domain_scores_gemma":[0.991692,0.0050699604,0.00056252367,0.0019488797,0.0005138399,0.00021278838],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0019840142,0.00073017273,0.0011458739,0.0012565365,0.00020913439,0.0038422588,0.0019430643,0.00079549354,0.03687914],"category_scores_gemma":[0.000713094,0.0005038846,0.00083106017,0.00018309109,0.00032969762,0.00057235174,0.00084619917,0.00089032506,0.075179085],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001919606,0.000008207299,0.000006447954,0.000003292148,0.00003113786,0.00018761017,0.000032787004,0.000044032444,0.0000012740531,0.3199674,0.08468618,0.5950124],"study_design_scores_gemma":[0.000047074274,0.000027352404,0.000004523961,0.00030778072,0.0000498389,0.00004539062,0.00015025516,0.00014535968,6.471053e-7,0.5298752,0.46898997,0.0003565844],"about_ca_topic_score_codex":0.000007976282,"about_ca_topic_score_gemma":0.00018979514,"teacher_disagreement_score":0.5946559,"about_ca_system_score_codex":0.00015667574,"about_ca_system_score_gemma":0.00046467493,"threshold_uncertainty_score":0.99974126},"labels":[],"label_agreement":null},{"id":"W4392562007","doi":"10.1037/cbs0000410","title":"Delay discounting in individuals with anxiety and related disorders compared to healthy controls.","year":2024,"lang":"en","type":"article","venue":"Canadian Journal of Behavioural Science/Revue canadienne des sciences du comportement","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Drug Abuse","keywords":"Psychology; Anxiety; Delay discounting; Clinical psychology; Discounting; Developmental psychology; Psychiatry; Impulsivity","score_opus":0.10574717252733956,"score_gpt":0.3289289665401412,"score_spread":0.22318179401280164,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392562007","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99216163,0.00055177195,0.00013523031,0.004535253,0.0015463672,0.0003695555,0.00005044085,0.000011955397,0.000637816],"genre_scores_gemma":[0.9978731,0.000019662255,0.0017686991,0.00022529408,0.000044965058,0.000008399612,0.0000015750169,0.000014213229,0.00004405888],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9951347,0.00012502103,0.0016435771,0.000924206,0.0008625394,0.0013099414],"domain_scores_gemma":[0.9958441,0.00032862384,0.0005155033,0.00033876163,0.00047139465,0.0025016172],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":["sts"],"category_scores_codex":[0.013928063,0.00029479488,0.0006099081,0.003113012,0.0013670624,0.0023769045,0.0019201094,0.000068254085,0.00019176159],"category_scores_gemma":[0.00063272036,0.00021147178,0.00011902916,0.0050088093,0.0032856923,0.0019354383,0.00011622124,0.00038838497,0.00001421918],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010586913,0.000027466884,0.90905875,0.0000044850585,0.000007769873,0.00032062278,0.005381319,0.0029109223,0.000046150166,0.0012249328,0.00021406049,0.08079294],"study_design_scores_gemma":[0.0011127433,0.0016224579,0.92931443,0.0008001822,0.00007395709,0.0030429082,0.012714337,0.011530368,0.000014177147,0.025615757,0.013343668,0.00081502425],"about_ca_topic_score_codex":0.05341316,"about_ca_topic_score_gemma":0.7304072,"teacher_disagreement_score":0.676994,"about_ca_system_score_codex":0.0018601232,"about_ca_system_score_gemma":0.0039188256,"threshold_uncertainty_score":0.999933},"labels":[],"label_agreement":null},{"id":"W4392730158","doi":"10.48152/ssrp-1yg9-0z41","title":"Reproduction of 'Agency Beliefs Over Time and Across Cultures: Free Will Beliefs Predict Higher Job Satisfaction'","year":2024,"lang":"en","type":"report","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Agency (philosophy); Job satisfaction; Reproduction; Social psychology; Psychology; Job attitude; Demographic economics; Job performance; Economics; Sociology; Biology; Ecology; Social science","score_opus":0.08711710148123276,"score_gpt":0.41717115684411543,"score_spread":0.3300540553628827,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392730158","genre_codex":"empirical","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89505976,0.0063539473,0.00006925145,0.0008475649,0.014053804,0.000701619,0.0021304972,0.00033048476,0.08045306],"genre_scores_gemma":[0.2835682,0.0040253354,0.0017225179,0.00014155905,0.003618822,0.000052810552,0.00012817622,0.00020227046,0.7065403],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9914174,0.000117626914,0.002396897,0.0024058893,0.003204629,0.0004575794],"domain_scores_gemma":[0.993915,0.00051796995,0.0011687161,0.0029412697,0.0012396533,0.00021738937],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0052294396,0.0005941198,0.0012528638,0.00048479546,0.00023966262,0.0007785669,0.0009646515,0.00090077316,0.006182803],"category_scores_gemma":[0.0033679085,0.00040830488,0.00051292474,0.0007980171,0.000346805,0.0008406178,0.0010360812,0.00074429216,0.0008385784],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002582434,0.000051216313,0.008917439,0.000055161472,0.00011248469,0.000035956822,0.0005382256,0.000037763955,0.00042080847,0.00008408884,0.66252226,0.32719877],"study_design_scores_gemma":[0.0004168718,0.00025634436,0.19035567,0.00051383395,0.00019349379,0.00026885688,0.0001457327,0.000036003625,0.0002322189,0.08132964,0.7253796,0.00087177084],"about_ca_topic_score_codex":0.001809964,"about_ca_topic_score_gemma":0.0005698035,"teacher_disagreement_score":0.62608725,"about_ca_system_score_codex":0.00030417164,"about_ca_system_score_gemma":0.0005347195,"threshold_uncertainty_score":0.9999394},"labels":[],"label_agreement":null},{"id":"W4392863756","doi":"10.1002/bdm.2377","title":"Attention! Do We Really Need Attention Checks?","year":2024,"lang":"en","type":"article","venue":"Journal of Behavioral Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Israel Science Foundation","keywords":"Cognitive psychology; Psychology; Computer science","score_opus":0.1264952074393649,"score_gpt":0.4466319224044139,"score_spread":0.32013671496504903,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392863756","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96229255,0.00303048,0.025176616,0.0007958623,0.007887752,0.00018650468,0.00002778261,0.00008402177,0.0005184412],"genre_scores_gemma":[0.9802429,0.00038377364,0.017796148,0.00006910239,0.0006658209,0.00000396896,0.0000016582349,0.00006533754,0.0007712747],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99111813,0.00026042387,0.0037295031,0.000838955,0.0035170296,0.0005359846],"domain_scores_gemma":[0.9938785,0.0019541306,0.0015302283,0.00093120115,0.0013733224,0.00033261106],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.007622189,0.00043174115,0.00094996067,0.002440485,0.00031970468,0.0035741245,0.001761173,0.00033997145,0.001683501],"category_scores_gemma":[0.0010967609,0.0003107623,0.0013681257,0.0019202334,0.00013195851,0.0023385473,0.00040103108,0.00094179815,0.0013607983],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001956325,0.00020691929,0.005363513,0.000005656034,0.000020332842,0.00077150785,0.00022692501,0.00021823419,0.0035934353,0.00025728668,0.020179778,0.96896076],"study_design_scores_gemma":[0.0025890793,0.002404212,0.06192491,0.010041416,0.0008781422,0.005374103,0.0064797923,0.0065115895,0.00018048339,0.68628204,0.21554251,0.0017917124],"about_ca_topic_score_codex":0.000008302816,"about_ca_topic_score_gemma":0.00001748595,"teacher_disagreement_score":0.96716905,"about_ca_system_score_codex":0.00037456365,"about_ca_system_score_gemma":0.00028110968,"threshold_uncertainty_score":0.99993443},"labels":[],"label_agreement":null},{"id":"W4392905657","doi":"10.2139/ssrn.4731568","title":"Veblen Goods and Neighborhoods: Endogenizing Consumption Reference Groups","year":2024,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Veblen good; Consumption (sociology); Luxury goods; Economics; Conspicuous consumption; Neoclassical economics; Sociology; Business; Advertising; Institutional economics; Social science","score_opus":0.12246217836395266,"score_gpt":0.38670562112736373,"score_spread":0.26424344276341105,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392905657","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9759468,0.012536683,0.008393935,0.00055923464,0.00081981014,0.00007582671,0.000008240534,0.00006752398,0.0015919455],"genre_scores_gemma":[0.9927889,0.005944837,0.0002315159,0.00006780857,0.0002550518,0.0000028896666,0.0000018571784,0.00002117411,0.0006859335],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9967582,0.00014926532,0.0006712496,0.00051646365,0.0006011066,0.001303679],"domain_scores_gemma":[0.99859005,0.0006945453,0.00017546915,0.00029836473,0.00009394068,0.0001476409],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0062120147,0.00018655066,0.00027163822,0.00038057775,0.0003001874,0.0012901981,0.00054030656,0.00011949914,0.00021808322],"category_scores_gemma":[0.00042954326,0.00013695109,0.0001258993,0.00033716107,0.00008654892,0.00075277267,0.00012372312,0.0016215721,0.0006035508],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025396692,0.00001793795,0.0033533291,0.0000023922657,0.00003263684,0.000020215932,0.0001345913,0.000010852213,0.0005694182,0.08187567,0.00025098643,0.9137066],"study_design_scores_gemma":[0.0002476596,0.00020919963,0.0012521249,0.000059021364,0.000041042207,0.0019558105,0.0010048266,0.0010370895,0.000055554563,0.97985995,0.0140706245,0.00020712792],"about_ca_topic_score_codex":0.000019988438,"about_ca_topic_score_gemma":0.00022034424,"teacher_disagreement_score":0.9134994,"about_ca_system_score_codex":0.0004916331,"about_ca_system_score_gemma":0.00094249495,"threshold_uncertainty_score":0.99974656},"labels":[],"label_agreement":null},{"id":"W4392916327","doi":"10.31234/osf.io/qjcwn","title":"Goal-directed behaviour is associated with decreased temporal discounting","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; Baycrest Hospital","funders":"","keywords":"Discounting; Psychology; Delay discounting; Temporal discounting; Economics; Econometrics","score_opus":0.09562391032963335,"score_gpt":0.3848496818078755,"score_spread":0.28922577147824213,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392916327","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.979387,0.00014690284,0.0002940947,0.000931423,0.0019087536,0.0005110463,0.0006137168,0.00090462295,0.015302443],"genre_scores_gemma":[0.9792574,0.000005194355,0.0030699135,0.0003655004,0.0001647561,0.0000544184,0.00020005513,0.000106564214,0.016776174],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.992771,0.00023195209,0.0018154321,0.0022728904,0.0022635057,0.000645218],"domain_scores_gemma":[0.99450994,0.0013320785,0.0010847484,0.0018155918,0.0009062047,0.0003514207],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0036842565,0.00074298563,0.0012930625,0.00081780535,0.00025224482,0.003729835,0.0019459412,0.0007492798,0.00249925],"category_scores_gemma":[0.0023927141,0.0004786814,0.00059297506,0.0011307752,0.00019169069,0.000244009,0.0024417273,0.0015234553,0.0017714852],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002727562,0.0012083182,0.36287054,0.000039977058,0.0005449377,0.0012485497,0.0019440327,0.0005488251,0.000077742305,0.0002893379,0.2923088,0.3386462],"study_design_scores_gemma":[0.0032324924,0.0006401283,0.13504577,0.005040776,0.0022329737,0.00016895296,0.004564545,0.074079275,0.0011156495,0.7493454,0.017373018,0.0071610007],"about_ca_topic_score_codex":0.0015760813,"about_ca_topic_score_gemma":0.0020130358,"teacher_disagreement_score":0.7490561,"about_ca_system_score_codex":0.0003696758,"about_ca_system_score_gemma":0.0008676671,"threshold_uncertainty_score":0.99976647},"labels":[],"label_agreement":null},{"id":"W4392919485","doi":"10.1177/15501906241232454","title":"The Problem of Compromise in Conservation and Exhibit Decision Making","year":2024,"lang":"en","type":"article","venue":"Collections A Journal for Museum and Archives Professionals","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Heritage; Canadian Museum of Nature; Queen's University","funders":"","keywords":"Compromise; Mindset; Heuristics; Perspective (graphical); Management science; Risk analysis (engineering); Constructive; Computer science; Instinct; Teamwork; Operations research; Business; Political science; Process (computing); Engineering; Artificial intelligence; Law","score_opus":0.07858467272393613,"score_gpt":0.42753863199592407,"score_spread":0.3489539592719879,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392919485","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98308784,0.0021596013,0.009208463,0.0036035774,0.0008539818,0.00047999315,0.000027250762,0.000013216218,0.0005660997],"genre_scores_gemma":[0.9818624,0.00049561716,0.014419965,0.00008040009,0.00007104683,0.000049048915,8.0591496e-7,0.000012605183,0.0030080588],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99822444,0.0001641209,0.000876632,0.0002787685,0.00027600568,0.00018000678],"domain_scores_gemma":[0.98904794,0.010434132,0.00023189608,0.00013569521,0.000077948665,0.00007239441],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0019842265,0.00011029712,0.00023871784,0.00067668705,0.0015523789,0.0007368377,0.00021423188,0.000051379706,0.000021849337],"category_scores_gemma":[0.0005466811,0.00006206995,0.00010431523,0.0006429768,0.00017605186,0.0002863041,0.0001335545,0.0002622122,0.000001176283],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041053753,0.000088442925,0.0025558814,0.00002321824,0.000017862612,0.000006181721,0.0018075309,0.000109528206,0.00091526215,0.0044365386,0.011065624,0.97856337],"study_design_scores_gemma":[0.0005708642,0.00016689426,0.008104075,0.0014702649,0.000016151665,0.0002143568,0.0025223177,0.028461197,0.000067535715,0.90583175,0.052453205,0.00012140072],"about_ca_topic_score_codex":0.000002039793,"about_ca_topic_score_gemma":0.000037788923,"teacher_disagreement_score":0.978442,"about_ca_system_score_codex":0.000014990332,"about_ca_system_score_gemma":0.00018437796,"threshold_uncertainty_score":0.99974746},"labels":[],"label_agreement":null},{"id":"W4393259529","doi":"10.1037/mac0000172","title":"Younger and older women, but not men, are implicitly biased to associate honesty with children.","year":2024,"lang":"en","type":"article","venue":"Journal of Applied Research in Memory and Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Honesty; Psychology; Developmental psychology; Social psychology","score_opus":0.13997066518018156,"score_gpt":0.42389111911387456,"score_spread":0.28392045393369303,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393259529","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9967493,0.00011246526,0.0001048981,0.0012172617,0.00008711124,0.00026465862,0.000030802257,0.000009254357,0.0014242416],"genre_scores_gemma":[0.9991266,0.000087351604,0.00016821062,0.00027900742,0.0001441555,0.000022843431,0.0000014430333,0.000014380961,0.00015602265],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99723494,0.00016344115,0.0005960378,0.0003851427,0.0012633916,0.0003570384],"domain_scores_gemma":[0.99781394,0.0011440547,0.00018266596,0.00015584366,0.00042510818,0.0002783953],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00909197,0.00013062728,0.0003485535,0.0010519706,0.0001877985,0.0008157125,0.00023386587,0.00010276833,0.00008303069],"category_scores_gemma":[0.00031249473,0.00008503589,0.00004231163,0.00085251307,0.00013412641,0.00040193475,0.000111623245,0.0006777813,0.0000621391],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00209867,0.00024089363,0.001966818,0.000027986294,0.000068611065,0.00039956946,0.0024186005,0.00007718407,0.015203584,0.00013699566,0.0033485692,0.9740125],"study_design_scores_gemma":[0.008264637,0.0029558137,0.6072168,0.0024127462,0.00014001233,0.0013765432,0.0584708,0.00069671625,0.023333209,0.29077822,0.0031167816,0.0012377758],"about_ca_topic_score_codex":0.000010645227,"about_ca_topic_score_gemma":0.000016596094,"teacher_disagreement_score":0.97277474,"about_ca_system_score_codex":0.00011802703,"about_ca_system_score_gemma":0.00013564593,"threshold_uncertainty_score":0.78659344},"labels":[],"label_agreement":null},{"id":"W4393319687","doi":"10.1177/01461672261439247","title":"Everyone I Don’t Like Is Biased: Affective Evaluations and the Bias Blind Spot","year":2024,"lang":"en","type":"preprint","venue":"Personality and Social Psychology Bulletin","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Blind spot; Psychology; Cognitive psychology; Neuroscience","score_opus":0.2869992681249452,"score_gpt":0.4845625428265228,"score_spread":0.19756327470157758,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393319687","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8838119,0.0029538786,0.00014338976,0.10626451,0.002151812,0.00058014004,0.00047624204,0.000048508955,0.0035696137],"genre_scores_gemma":[0.98595756,0.00033412696,0.00018108153,0.009386194,0.00065709563,0.00009846688,0.000024815774,0.000029108716,0.0033315243],"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99471515,0.0016353488,0.0008667372,0.0015843888,0.0008460527,0.00035229785],"domain_scores_gemma":[0.9946745,0.0037758497,0.0004758779,0.0006451712,0.00031026037,0.00011835787],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.011190912,0.00040376835,0.00094533607,0.00027333366,0.00080307166,0.0008889474,0.0007020208,0.00082364137,0.0030484174],"category_scores_gemma":[0.0012847004,0.0002758551,0.00047941247,0.00027187463,0.002018132,0.000037550897,0.0011882109,0.0015593003,0.0008799971],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001947118,0.00039633442,0.0026902761,0.00006348716,0.0004406715,0.00003410483,0.047456812,0.00001404114,0.000010472085,0.0030981817,0.5595578,0.3842907],"study_design_scores_gemma":[0.0027435268,0.00009045212,0.036548942,0.000077348894,0.0004360511,0.0000507729,0.0037874214,0.0002365694,0.0000018955035,0.76163507,0.19382912,0.0005628553],"about_ca_topic_score_codex":0.0005143565,"about_ca_topic_score_gemma":0.00020021226,"teacher_disagreement_score":0.7585369,"about_ca_system_score_codex":0.00006787143,"about_ca_system_score_gemma":0.00015961991,"threshold_uncertainty_score":0.99996936},"labels":[],"label_agreement":null},{"id":"W4393858146","doi":"10.1016/j.cognition.2024.105774","title":"Emotions before actions: When children see costs as causal","year":2024,"lang":"en","type":"article","venue":"Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Psychology; Cognitive psychology; Cognition; Developmental psychology; Social psychology; Neuroscience","score_opus":0.1232972240289099,"score_gpt":0.41432051707761963,"score_spread":0.2910232930487097,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393858146","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9712117,0.00009397485,0.0024003135,0.0011050148,0.001182454,0.00021649667,0.00022255292,0.00023667763,0.023330865],"genre_scores_gemma":[0.99444884,0.000016264557,0.00037738087,0.00024388134,0.00027044996,0.000022492257,0.00015277832,0.000019489786,0.0044484315],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9982439,0.000072505834,0.0004442854,0.00051749736,0.0005228178,0.00019894111],"domain_scores_gemma":[0.99884063,0.00037610604,0.00008262563,0.00035570914,0.0002256288,0.00011930529],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0007362443,0.00013858039,0.00016616851,0.00040532157,0.00027249617,0.0009492771,0.00028810446,0.00012209328,0.0035597067],"category_scores_gemma":[0.0007924451,0.0001128282,0.00015367476,0.00045200626,0.00007925243,0.0007407172,0.000086911416,0.00022120753,0.019155484],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000093971985,0.000065951615,0.00075805426,0.0000014656601,0.000019086478,0.00001493758,0.00020379503,0.00001222512,0.0002518316,0.0012462279,0.027700411,0.9697166],"study_design_scores_gemma":[0.0003945575,0.00025408898,0.03177942,0.00021387963,0.00014640695,0.0003500446,0.0006063707,0.0015425229,0.0011612423,0.8978482,0.065291986,0.00041126704],"about_ca_topic_score_codex":0.00003332363,"about_ca_topic_score_gemma":0.00013716017,"teacher_disagreement_score":0.96930534,"about_ca_system_score_codex":0.00011420511,"about_ca_system_score_gemma":0.00010498341,"threshold_uncertainty_score":0.99735117},"labels":[],"label_agreement":null},{"id":"W4394617843","doi":"10.1002/bdm.2381","title":"Measuring Rational Thinking in Adolescents: The Assessment of Rational Thinking for Youth (ART‐Y)","year":2024,"lang":"en","type":"article","venue":"Journal of Behavioral Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; York University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Psychology; Rationality; Numeracy; Cognition; Literacy; Developmental psychology; Mathematics education; Cognitive psychology; Social psychology; Pedagogy; Epistemology","score_opus":0.21265458672150173,"score_gpt":0.4519607289546748,"score_spread":0.2393061422331731,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394617843","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.84026617,0.00041682125,0.15521201,0.00029367697,0.0031554056,0.00036949595,0.0000524957,0.000019727035,0.00021420378],"genre_scores_gemma":[0.9609181,0.000020646901,0.03850875,0.000096214804,0.00036851264,0.0000063538387,0.0000035010423,0.00003564902,0.000042256386],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99166745,0.00028046255,0.0033536274,0.000533723,0.0037941237,0.00037059793],"domain_scores_gemma":[0.9935459,0.0031043885,0.0015183417,0.0005105446,0.0012171482,0.00010370738],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.014599217,0.00029950982,0.000735218,0.0014174375,0.00048990495,0.001516694,0.0017408279,0.00018288333,0.00015956206],"category_scores_gemma":[0.0010221561,0.00019026647,0.0007407049,0.0010501058,0.000113552065,0.0014798251,0.00019985992,0.000792991,0.00002025727],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005827327,0.0007681063,0.076395586,0.000039422284,0.000052588846,0.00018777732,0.0065494087,0.030827848,0.0011682608,0.008776992,0.0027713748,0.8718799],"study_design_scores_gemma":[0.0033754653,0.0010413064,0.12687732,0.0142688155,0.00047953878,0.00050645677,0.010642966,0.061882477,0.00034715058,0.77141637,0.008130046,0.0010320778],"about_ca_topic_score_codex":0.000009332241,"about_ca_topic_score_gemma":0.00015774004,"teacher_disagreement_score":0.8708478,"about_ca_system_score_codex":0.00040133146,"about_ca_system_score_gemma":0.00087891135,"threshold_uncertainty_score":0.9995198},"labels":[],"label_agreement":null},{"id":"W4394773979","doi":"10.1016/bs.adms.2024.03.002","title":"Boundary conditions of the rational model: Finding the limits of rationality","year":2024,"lang":"en","type":"book-chapter","venue":"Advances in motivation science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Rationality; Rational planning model; Axiom; Mathematical proof; Mathematical economics; Management science; Irrational number; Computer science; Epistemology; Mathematics; Economics","score_opus":0.19618450666490836,"score_gpt":0.44265941162310973,"score_spread":0.24647490495820137,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394773979","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3068707,0.002194932,0.01674103,0.006225748,0.0061190687,0.0016141252,0.0013548135,0.000054692475,0.65882486],"genre_scores_gemma":[0.96605253,0.000080665086,0.0006766614,0.00013789834,0.0000486212,0.000011074345,0.0000092519485,0.000010840196,0.032972425],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9957374,0.000040348823,0.0012733658,0.0005876387,0.0022088313,0.00015245692],"domain_scores_gemma":[0.9946559,0.0026261276,0.0010479366,0.0007941587,0.0008410291,0.00003485743],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003925326,0.00017113287,0.00030443366,0.000493528,0.00040302437,0.00020867756,0.0017812676,0.00009701111,0.00019871375],"category_scores_gemma":[0.0034281837,0.00009699884,0.00017447195,0.00086854334,0.0023982564,0.0013043553,0.00028979834,0.00033318138,0.000032777054],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008513908,0.000023816112,0.0014754852,0.000008008691,0.0000036305341,4.3774637e-7,0.00030900256,0.091995135,0.0005251334,0.88211095,0.00043184907,0.023108054],"study_design_scores_gemma":[0.00006155651,0.000013547275,0.0042745923,0.00019417994,0.000009512764,0.0000026312844,0.00007153404,0.011213252,0.00040236505,0.96982133,0.013829736,0.0001057555],"about_ca_topic_score_codex":0.000002920109,"about_ca_topic_score_gemma":0.00005267831,"teacher_disagreement_score":0.65918183,"about_ca_system_score_codex":0.00015710843,"about_ca_system_score_gemma":0.00089530216,"threshold_uncertainty_score":0.88364756},"labels":[],"label_agreement":null},{"id":"W4394841178","doi":"10.1371/journal.pone.0299511","title":"Gamification and motivation: Impact on delay discounting performance","year":2024,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Reed College","keywords":"Discounting; Delay discounting; Impulsivity; Task (project management); Psychology; Temporal discounting; Social psychology; Context (archaeology); Cognitive psychology; Function (biology); Developmental psychology; Economics","score_opus":0.24949325862279703,"score_gpt":0.38132069503653576,"score_spread":0.13182743641373873,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394841178","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99725324,0.00011872551,0.00016172393,0.0004689922,0.00010336554,0.00011101631,0.000010694712,0.000055144614,0.0017171166],"genre_scores_gemma":[0.9986206,0.0000397911,0.00047465935,0.000053895026,0.000114667986,0.000009319082,0.0000041838657,0.000009964145,0.0006729079],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9986678,0.00002427348,0.00031577173,0.00034517344,0.0005222892,0.0001246872],"domain_scores_gemma":[0.9987416,0.00075027865,0.0000728182,0.00029589774,0.00008715129,0.000052252475],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00091748976,0.00009266586,0.00015044218,0.00020162149,0.00011138825,0.00063307694,0.00018493576,0.000043147473,0.00021937858],"category_scores_gemma":[0.00053215405,0.00006055754,0.000041598352,0.0003343396,0.000038828002,0.0005294946,0.000044080443,0.000119643824,0.0007339154],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003261259,0.00027267018,0.07090592,0.000015631613,0.000030207948,0.000005082745,0.00041820182,0.00024012392,0.0026336317,0.00039739476,0.00064839027,0.92440015],"study_design_scores_gemma":[0.0003040419,0.0005821978,0.67775834,0.0010168871,0.00010170543,0.000018694762,0.00031498203,0.28369153,0.0065296795,0.02669967,0.0024561435,0.0005261628],"about_ca_topic_score_codex":0.00000433417,"about_ca_topic_score_gemma":0.0000014584996,"teacher_disagreement_score":0.92387396,"about_ca_system_score_codex":0.000042452946,"about_ca_system_score_gemma":0.000025346533,"threshold_uncertainty_score":0.94332427},"labels":[],"label_agreement":null},{"id":"W4396899401","doi":"10.1007/s10683-024-09824-2","title":"Task completion without commitment","year":2024,"lang":"en","type":"article","venue":"Experimental Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University; Simon Fraser University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Task (project management); Organizational commitment; Psychology; Completion (oil and gas wells); Social psychology; Economics; Management","score_opus":0.15626036128212378,"score_gpt":0.4305159007337755,"score_spread":0.2742555394516517,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396899401","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97850215,0.00079638674,0.0006197148,0.00051793916,0.0031724975,0.00019718766,0.00006208907,0.00013850885,0.01599353],"genre_scores_gemma":[0.9966576,0.000023961125,0.0013784271,0.00041714092,0.00023359733,0.00002835162,0.000020513331,0.00003159619,0.0012088077],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9979567,0.00005831544,0.00077096885,0.0007164597,0.00023476253,0.00026279312],"domain_scores_gemma":[0.9987738,0.00030123309,0.000121484605,0.0006150751,0.000033574313,0.00015484921],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00095712143,0.00021401286,0.00035430223,0.00024600464,0.00016819104,0.0011641274,0.00060565065,0.00008600315,0.002202902],"category_scores_gemma":[0.000046673882,0.0001824424,0.0002180365,0.00015451823,0.00012319032,0.0005507772,0.00024164031,0.00014564389,0.006783893],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015442615,0.000627814,0.0045759785,0.000006371417,0.00009235112,0.00005520559,0.0030982872,0.0017398677,0.009484123,0.048116267,0.06951992,0.8625294],"study_design_scores_gemma":[0.0005378496,0.00025291392,0.0007704075,0.000036844645,0.00001539365,0.0000810062,0.0023258002,0.04287879,0.012250012,0.057765186,0.88251716,0.0005686361],"about_ca_topic_score_codex":0.000035153487,"about_ca_topic_score_gemma":0.00001885787,"teacher_disagreement_score":0.86196077,"about_ca_system_score_codex":0.00040072663,"about_ca_system_score_gemma":0.00006824638,"threshold_uncertainty_score":0.99987274},"labels":[],"label_agreement":null},{"id":"W4398332890","doi":"10.1080/00131857.2024.2354459","title":"Behavioral insights: The problem of control in education governance","year":2024,"lang":"en","type":"article","venue":"Educational Philosophy and Theory","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kwantlen Polytechnic University","funders":"","keywords":"Corporate governance; Sociology; Control (management); Philosophy of education; Public administration; Higher education; Pedagogy; Epistemology; Environmental ethics; Engineering ethics; Political science; Management; Economics; Law; Philosophy; Engineering","score_opus":0.05102831256646106,"score_gpt":0.37540851913693973,"score_spread":0.32438020657047867,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4398332890","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95631075,0.0080175875,0.000088517736,0.012974872,0.0011700903,0.00024729766,0.000042598316,0.000012065664,0.021136224],"genre_scores_gemma":[0.99848413,0.000052268224,0.00020089754,0.00038519036,0.0003044852,0.00004418349,0.000003896734,0.000007694758,0.0005172211],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986337,0.00015857982,0.00047213698,0.0003086523,0.00033447542,0.0000924632],"domain_scores_gemma":[0.99761397,0.0018289177,0.0001323219,0.00026212086,0.00011908382,0.000043562934],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013308916,0.00009888528,0.00015577354,0.00015473636,0.00008102263,0.00014888,0.00034825588,0.000051714724,0.00026157848],"category_scores_gemma":[0.00015568512,0.00006050866,0.00007001818,0.00038966222,0.00021426364,0.00034472818,0.00003978487,0.0001565876,0.00008813772],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025731893,0.00019229217,0.0010897944,0.000004738344,0.000003660651,4.3576918e-7,0.0007883073,0.000013776346,0.00002887925,0.7518094,0.0008985389,0.24514443],"study_design_scores_gemma":[0.00009483178,0.000032595763,0.011325201,0.00008712283,0.000011163863,0.000007729703,0.00037458984,0.00005470646,0.000010035597,0.97073597,0.01719237,0.00007366477],"about_ca_topic_score_codex":0.000026178217,"about_ca_topic_score_gemma":0.000011859023,"teacher_disagreement_score":0.24507076,"about_ca_system_score_codex":0.0000465659,"about_ca_system_score_gemma":0.00045589136,"threshold_uncertainty_score":0.2864101},"labels":[],"label_agreement":null},{"id":"W4399215419","doi":"10.1177/0272989x241256121","title":"Thinking Fast, Slow, and Forever: Daniel Kahneman Obituary","year":2024,"lang":"en","type":"editorial","venue":"Medical Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; University of Toronto; Institute for Clinical Evaluative Sciences; Sunnybrook Health Science Centre","funders":"Canada Research Chairs","keywords":"Obituary; Prospect theory; Psychology; Economics; Computer science; Mathematical economics; Philosophy; Microeconomics; Theology","score_opus":0.0449707019638836,"score_gpt":0.40334184378099586,"score_spread":0.35837114181711227,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399215419","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007473793,0.0027904615,0.021078488,0.0008893124,0.9573523,0.0004410831,0.00025709515,0.00035793538,0.009359569],"genre_scores_gemma":[0.018251535,0.0010948457,0.02327206,0.0016119166,0.9436273,0.000067727546,0.00011031482,0.00043031632,0.011533966],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.976024,0.00039398207,0.0035430503,0.0032127663,0.015762521,0.0010636868],"domain_scores_gemma":[0.9503024,0.044488523,0.0010761404,0.0024084745,0.00077890983,0.0009455077],"candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication","research_integrity","insufficient_payload"],"consensus_categories":["research_integrity","insufficient_payload"],"category_scores_codex":[0.017943349,0.0010548163,0.0021296411,0.0016453636,0.00078202406,0.004328612,0.005268728,0.003220507,0.0023295959],"category_scores_gemma":[0.0793205,0.0007510968,0.0007947191,0.0013163276,0.000565273,0.0006509015,0.0047287815,0.004120836,0.0029287057],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000053153195,0.000032832304,0.00002418543,0.000019647441,0.000020217083,0.0005773114,0.00016573347,0.0000065072363,8.0170986e-7,0.00013899662,0.52381027,0.47515035],"study_design_scores_gemma":[0.000386455,0.00011581706,0.000024841069,0.0027056502,0.00008892057,0.00007298188,0.00018798895,0.002768024,8.2774505e-7,0.3492396,0.6438375,0.0005713856],"about_ca_topic_score_codex":0.00002840158,"about_ca_topic_score_gemma":0.00017131996,"teacher_disagreement_score":0.47457895,"about_ca_system_score_codex":0.00031930025,"about_ca_system_score_gemma":0.0011675141,"threshold_uncertainty_score":0.999494},"labels":[],"label_agreement":null},{"id":"W4399217197","doi":"10.1287/mnsc.2023.00522","title":"Forgetful Consumers and Consumption Tracking","year":2024,"lang":"en","type":"article","venue":"Management Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Consumption (sociology); Tracking (education); Computer science; Economics; Business; Psychology; Sociology","score_opus":0.18233446637327122,"score_gpt":0.444194229170756,"score_spread":0.2618597627974848,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399217197","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97310746,0.00032149596,0.0063254084,0.0005637226,0.0013356352,0.00016134811,0.000004178693,0.00010672087,0.018074056],"genre_scores_gemma":[0.9954129,0.000081196886,0.0019010975,0.00015716038,0.00001567662,0.0000059403533,3.8568936e-7,0.000005805907,0.00241983],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9976687,0.000023961295,0.0003531795,0.0007729703,0.0009050228,0.0002761742],"domain_scores_gemma":[0.99904954,0.00032143877,0.000059684313,0.00039830725,0.000057536887,0.00011347722],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0042328793,0.000104016755,0.00012716743,0.00069863716,0.0003282173,0.0024137734,0.000679591,0.000024864412,0.00024856723],"category_scores_gemma":[0.0002441694,0.00007842977,0.00004511614,0.0010047061,0.0006354764,0.0011135635,0.0003567021,0.000081772996,0.0010869442],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000027194897,0.000009060577,0.0069279214,0.000007432134,0.0000029691005,0.000031301926,0.00012998581,0.000022753204,0.00019125645,0.012413937,0.0010343471,0.9792263],"study_design_scores_gemma":[0.00047011022,0.000100636484,0.17030765,0.00028300448,0.00008537752,0.000085940745,0.0024418042,0.057218656,0.0007436837,0.325523,0.4419757,0.00076443487],"about_ca_topic_score_codex":0.000004925106,"about_ca_topic_score_gemma":0.000008621626,"teacher_disagreement_score":0.97846186,"about_ca_system_score_codex":0.00006182005,"about_ca_system_score_gemma":0.000025517089,"threshold_uncertainty_score":0.99969083},"labels":[],"label_agreement":null},{"id":"W4399466491","doi":"10.1101/2024.06.05.597571","title":"SK609, a novel dopamine D3 receptor agonist and norepinephrine transporter blocker with pro-cognitive actions, does not induce psychostimulant-like increases in risky choice during probabilistic discounting","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Dopamine receptor D3; Agonist; Dopamine; Discounting; Dopamine transporter; Norepinephrine transporter; Dopamine receptor D2; Norepinephrine; Probabilistic logic; Neuroscience; Pharmacology; Receptor; Psychology; Medicine; Computer science; Internal medicine; Business; Dopaminergic; Finance; Artificial intelligence","score_opus":0.04670085633784389,"score_gpt":0.30959718391925434,"score_spread":0.26289632758141046,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399466491","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9941947,0.00033315236,0.00016295917,0.0003424558,0.0011602384,0.0015999365,0.0019102917,0.0002853346,0.000010954865],"genre_scores_gemma":[0.9951755,0.00009746638,0.0033406809,0.00010989132,0.00054281217,0.0004934676,0.0000030238791,0.00018331839,0.000053873195],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9930156,0.00015725597,0.0018416292,0.0029955755,0.0011680677,0.0008219081],"domain_scores_gemma":[0.9952232,0.0010272112,0.0010141558,0.0014703444,0.00086532783,0.00039976093],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0018938752,0.0010435045,0.0013151324,0.001180695,0.00037425983,0.0017220314,0.00092286937,0.0005579923,0.00009873148],"category_scores_gemma":[0.001852543,0.00075852295,0.00021522032,0.0014859475,0.00044816927,0.0005522741,0.00078679144,0.0017588557,0.00009744816],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002626568,0.0036065588,0.4960773,0.0020044895,0.0006880745,0.00083499367,0.00032336565,0.00066041556,0.4918278,0.00015289313,0.0002133072,0.0009842635],"study_design_scores_gemma":[0.004294564,0.0002751319,0.93443644,0.008278141,0.00079192244,0.0000022655179,0.00015977272,0.0019411796,0.04338758,0.00009715189,0.0030093223,0.0033265154],"about_ca_topic_score_codex":0.0007369305,"about_ca_topic_score_gemma":0.00059945154,"teacher_disagreement_score":0.4484402,"about_ca_system_score_codex":0.00033144263,"about_ca_system_score_gemma":0.00065723807,"threshold_uncertainty_score":0.99948657},"labels":[],"label_agreement":null},{"id":"W4399523074","doi":"10.3389/fpsyg.2024.1390741","title":"Time pressure increases children’s aversion to advantageous inequity","year":2024,"lang":"en","type":"article","venue":"Frontiers in Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"St. Francis Xavier University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Psychology; Inequity aversion; Social psychology; Cognitive psychology; Developmental psychology; Inequality","score_opus":0.037840186047903124,"score_gpt":0.39858756805411316,"score_spread":0.36074738200621004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399523074","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9746571,0.001956051,0.009466427,0.0013795503,0.006475437,0.00031066127,0.00013085069,0.00014082046,0.0054831035],"genre_scores_gemma":[0.9849311,0.00008882251,0.010641544,0.0016266052,0.00023981005,0.000018653365,0.000018337132,0.00003189248,0.0024032192],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99734575,0.00020560922,0.0006309195,0.0010164642,0.00041689875,0.00038433325],"domain_scores_gemma":[0.9985436,0.00031693175,0.00008040737,0.0008241807,0.00005701216,0.00017783282],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0016198241,0.00019641615,0.00044006124,0.0010545573,0.00007512364,0.00020098998,0.001049558,0.00021640504,0.0012566078],"category_scores_gemma":[0.00076349225,0.00016053578,0.00013482319,0.00088549376,0.00012899337,0.00028904702,0.00027113708,0.00030335778,0.0038828098],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009544268,0.00007863179,0.023748768,0.0000011518582,0.000011921762,0.000066311346,0.00010675634,0.0001041882,0.000052848394,0.00002045949,0.45015684,0.5255567],"study_design_scores_gemma":[0.0006706149,0.00037503376,0.039001916,0.00008970282,0.0000476409,0.00019178017,0.00021554329,0.0033426455,0.000045794055,0.16382283,0.7916955,0.00050101016],"about_ca_topic_score_codex":0.000043621767,"about_ca_topic_score_gemma":0.000015300835,"teacher_disagreement_score":0.52505565,"about_ca_system_score_codex":0.000060559472,"about_ca_system_score_gemma":0.0000556469,"threshold_uncertainty_score":0.9996564},"labels":[],"label_agreement":null},{"id":"W4399848062","doi":"10.1177/09567976241256961","title":"Sensitivity to the Instrumental Value of Choice Increases Across Development","year":2024,"lang":"en","type":"article","venue":"Psychological Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Templeton World Charity Foundation; Jacobs Foundation; National Institute of Mental Health; York University; National Science Foundation","keywords":"Psychology; Preference; Value (mathematics); Agency (philosophy); Developmental psychology; Social psychology; Replication (statistics); Statistics","score_opus":0.17906294243747187,"score_gpt":0.5050483237752172,"score_spread":0.32598538133774535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399848062","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9941362,0.00003278786,0.0014250302,0.0013365452,0.0010057652,0.00014468856,0.000021963908,0.000046272446,0.0018507533],"genre_scores_gemma":[0.99634135,0.0000020840043,0.002752776,0.000719941,0.00005834325,0.000007705013,3.6650286e-7,0.000003438136,0.00011401473],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9967919,0.00012477482,0.00053111557,0.00086586847,0.001296307,0.00039001097],"domain_scores_gemma":[0.997319,0.0016804434,0.00008548618,0.00057713944,0.00013027835,0.00020768528],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0094025675,0.00012380096,0.000198815,0.00012748643,0.000433006,0.00071042613,0.0014051949,0.00005079691,0.00017900844],"category_scores_gemma":[0.0038055507,0.000060366317,0.00008464527,0.0021884171,0.0007877795,0.00035183536,0.00067577465,0.0001570531,0.0011087863],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013179472,0.00012694063,0.009394111,6.600156e-7,0.0000015759541,0.000013851897,0.0004706371,0.00011792723,0.003565435,0.0006185515,0.0010397682,0.9846374],"study_design_scores_gemma":[0.000109396446,0.00018018573,0.9064325,0.00004937497,0.0000037400628,0.00009165589,0.0006238984,0.0013513328,0.003461315,0.009406651,0.07805976,0.0002301686],"about_ca_topic_score_codex":0.000104901075,"about_ca_topic_score_gemma":0.000103890314,"teacher_disagreement_score":0.9844072,"about_ca_system_score_codex":0.00008663156,"about_ca_system_score_gemma":0.00009099883,"threshold_uncertainty_score":0.99966896},"labels":[],"label_agreement":null},{"id":"W4399856812","doi":"10.1037/emo0001347","title":"How bad becomes good: A neurocomputational model of affect-informed choice.","year":2024,"lang":"en","type":"article","venue":"Emotion","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; National Institute of Mental Health; Canada Foundation for Innovation","keywords":"Affect (linguistics); Psychology; Social psychology; Cognitive psychology; Developmental psychology","score_opus":0.15814602079910306,"score_gpt":0.4089237130035878,"score_spread":0.25077769220448476,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399856812","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9484832,0.000048358008,0.046991426,0.0017288043,0.00094638567,0.00012217872,0.000035988847,0.00007509956,0.0015685483],"genre_scores_gemma":[0.99446243,0.0000051605343,0.0026808344,0.00007119299,0.00010359333,0.0000042837905,0.000012223231,0.000010861382,0.0026494479],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998417,0.000042784926,0.00041410027,0.0003416494,0.00063993165,0.0001445057],"domain_scores_gemma":[0.9982095,0.0011900582,0.0001401972,0.00025710446,0.00013797074,0.000065189495],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006860245,0.00011330195,0.00020611547,0.00037968255,0.000065324915,0.0005605958,0.0003168033,0.00007169834,0.00011079851],"category_scores_gemma":[0.00075150246,0.000086167296,0.00017274504,0.0004252677,0.000046619603,0.00076992536,0.000076785625,0.00011215489,0.00023983396],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000106176885,0.000056546112,0.001707747,0.000014015935,0.000009277725,0.0000036176573,0.00036482318,0.033408426,0.00057013874,0.003598703,0.011002756,0.9492533],"study_design_scores_gemma":[0.00020894094,0.000092016475,0.018701065,0.000058460453,0.000015617805,0.000010125448,0.000111152636,0.85370815,0.0002755491,0.11590164,0.010769528,0.00014776886],"about_ca_topic_score_codex":0.000007817001,"about_ca_topic_score_gemma":0.000023410596,"teacher_disagreement_score":0.94910556,"about_ca_system_score_codex":0.00005283021,"about_ca_system_score_gemma":0.00013694454,"threshold_uncertainty_score":0.54058385},"labels":[],"label_agreement":null},{"id":"W4399887836","doi":"10.1007/978-3-031-59144-0_18","title":"Consumer Well-Being in Judgment and Decision-Making","year":2024,"lang":"en","type":"book-chapter","venue":"International series on consumer science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Psychology; Computer science","score_opus":0.050484455948971635,"score_gpt":0.3679224903292694,"score_spread":0.3174380343802977,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399887836","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09125625,0.00081085163,0.0001556736,0.0014367035,0.0084852325,0.00034933013,0.000108889195,0.00008481912,0.8973122],"genre_scores_gemma":[0.85651195,0.0007189189,0.0030545907,0.0009535673,0.00016834233,0.000021008798,0.0000056889694,0.00006722287,0.13849872],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99341655,0.000017213802,0.001386024,0.001843143,0.0029107057,0.00042637516],"domain_scores_gemma":[0.9956494,0.0022704925,0.00045604582,0.00086488307,0.0005579023,0.00020127036],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0028254497,0.00048425616,0.00059070013,0.0022365116,0.00028408298,0.0022560204,0.0023181324,0.0002410233,0.0024116507],"category_scores_gemma":[0.0014035853,0.00039584513,0.00017906744,0.00036828642,0.0015706522,0.0010031202,0.0012551658,0.00066627294,0.003862242],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011618651,0.000026886657,0.00080630346,0.000003655815,0.00002394091,0.00026554,0.00018915176,0.00007121429,0.000026874503,0.27299362,0.0022935383,0.7231831],"study_design_scores_gemma":[0.00013820466,0.00005020044,0.00033342282,0.00081004476,0.000014583818,0.0001003618,0.0000676536,0.00063353276,0.000028495913,0.63563323,0.36182433,0.00036595183],"about_ca_topic_score_codex":0.00002077333,"about_ca_topic_score_gemma":0.00024122193,"teacher_disagreement_score":0.7652557,"about_ca_system_score_codex":0.0004636806,"about_ca_system_score_gemma":0.00036797213,"threshold_uncertainty_score":0.9998493},"labels":[],"label_agreement":null},{"id":"W4400229466","doi":"10.1016/j.jecp.2024.105995","title":"The impact of strategies on young children’s saving for the future","year":2024,"lang":"en","type":"article","venue":"Journal of Experimental Child Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Brock University","funders":"Ontario Ministry of Economic Development, Job Creation and Trade; Ontario Ministry of Research and Innovation; Natural Sciences and Engineering Research Council of Canada; Ontario Ministry of Research, Innovation and Science","keywords":"Psychology; Control (management); Tracking (education); Perspective (graphical); Developmental psychology; Early childhood; Early childhood education; Covariate; Economics; Pedagogy","score_opus":0.07180166381770783,"score_gpt":0.4910968086294683,"score_spread":0.41929514481176045,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400229466","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.975098,0.013195863,0.00028443453,0.0027682642,0.0049609756,0.00016844495,0.000024711617,0.0000074411014,0.0034918615],"genre_scores_gemma":[0.9985267,0.00016854829,0.00010666713,0.00013560506,0.0009904878,0.0000043707523,5.796785e-7,0.000014629364,0.000052418458],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9982108,0.000100972764,0.0008546102,0.00023007259,0.00040049784,0.00020306169],"domain_scores_gemma":[0.9975987,0.0013333516,0.00047164416,0.0004263099,0.00010890678,0.00006108388],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018515105,0.00015354465,0.00028943282,0.00018703459,0.00031551466,0.00048135882,0.0010308936,0.00008831606,0.0001879659],"category_scores_gemma":[0.000114635906,0.000062112566,0.00065371324,0.00023136745,0.00017874935,0.0002589022,0.000049070357,0.00036237523,0.00002411798],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0026198286,0.00090910995,0.006701814,0.0000023669004,0.0007247272,0.000044500408,0.0045311484,0.0014171137,0.011378737,0.02386826,0.21595381,0.7318486],"study_design_scores_gemma":[0.0035043454,0.0123942215,0.73327583,0.0003014907,0.00015636095,0.006607463,0.03344196,0.0007291944,0.005109371,0.13387205,0.06990269,0.00070502824],"about_ca_topic_score_codex":0.00000803046,"about_ca_topic_score_gemma":0.000006312575,"teacher_disagreement_score":0.73114353,"about_ca_system_score_codex":0.000067495865,"about_ca_system_score_gemma":0.000078006655,"threshold_uncertainty_score":0.4641754},"labels":[],"label_agreement":null},{"id":"W4400313395","doi":"10.2139/ssrn.4885567","title":"Information Combination and Preference Reversals: Eye-Tracking Data","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Vanier College","funders":"","keywords":"Preference; Eye tracking; Computer science; Artificial intelligence; Cognitive psychology; Optometry; Psychology; Economics; Medicine; Microeconomics","score_opus":0.16690602240847222,"score_gpt":0.4187591811976885,"score_spread":0.2518531587892163,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400313395","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9786269,0.0036600218,0.011409853,0.0020425161,0.0026089267,0.0002680405,0.00011040845,0.00007018037,0.0012031278],"genre_scores_gemma":[0.99471825,0.0040402715,0.0003460158,0.000077991295,0.00021054981,0.0000040151685,0.00009624949,0.000019054929,0.00048758046],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9957269,0.0001930463,0.0013079776,0.00057436555,0.0011143384,0.0010833857],"domain_scores_gemma":[0.9968208,0.0003819547,0.0010002548,0.001213818,0.00046897947,0.00011417437],"candidate_categories":["scholarly_communication","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.015015436,0.000284065,0.00043633702,0.00068883057,0.00025227736,0.003433866,0.0024078789,0.00032246835,0.000049994596],"category_scores_gemma":[0.0023202542,0.00022394475,0.000116992735,0.0002987776,0.000072828036,0.0018831441,0.0032631534,0.004990419,0.00040286186],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022866408,0.00002377319,0.0005522225,0.000012689298,0.000046160345,0.0000022131228,0.0004642695,0.00014060835,0.000006430751,0.011082423,0.0017909679,0.9858554],"study_design_scores_gemma":[0.00020743418,0.00008145004,0.0006849738,0.00019409326,0.00007820614,0.00015488098,0.0021682887,0.0069066687,0.00000498791,0.9802943,0.0089719575,0.0002527516],"about_ca_topic_score_codex":0.000070492046,"about_ca_topic_score_gemma":0.00032773917,"teacher_disagreement_score":0.9856026,"about_ca_system_score_codex":0.0007911954,"about_ca_system_score_gemma":0.0030259169,"threshold_uncertainty_score":0.9976007},"labels":[],"label_agreement":null},{"id":"W4400341720","doi":"10.1080/00014788.2024.2364215","title":"Enhancing auditors’ professional skepticism through nudges: an eye-tracking experiment","year":2024,"lang":"en","type":"article","venue":"Accounting and Business Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"HEC Montréal; Agence Nationale de la Recherche","keywords":"Skepticism; Nudge theory; Audit; Eye tracking; Psychology; Tracking (education); Accounting; Business; Cognitive psychology; Computer science; Social psychology; Artificial intelligence; Epistemology; Pedagogy; Philosophy","score_opus":0.23787423315535733,"score_gpt":0.5344445220813828,"score_spread":0.2965702889260255,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400341720","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99058473,0.0012007565,0.0010777058,0.0016803431,0.0036960887,0.0002068269,0.0000073733636,0.00013492843,0.0014112649],"genre_scores_gemma":[0.9949459,0.00008761562,0.0016422361,0.00009431364,0.0015629497,0.000039543505,0.000008673527,0.00004233752,0.0015764451],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99468505,0.000280249,0.00080275774,0.0011518374,0.0023500214,0.00073009706],"domain_scores_gemma":[0.99533683,0.0023136463,0.00011375723,0.0006751911,0.0014230183,0.00013757088],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00881163,0.00023667798,0.00036057853,0.0006453408,0.0010481952,0.004172916,0.00087289506,0.00020165555,0.00054965314],"category_scores_gemma":[0.0029463049,0.00016632644,0.00007907376,0.0019593304,0.00030260222,0.0025364917,0.0006696901,0.0006871603,0.00067667],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007470435,0.00040568723,0.0084093865,0.0001033628,0.0000255137,0.00019265199,0.008036853,0.00010214394,0.0460225,0.0020891486,0.018796094,0.915742],"study_design_scores_gemma":[0.0010518121,0.000405103,0.07248261,0.0038446574,0.00005332044,0.00016066188,0.04353518,0.01631022,0.022018122,0.30522522,0.53290045,0.0020126419],"about_ca_topic_score_codex":0.00033768438,"about_ca_topic_score_gemma":0.000074214026,"teacher_disagreement_score":0.9137293,"about_ca_system_score_codex":0.000118892654,"about_ca_system_score_gemma":0.0004091587,"threshold_uncertainty_score":0.99686086},"labels":[],"label_agreement":null},{"id":"W4400442148","doi":"10.5465/amproc.2024.80bp","title":"When and Why Employees Can (Cannot) Learn from Their Errors: From a Cognitive Rumination Perspective","year":2024,"lang":"en","type":"article","venue":"Academy of Management Proceedings","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ted Rogers Centre for Heart Research","funders":"","keywords":"Rumination; Perspective (graphical); Psychology; Cognition; Cognitive psychology; Social psychology; Computer science; Artificial intelligence","score_opus":0.08981426636891607,"score_gpt":0.36629618125678914,"score_spread":0.2764819148878731,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400442148","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98282725,0.00076870876,0.0002907087,0.00886475,0.0001612018,0.0003556479,0.00019485848,0.000109265675,0.006427619],"genre_scores_gemma":[0.9970097,0.00017337609,0.0010203077,0.0006377256,0.00013684267,0.000028092418,0.000008630898,0.000026660193,0.0009586821],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.997386,0.000026297175,0.00059724273,0.0010098607,0.0007378289,0.00024279548],"domain_scores_gemma":[0.99863946,0.00069890777,0.0002640071,0.00009190704,0.0002060106,0.000099675526],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001035087,0.00024475393,0.00037049566,0.0005556818,0.0001265641,0.0006713589,0.00061508804,0.00015519206,0.00027982134],"category_scores_gemma":[0.00042361606,0.00019183189,0.00011493196,0.0004671139,0.00021266937,0.0009794087,0.00046224584,0.00031538302,0.00009325449],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012816963,0.00010573941,0.0056529897,0.000026173835,0.00028287934,0.000009569787,0.023723638,0.0000023956575,0.00037839546,0.015129737,0.038748734,0.9158116],"study_design_scores_gemma":[0.00043351803,0.0001206497,0.027032457,0.00051304564,0.00019567429,0.0000018518032,0.06786489,0.0009398944,0.0013171314,0.8603678,0.040879656,0.00033347748],"about_ca_topic_score_codex":0.0004942593,"about_ca_topic_score_gemma":0.000030232912,"teacher_disagreement_score":0.9154781,"about_ca_system_score_codex":0.00010841899,"about_ca_system_score_gemma":0.00001589391,"threshold_uncertainty_score":0.78226775},"labels":[],"label_agreement":null},{"id":"W4400855815","doi":"10.1016/j.cognition.2024.105895","title":"Risky effort","year":2024,"lang":"en","type":"article","venue":"Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Economic and Social Research Council; Natural Sciences and Engineering Research Council of Canada; Leverhulme Trust","keywords":"Psychology; Outcome (game theory); Bridge (graph theory); Risk-seeking; Social psychology; Actuarial science; Microeconomics; Economics","score_opus":0.17018418784733802,"score_gpt":0.4379307702795981,"score_spread":0.26774658243226007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400855815","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9330366,0.00021156593,0.0037080783,0.00034549675,0.0014333416,0.000074096446,0.000027532476,0.0001470206,0.061016228],"genre_scores_gemma":[0.99781746,0.000013908124,0.00029859736,0.00015855777,0.00013998893,0.000007597905,0.00001200152,0.000008776903,0.0015431211],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9988412,0.000022964927,0.0003089797,0.00032990664,0.00037909497,0.0001178207],"domain_scores_gemma":[0.99914104,0.00043303863,0.000039859893,0.00022214236,0.00010628343,0.000057653953],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0010170876,0.000071375085,0.00010763453,0.00021706476,0.000078567165,0.0006157602,0.0001994069,0.000058305104,0.0016399679],"category_scores_gemma":[0.00040829257,0.000052527415,0.000101686994,0.00037120012,0.00003873246,0.00033618198,0.000049463375,0.00009875179,0.01564945],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000058387027,0.000014625574,0.0002160846,0.0000013269236,0.0000027757856,0.00002511484,0.000046027817,0.0000060489465,0.0001981375,0.00039143724,0.019180076,0.9799125],"study_design_scores_gemma":[0.00011235364,0.000049314374,0.0031855523,0.00006308071,0.000028717022,0.000036070243,0.00014991694,0.0031102987,0.0014403785,0.687899,0.30377898,0.0001463383],"about_ca_topic_score_codex":0.0000019998827,"about_ca_topic_score_gemma":0.000006150588,"teacher_disagreement_score":0.9797662,"about_ca_system_score_codex":0.000022617754,"about_ca_system_score_gemma":0.000035068533,"threshold_uncertainty_score":0.99927264},"labels":[],"label_agreement":null},{"id":"W4401031491","doi":"10.1177/10591478241265645","title":"Ups and Downs in Experience Design","year":2024,"lang":"en","type":"article","venue":"Production and Operations Management","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Valuation (finance); Event (particle physics); Computer science; A priori and a posteriori; Point (geometry); Target audience; Advertising; Psychology; Mathematics; Business; Epistemology","score_opus":0.1709372064768888,"score_gpt":0.41818925359745973,"score_spread":0.24725204712057094,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401031491","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96349,0.0006902901,0.026397804,0.0049623945,0.00096671307,0.00046051375,0.0000013376671,0.000061209175,0.0029697355],"genre_scores_gemma":[0.98491514,0.0003168184,0.006077483,0.000087595494,0.000045721332,0.0000617785,7.254546e-7,0.0000042973056,0.008490462],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989137,0.000050203977,0.00027191185,0.00048134758,0.00018434723,0.00009846387],"domain_scores_gemma":[0.9996443,0.00005193685,0.0000130042345,0.0002164194,0.000037830174,0.000036556623],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011768636,0.00006970655,0.000083144514,0.0003610028,0.00016060517,0.00093916146,0.00009954235,0.000019386156,0.00009723264],"category_scores_gemma":[0.00019579442,0.00005271595,0.000013566573,0.00044837245,0.000055206827,0.00056787155,0.000100913094,0.00005591935,0.000099949386],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008319301,0.0000462804,0.00066672143,0.0000075177695,0.0000048056404,0.000025287667,0.0025097888,0.0046445327,0.00009219093,0.016398193,0.0042318064,0.97136456],"study_design_scores_gemma":[0.00070303207,0.00027016684,0.054231636,0.0003210872,0.00007851459,0.0002457932,0.03796156,0.174057,0.0011342361,0.16749401,0.56236476,0.0011381743],"about_ca_topic_score_codex":0.000015941474,"about_ca_topic_score_gemma":0.000042993102,"teacher_disagreement_score":0.9702264,"about_ca_system_score_codex":0.000024782801,"about_ca_system_score_gemma":0.000009508058,"threshold_uncertainty_score":0.90563554},"labels":[],"label_agreement":null},{"id":"W4401101277","doi":"10.3389/frym.2024.1212103","title":"How Do Simple Games Help us to Understand Decision-Making?","year":2024,"lang":"en","type":"article","venue":"Frontiers for Young Minds","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Outcome (game theory); Simple (philosophy); Decision fatigue; Order (exchange); Energy (signal processing); Psychology; Computer science; Business decision mapping; Decision engineering; Economics; Microeconomics; Artificial intelligence; Decision support system; Mathematics; Epistemology","score_opus":0.05803270143153461,"score_gpt":0.36973157936087786,"score_spread":0.31169887792934325,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401101277","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.53055704,0.001358596,0.45663476,0.0011483704,0.008074131,0.00048454662,0.0003141378,0.00012476595,0.0013036558],"genre_scores_gemma":[0.94780886,0.000017616734,0.044637762,0.0002769582,0.00040227114,0.000038591428,0.0000119903825,0.00006895551,0.0067370036],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99593526,0.000053054635,0.00078283413,0.001321302,0.0012228694,0.0006846788],"domain_scores_gemma":[0.996661,0.001488702,0.00016227343,0.0010588705,0.0003068167,0.00032232175],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0020962982,0.0003721025,0.00063067244,0.0010445617,0.00035122375,0.0045795604,0.0013132599,0.00024361772,0.00021203313],"category_scores_gemma":[0.0026241126,0.00029091042,0.0005245502,0.0011471399,0.00012965538,0.0007826024,0.00025918047,0.00021394178,0.0003661685],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009692547,0.000021906764,0.0020619875,0.0000033855717,0.000023480547,0.000029194322,0.00059396145,0.00010654428,0.00002098913,0.00031907117,0.45641407,0.5403085],"study_design_scores_gemma":[0.0002900789,0.00025184394,0.00064813066,0.00011316632,0.00005856786,0.000035428446,0.0063546523,0.005711325,0.00009923014,0.30276436,0.6832238,0.000449434],"about_ca_topic_score_codex":0.000010092692,"about_ca_topic_score_gemma":0.000102494436,"teacher_disagreement_score":0.53985906,"about_ca_system_score_codex":0.00036826203,"about_ca_system_score_gemma":0.00019320694,"threshold_uncertainty_score":0.9999543},"labels":[],"label_agreement":null},{"id":"W4401176145","doi":"10.1080/1047840x.2024.2366773","title":"Social Projection Meets Social Reality: A Probabilistic Implementation of the Inductive Reasoning Model","year":2024,"lang":"en","type":"article","venue":"Psychological Inquiry","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Social Sciences and Humanities Research Council; Natural Sciences and Engineering Research Council of Canada","keywords":"Psychology; Probabilistic logic; Projection (relational algebra); Cognitive psychology; Social psychology; Cognitive science; Artificial intelligence; Computer science","score_opus":0.5401420870777613,"score_gpt":0.5801912568672705,"score_spread":0.04004916978950912,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401176145","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9908178,0.000018003038,0.0025476264,0.00322824,0.0011811468,0.00033065365,0.00002971433,0.0000701197,0.0017766888],"genre_scores_gemma":[0.99886686,0.000001935066,0.00042805407,0.00014874792,0.0003971168,0.000046796802,0.0000033962592,0.000010305948,0.000096763564],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9974331,0.0003130089,0.0007262441,0.0006361275,0.00067282026,0.00021866885],"domain_scores_gemma":[0.99895567,0.00029258116,0.00027001224,0.00026366647,0.00018301459,0.000035046392],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022577422,0.00013906928,0.00026362162,0.00013109561,0.00031561463,0.00024337482,0.0005025336,0.00019108568,0.00013894003],"category_scores_gemma":[0.0005573805,0.00008013093,0.00024172186,0.0008096528,0.00040581488,0.00026652197,0.00017280589,0.0002962735,0.000042884305],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007769885,0.00019329214,0.0006477261,0.000007615148,0.0000196249,0.0000037043303,0.011300777,0.00013805895,0.0008537581,0.02651136,0.022416763,0.9378296],"study_design_scores_gemma":[0.00033867327,0.0001789718,0.04974866,0.000035450495,0.00006120576,0.000017280414,0.007166979,0.009327628,0.00013423373,0.93020755,0.0025298516,0.00025354596],"about_ca_topic_score_codex":0.00003405342,"about_ca_topic_score_gemma":0.00002894955,"teacher_disagreement_score":0.93757606,"about_ca_system_score_codex":0.000120550554,"about_ca_system_score_gemma":0.000073231335,"threshold_uncertainty_score":0.32676443},"labels":[],"label_agreement":null},{"id":"W4401176186","doi":"10.1080/1047840x.2024.2366813","title":"Kahneman in Quotes and Reflections","year":2024,"lang":"en","type":"article","venue":"Psychological Inquiry","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University; University of Waterloo","funders":"","keywords":"Psychology; Cognitive psychology; Psychoanalysis; Epistemology; Social psychology; Cognitive science; Philosophy","score_opus":0.6025791707107563,"score_gpt":0.6101577821525156,"score_spread":0.007578611441759309,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401176186","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.981242,0.0005944587,0.0010869602,0.0017522124,0.0019118414,0.00006936248,0.000003819177,0.00010155528,0.013237769],"genre_scores_gemma":[0.9975727,0.00006361006,0.0011397591,0.00048401093,0.00017090628,0.00001140774,8.49338e-7,0.0000068757877,0.0005498828],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9982952,0.000101244514,0.00047885667,0.00067398325,0.0002524669,0.00019823888],"domain_scores_gemma":[0.99839014,0.0011039536,0.000037013277,0.00034573863,0.00003133416,0.000091840426],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0015431846,0.00010755433,0.00020130137,0.000350178,0.00007252759,0.00049172423,0.00031293422,0.00014053797,0.00073895976],"category_scores_gemma":[0.0008314023,0.0000686822,0.0000732018,0.0007641357,0.0002411879,0.00022725396,0.000104939405,0.00027169546,0.0011957453],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020757318,0.0001316433,0.004332316,0.0000014212893,0.0000026924884,0.00010412842,0.00069166714,0.00001726972,0.0005265763,0.004006164,0.019526754,0.97063863],"study_design_scores_gemma":[0.00016891788,0.00021446319,0.079560824,0.000042462765,0.000005619846,0.00011616127,0.00089974195,0.0005134868,0.000026234597,0.82074744,0.09749401,0.00021062444],"about_ca_topic_score_codex":0.0000089497935,"about_ca_topic_score_gemma":0.00004041112,"teacher_disagreement_score":0.970428,"about_ca_system_score_codex":0.000024774696,"about_ca_system_score_gemma":0.000008212782,"threshold_uncertainty_score":0.99958193},"labels":[],"label_agreement":null},{"id":"W4401335402","doi":"10.1037/cep0000342","title":"Updating local and global probabilities during maze navigation.","year":2024,"lang":"en","type":"article","venue":"Canadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Task (project management); ENCODE; Reliability (semiconductor); Computer science; PsycINFO; Representation (politics); Artificial intelligence; Cognitive psychology; Psychology; MEDLINE; Engineering; Political science","score_opus":0.08597934004897054,"score_gpt":0.3965047750507864,"score_spread":0.31052543500181584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401335402","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9828967,0.006499291,0.0003841138,0.001541355,0.0045449673,0.00021542436,0.00013932645,0.000037526734,0.0037413244],"genre_scores_gemma":[0.99671143,0.00001653532,0.002085242,0.0006367495,0.00028233067,0.000016421496,0.000008006332,0.00003639889,0.00020687582],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99623406,0.00020174279,0.0013630794,0.0009338494,0.00021785391,0.0010493993],"domain_scores_gemma":[0.9970243,0.00023829148,0.00036535802,0.0006533339,0.0001674759,0.0015512317],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0021776124,0.00036150592,0.00053796824,0.0006389135,0.00028907164,0.0006283209,0.0011416728,0.00026271257,0.00079639186],"category_scores_gemma":[0.00033455368,0.0003351793,0.00026162268,0.0006828899,0.0008620689,0.00071378896,0.00008248225,0.0005067043,0.00012968465],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00089255377,0.0008553131,0.15729485,0.0001408013,0.0006521615,0.023738177,0.051068462,0.00069322647,0.11262743,0.020367768,0.09487978,0.5367895],"study_design_scores_gemma":[0.007645267,0.004887141,0.13709664,0.0023007137,0.00024064952,0.09455901,0.21038881,0.0010890649,0.02337803,0.41027462,0.104282945,0.003857101],"about_ca_topic_score_codex":0.0021837451,"about_ca_topic_score_gemma":0.010605544,"teacher_disagreement_score":0.53293234,"about_ca_system_score_codex":0.0019311631,"about_ca_system_score_gemma":0.0005613303,"threshold_uncertainty_score":0.99991},"labels":[],"label_agreement":null},{"id":"W4401363623","doi":"10.1057/s41272-024-00499-1","title":"Tackling no-shows in fine dining: insights into cancellation policies and consumer awareness campaigns","year":2024,"lang":"en","type":"article","venue":"Journal of Revenue and Pricing Management","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Mount Royal University","funders":"Montclair State University","keywords":"Reservation; Popularity; Entitlement (fair division); Marketing; Equity (law); Dual (grammatical number); Honor; Business; Advertising; Public relations; Economics; Computer science; Psychology; Microeconomics; Internet privacy; Political science; Social psychology","score_opus":0.0684214481563083,"score_gpt":0.3858162681265433,"score_spread":0.317394819970235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401363623","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9938594,0.0038927773,0.000884007,0.00031556276,0.00065072544,0.000063544605,0.0000020976124,0.0000037884313,0.00032810165],"genre_scores_gemma":[0.99746037,0.001010389,0.0007472936,0.000067124274,0.000108228276,0.000001096522,3.4329415e-7,0.000006506289,0.000598646],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988412,0.000058471094,0.0005407819,0.00017781202,0.00027826775,0.00010345442],"domain_scores_gemma":[0.9991298,0.00039891497,0.0002216879,0.00011778742,0.000080140715,0.00005171217],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013662038,0.00008714655,0.00023386187,0.000508461,0.00008513869,0.00031957193,0.00013918574,0.00003488054,0.00001205228],"category_scores_gemma":[0.00016953635,0.00006308203,0.000040756277,0.00030480142,0.000035175126,0.0002593937,0.000100178986,0.00013807343,0.000009798008],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029653456,0.000019989937,0.03462762,0.00006137916,0.000028042858,0.0001849629,0.005154373,0.0010745248,0.0002582981,0.0002637297,0.00411192,0.9541855],"study_design_scores_gemma":[0.0011248741,0.0003686563,0.06903912,0.0032973827,0.00019123011,0.00014357314,0.0041228295,0.012646389,0.00024222658,0.13089426,0.777407,0.00052247406],"about_ca_topic_score_codex":0.0000863369,"about_ca_topic_score_gemma":0.00030328674,"teacher_disagreement_score":0.95366305,"about_ca_system_score_codex":0.000052070893,"about_ca_system_score_gemma":0.000032134114,"threshold_uncertainty_score":0.30816397},"labels":[],"label_agreement":null},{"id":"W4401613713","doi":"10.1037/dev0001817","title":"Children (and many adults) use perceptual similarity to assess relative impossibility.","year":2024,"lang":"en","type":"article","venue":"Developmental Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Psychology; Perception; Impossibility; Spell; Cognitive psychology; PsycINFO; Similarity (geometry); Object (grammar); Social perception; Developmental psychology; Social psychology; Artificial intelligence; Computer science; MEDLINE","score_opus":0.2218656612072493,"score_gpt":0.46263540366822625,"score_spread":0.24076974246097696,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401613713","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9930058,0.0000571355,0.0019189164,0.0011071053,0.0013752121,0.0003078353,0.0001210704,0.00010299117,0.0020038981],"genre_scores_gemma":[0.98284096,0.000014338261,0.014370518,0.0016620338,0.00008173499,0.000015125423,0.00002056902,0.00002266005,0.0009720753],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99683595,0.00017183993,0.00079901516,0.0013795798,0.00044790783,0.00036572272],"domain_scores_gemma":[0.99817246,0.0009392757,0.00007668732,0.0004532168,0.00010218005,0.00025619534],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0016279593,0.000248636,0.00036025533,0.00043676552,0.00018168161,0.00063697057,0.00059263804,0.00021876433,0.000867591],"category_scores_gemma":[0.000862533,0.00019645042,0.00010454799,0.0006161148,0.00021673311,0.00076389,0.00041299837,0.00037106022,0.0028285286],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018265047,0.00013810818,0.23580578,0.0000020835455,0.000042383945,0.0000768568,0.004010365,0.0000028138295,0.0003405715,0.00065925106,0.031396184,0.72734296],"study_design_scores_gemma":[0.00031808077,0.00012393873,0.9627043,0.00003706685,0.000010026412,0.0002663012,0.0005560921,0.00007377995,0.00003432258,0.020149045,0.0154193165,0.00030774626],"about_ca_topic_score_codex":0.000049356335,"about_ca_topic_score_gemma":0.000111503155,"teacher_disagreement_score":0.7270352,"about_ca_system_score_codex":0.00013389357,"about_ca_system_score_gemma":0.00009484779,"threshold_uncertainty_score":0.9979479},"labels":[],"label_agreement":null},{"id":"W4401765322","doi":"10.1108/ejm-04-2023-0258","title":"Slow and steady or fast and furious: how movement speed in the digital medium impacts consumers’ risk judgments","year":2024,"lang":"en","type":"article","venue":"European Journal of Marketing","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Feeling; Popularity; Originality; Movement (music); Marketing; Risk perception; Psychology; Business; Advertising; Social psychology; Perception; Creativity","score_opus":0.0725964418911302,"score_gpt":0.33038183093264034,"score_spread":0.25778538904151016,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401765322","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9932491,0.00081410597,0.000082526785,0.0014266187,0.0005313499,0.00008567577,0.000023525328,0.000008004479,0.0037790805],"genre_scores_gemma":[0.9987684,0.00031899975,0.0002359186,0.00016808056,0.00012683419,1.2446252e-7,3.830206e-7,0.000018532133,0.0003627259],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99648273,0.0014489272,0.0008131922,0.00027920134,0.0007471273,0.0002288325],"domain_scores_gemma":[0.9946325,0.004429342,0.00050859206,0.0002009992,0.000077092256,0.00015150041],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.027497437,0.00015650579,0.00026837437,0.00030936525,0.00012116155,0.0029148299,0.0004825678,0.00002034672,0.00004922094],"category_scores_gemma":[0.007441748,0.00008065175,0.00008153874,0.00026299985,0.000105667255,0.0005658053,0.00021300848,0.00040569765,0.000027045935],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033786273,0.000038735656,0.040472634,0.00000888107,0.000028691162,0.001431704,0.0020780088,0.000013385862,0.00015779144,0.000001819344,0.0057214405,0.94970906],"study_design_scores_gemma":[0.0024491623,0.00088281865,0.90310735,0.0015884453,0.00011837205,0.0015670918,0.03333361,0.0016523778,0.000038974667,0.0014791267,0.05329091,0.0004917393],"about_ca_topic_score_codex":0.000002252902,"about_ca_topic_score_gemma":0.000007357844,"teacher_disagreement_score":0.9492173,"about_ca_system_score_codex":0.00003604815,"about_ca_system_score_gemma":0.000057973215,"threshold_uncertainty_score":0.99812025},"labels":[],"label_agreement":null},{"id":"W4401931553","doi":"10.1002/bdm.2407","title":"Reference‐Dependent Risk‐Taking in the NBA","year":2024,"lang":"en","type":"article","venue":"Journal of Behavioral Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Point (geometry); Prospect theory; Econometrics; Quarter (Canadian coin); Reference model; Psychology; Computer science; Statistics; Economics; Mathematics; Microeconomics; Geography","score_opus":0.23926284374588752,"score_gpt":0.4892373095558045,"score_spread":0.249974465809917,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401931553","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9862411,0.0011633717,0.007453742,0.00026586346,0.0034265858,0.00017299181,0.000025119929,0.000027514176,0.0012237289],"genre_scores_gemma":[0.992337,0.00011259698,0.006910908,0.0001636506,0.00035150797,0.000004551779,5.516426e-7,0.00003252417,0.000086702166],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99162596,0.00064793223,0.003104411,0.0006384556,0.0035041226,0.00047909314],"domain_scores_gemma":[0.98920137,0.006824191,0.0023504787,0.0009517891,0.0005326117,0.00013954382],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.017586632,0.00033188818,0.00073802914,0.001840696,0.0002799627,0.0027676318,0.0028124521,0.00024393752,0.0009901173],"category_scores_gemma":[0.0036736098,0.00018422974,0.0005898977,0.0017846588,0.00010616269,0.0012925353,0.00031348734,0.0016869545,0.00050454034],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014142507,0.00016175296,0.011703251,0.000001800948,0.000006681979,0.0014212684,0.0012420182,0.0009883957,0.000121039135,0.00027195894,0.004094623,0.97984576],"study_design_scores_gemma":[0.0017280054,0.0014064214,0.15901393,0.0029821496,0.0003997318,0.0046022437,0.014893098,0.0059838057,0.000106425374,0.7308099,0.076953046,0.0011211967],"about_ca_topic_score_codex":0.00005128433,"about_ca_topic_score_gemma":0.00021913905,"teacher_disagreement_score":0.9787246,"about_ca_system_score_codex":0.0002768627,"about_ca_system_score_gemma":0.00024932643,"threshold_uncertainty_score":0.9999231},"labels":[],"label_agreement":null},{"id":"W4401989579","doi":"10.2139/ssrn.4940588","title":"Robust Inattentive Discrete Choice","year":2024,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Quest University Canada","funders":"","keywords":"Computer science","score_opus":0.09152516552525311,"score_gpt":0.3837529709345422,"score_spread":0.29222780540928905,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401989579","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9447496,0.0046419953,0.03897783,0.0030942096,0.0024276609,0.00009673292,0.000011439948,0.000088030785,0.005912536],"genre_scores_gemma":[0.9880891,0.0006238758,0.00016445345,0.000105050356,0.00054300233,0.0000028509078,0.0000015490804,0.000027052201,0.01044308],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9960649,0.00013964895,0.00068644213,0.00051466783,0.000860544,0.0017337708],"domain_scores_gemma":[0.9983221,0.00081020687,0.00017589472,0.0003646873,0.00018438823,0.0001426702],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0067266477,0.00018982361,0.0002750738,0.00046564263,0.0002988386,0.00147263,0.0010229911,0.00009824969,0.0005183124],"category_scores_gemma":[0.0009231695,0.00012778207,0.00031902007,0.0007263221,0.00008122966,0.0008597169,0.00013533776,0.0021397641,0.003221787],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018145078,0.000028166582,0.0011249885,9.705403e-7,0.000055594395,0.000033081473,0.00013836104,0.00033318336,0.00006736933,0.039211452,0.0045832493,0.9544054],"study_design_scores_gemma":[0.00018004028,0.00013039312,0.00049232494,0.000038066435,0.00003431013,0.0006439327,0.0018986673,0.001882329,0.000018679566,0.91919094,0.075289026,0.00020128168],"about_ca_topic_score_codex":0.000040685187,"about_ca_topic_score_gemma":0.00070083374,"teacher_disagreement_score":0.95420414,"about_ca_system_score_codex":0.0008302459,"about_ca_system_score_gemma":0.0015027286,"threshold_uncertainty_score":0.99956393},"labels":[],"label_agreement":null},{"id":"W4402711270","doi":"10.1002/cjas.1767","title":"The erosion of rationality in high vulnerability conditions: A cognitive‐disruption perspective","year":2024,"lang":"en","type":"article","venue":"Canadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l Administration","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Rationality; Perspective (graphical); Vulnerability (computing); Cognition; Erosion; Psychology; Cognitive psychology; Cognitive science; Computer science; Epistemology; Geology; Computer security; Philosophy; Neuroscience; Geomorphology; Artificial intelligence","score_opus":0.2494642723321248,"score_gpt":0.4555875936148406,"score_spread":0.2061233212827158,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402711270","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9905674,0.000686206,0.0014118557,0.0032449472,0.0010767651,0.00026597077,0.00024891412,0.0000068284803,0.002491142],"genre_scores_gemma":[0.9985691,0.000030482908,0.0010839541,0.000053598156,0.00013534784,0.00001203609,0.0000050984977,0.0000067965266,0.00010358531],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99570227,0.00073323754,0.0016054984,0.0006720416,0.000647579,0.0006393532],"domain_scores_gemma":[0.99247235,0.004141996,0.00083372864,0.00025417397,0.0016027968,0.0006949757],"candidate_categories":["metaresearch","sts","scholarly_communication"],"consensus_categories":["sts"],"category_scores_codex":[0.015496371,0.00022436453,0.00040334198,0.001056063,0.001761371,0.0015657651,0.0012393695,0.00012480722,0.00021929755],"category_scores_gemma":[0.011217658,0.00015849569,0.00021428734,0.0032249552,0.009320799,0.0017820796,0.00002217994,0.00043429816,0.000011592075],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026776872,0.0002973704,0.085687384,0.000051746258,0.000053404226,0.00071358663,0.03923212,0.0038629894,0.0020728284,0.790543,0.000825399,0.07639236],"study_design_scores_gemma":[0.00022546633,0.0025419637,0.10090517,0.0006220296,0.000033117307,0.00073176745,0.051388226,0.0040036063,0.00078259787,0.8381972,0.00031690416,0.00025199144],"about_ca_topic_score_codex":0.008791138,"about_ca_topic_score_gemma":0.521615,"teacher_disagreement_score":0.5128239,"about_ca_system_score_codex":0.0016440649,"about_ca_system_score_gemma":0.015206685,"threshold_uncertainty_score":0.9995382},"labels":[],"label_agreement":null},{"id":"W4402905276","doi":"10.1186/s12911-024-02681-2","title":"Decision threshold models in medical decision making: a scoping literature review","year":2024,"lang":"en","type":"article","venue":"BMC Medical Informatics and Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ottawa Hospital; Thompson Rivers University; University of Ottawa","funders":"University of Ottawa","keywords":"Health informatics; Medical decision making; Computer science; Management science; Data science; Decision analysis; Clinical decision making; Medicine; Public health; Medical emergency; Nursing; Family medicine; Engineering","score_opus":0.12242197308065546,"score_gpt":0.44994233850075793,"score_spread":0.3275203654201025,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402905276","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20480172,0.06310233,0.7256261,0.00020558905,0.0025641029,0.00072214316,0.000025447782,0.00016593497,0.0027866466],"genre_scores_gemma":[0.53689516,0.061592817,0.39255378,0.008238695,0.00048605644,0.00007341816,0.0000127927415,0.00010239271,0.000044865345],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.982672,0.00020136576,0.005885184,0.0011941649,0.009122314,0.0009249874],"domain_scores_gemma":[0.96443224,0.03192103,0.0006345404,0.001596996,0.000467723,0.0009474751],"candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.021408223,0.0006960557,0.0016421187,0.002038843,0.00035366922,0.0030978026,0.0025373925,0.0010541852,0.0021546904],"category_scores_gemma":[0.02482771,0.00046132103,0.0005348294,0.0034276969,0.00028018845,0.0024597964,0.0020836194,0.0016801667,0.000611795],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016326141,0.00006806074,0.00024559558,0.00066467986,0.0000080298605,0.0005645336,0.0004232155,0.0011502387,2.3115761e-7,0.0021483316,0.0121943485,0.9823695],"study_design_scores_gemma":[0.0005079874,0.00005462527,0.0000671148,0.1816481,0.000018573232,0.0006251903,0.00017844015,0.5387227,3.4427566e-7,0.27518496,0.002635673,0.00035628228],"about_ca_topic_score_codex":0.000002744524,"about_ca_topic_score_gemma":0.00022856194,"teacher_disagreement_score":0.98201317,"about_ca_system_score_codex":0.00018631709,"about_ca_system_score_gemma":0.0012280212,"threshold_uncertainty_score":0.9997839},"labels":[],"label_agreement":null},{"id":"W4402905744","doi":"10.1167/jov.24.10.954","title":"Object Stability, Attention, and Temporal Order Judgments","year":2024,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Object (grammar); Cognitive psychology; Stability (learning theory); Order (exchange); Psychology; Computer science; Cognitive science; Artificial intelligence; Machine learning; Economics","score_opus":0.10833816126190135,"score_gpt":0.4263056248485938,"score_spread":0.3179674635866925,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402905744","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9944257,0.00074113504,0.0014544423,0.0010349633,0.0018173486,0.0000553124,0.000006040761,0.000012733598,0.0004523148],"genre_scores_gemma":[0.99735934,0.00006452032,0.002028325,0.00006541453,0.00014561106,3.1372207e-7,5.8520885e-7,0.000009632552,0.0003262419],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9975169,0.00011191282,0.001028278,0.00027169535,0.0009374557,0.00013380391],"domain_scores_gemma":[0.9982529,0.00058172806,0.00031299054,0.00024539506,0.00047438714,0.0001325921],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0044640405,0.000108597415,0.0002851094,0.0004150519,0.000093747614,0.0008636073,0.00033136926,0.00007214302,0.0005096474],"category_scores_gemma":[0.00090407906,0.00006647023,0.00016361526,0.0004800918,0.00006541958,0.00086837786,0.00014592137,0.00022990721,0.00017470287],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008232465,0.00014408925,0.05952546,0.000008981912,0.000018665496,0.000113969036,0.0002783158,0.000019410505,0.003052236,0.00006693963,0.020071678,0.91661793],"study_design_scores_gemma":[0.001608402,0.0024689552,0.44747257,0.0010002693,0.0001422658,0.0011626309,0.0022665956,0.007051664,0.00050659286,0.3106444,0.22507477,0.0006009103],"about_ca_topic_score_codex":0.00000918771,"about_ca_topic_score_gemma":0.00001425471,"teacher_disagreement_score":0.916017,"about_ca_system_score_codex":0.00006122188,"about_ca_system_score_gemma":0.000114231785,"threshold_uncertainty_score":0.8327785},"labels":[],"label_agreement":null},{"id":"W4403940482","doi":"10.2139/ssrn.4963318","title":"Overcoming Algorithmic Exclusion: Evidence from A Large-Scale Randomized Field Experiment on Human versus AI Decision-Making","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Quest University Canada","funders":"","keywords":"Scale (ratio); Randomized experiment; Field (mathematics); Computer science; Data science; Mathematics; Physics; Statistics","score_opus":0.0837047906517912,"score_gpt":0.43764472774432506,"score_spread":0.35393993709253385,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403940482","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8992551,0.015626322,0.069115646,0.002023135,0.012152738,0.0008366444,0.000052765074,0.00013589577,0.00080173876],"genre_scores_gemma":[0.9909427,0.002558153,0.0031174081,0.0004789329,0.0021689122,0.00007856114,0.000008598162,0.0001112244,0.00053548877],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9875303,0.0010060753,0.0030971426,0.0022322556,0.0032373704,0.0028968693],"domain_scores_gemma":[0.978963,0.016632216,0.0015641295,0.0020574408,0.0004667771,0.0003164175],"candidate_categories":["metaepi_narrow","scholarly_communication","research_integrity","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.021590555,0.00095155777,0.0022515932,0.0011861441,0.0010417227,0.0029625248,0.0036421178,0.000845137,0.0015533307],"category_scores_gemma":[0.0070691435,0.00070971117,0.0020465783,0.00051131,0.0001415876,0.00045291812,0.004111596,0.010624406,0.00095808075],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.039630525,0.00034669836,0.000071055656,0.000010851415,0.00047759505,0.00023644228,0.002780539,0.0026067228,0.000205748,0.0042606113,0.0051989714,0.94417423],"study_design_scores_gemma":[0.018281896,0.0005355699,0.000009824219,0.0033245012,0.0003078426,0.00009173045,0.0025969,0.009283945,0.00015945424,0.9633927,0.001218848,0.00079683855],"about_ca_topic_score_codex":0.00027536383,"about_ca_topic_score_gemma":0.0011960902,"teacher_disagreement_score":0.959132,"about_ca_system_score_codex":0.0036396778,"about_ca_system_score_gemma":0.0035410293,"threshold_uncertainty_score":0.9998198},"labels":[],"label_agreement":null},{"id":"W4404172412","doi":"10.1145/3687056","title":"The Explanation That Hits Home: The Characteristics of Verbal Explanations That Affect Human Perception in Subjective Decision-Making","year":2024,"lang":"en","type":"article","venue":"Proceedings of the ACM on Human-Computer Interaction","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Affect (linguistics); Perception; Psychology; Cognitive psychology; Social psychology; Communication; Neuroscience","score_opus":0.1406993841255649,"score_gpt":0.42339952409040893,"score_spread":0.282700139964844,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404172412","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99451977,0.000026474132,0.00042310703,0.00088633184,0.0029261815,0.00043328133,0.000019942481,0.000047043457,0.00071788154],"genre_scores_gemma":[0.99918234,0.000019640947,0.00026673285,0.000073361545,0.00029231905,0.00003788503,0.0000047575463,0.000025090092,0.000097840006],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9969679,0.00009042877,0.00094967807,0.0005798317,0.0011671075,0.00024502023],"domain_scores_gemma":[0.9937551,0.0041386937,0.00091673527,0.00072203495,0.00043289515,0.000034564586],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0027974814,0.00025507764,0.00035767473,0.0006191122,0.0006524118,0.0010717746,0.0024820906,0.0001101768,0.00007282614],"category_scores_gemma":[0.0012702313,0.00013481213,0.00030787633,0.0006894899,0.00016543073,0.0011327182,0.0006541716,0.00054484303,0.000045203942],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002539343,0.00020455543,0.019115714,0.000030148083,0.00005735484,0.000002554655,0.008256642,0.00020448673,0.006247323,0.0041645723,0.009914018,0.9515487],"study_design_scores_gemma":[0.0004906156,0.0004260645,0.7679714,0.0023998136,0.000089969486,0.0000659921,0.008211303,0.01667256,0.0040545417,0.19599542,0.0031749543,0.00044739136],"about_ca_topic_score_codex":0.00003521659,"about_ca_topic_score_gemma":0.000107449596,"teacher_disagreement_score":0.9511013,"about_ca_system_score_codex":0.00035452354,"about_ca_system_score_gemma":0.000031136053,"threshold_uncertainty_score":0.9999652},"labels":[],"label_agreement":null},{"id":"W4404256573","doi":"10.2139/ssrn.5013140","title":"The Role of Mixed Discounting in Risk-Averse Sequential Decision-Making","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Discounting; Delay discounting; Economics; Actuarial science; Microeconomics; Finance","score_opus":0.02885405331500812,"score_gpt":0.3631262227069926,"score_spread":0.33427216939198445,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404256573","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9813741,0.00989173,0.0030629204,0.00019802676,0.004117407,0.00023814243,0.00004523651,0.000027139324,0.0010453095],"genre_scores_gemma":[0.9950796,0.003603872,0.00052060786,0.000009322302,0.0005037745,0.000009258649,0.0000018444131,0.000057787955,0.00021396666],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9914976,0.0005797871,0.0026853974,0.0009654921,0.0019384518,0.0023333146],"domain_scores_gemma":[0.9921277,0.0038676222,0.0023123648,0.0011874771,0.00040066423,0.0001041397],"candidate_categories":["metaepi_narrow","scholarly_communication","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.028726088,0.00045377066,0.0008421582,0.0009757208,0.0005308853,0.0017572717,0.0032011424,0.00041381532,0.000082073355],"category_scores_gemma":[0.005479119,0.0002860865,0.00088799815,0.000755605,0.00021169677,0.00024862532,0.0025378051,0.009190604,0.00025968938],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001471621,0.00005080154,0.004329889,0.000002899042,0.00009071386,0.000021179641,0.00028872213,0.004930349,0.000033003893,0.010084559,0.00013381033,0.9798869],"study_design_scores_gemma":[0.00023044384,0.00007207877,0.0004963798,0.0004743271,0.00009662981,0.00017426186,0.006835072,0.006834102,0.00003070091,0.98145384,0.0030026701,0.00029947658],"about_ca_topic_score_codex":0.00029942335,"about_ca_topic_score_gemma":0.010592165,"teacher_disagreement_score":0.97958744,"about_ca_system_score_codex":0.0017754481,"about_ca_system_score_gemma":0.005436463,"threshold_uncertainty_score":0.9999591},"labels":[],"label_agreement":null},{"id":"W4404412063","doi":"10.1073/pnas.2311714121","title":"Predecisional information search adaptively reduces three types of uncertainty","year":2024,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Banco Bilbao Vizcaya Argentaria; Max-Planck-Gesellschaft; Stiftung Suzanne und Hans Biäsch zur Förderung der Angewandten Psychologie; Saskatoon City Hospital Foundation; Agencia Estatal de Investigación; Ministerio de Ciencia, Innovación y Universidades; Fundación BBVA; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Ministerio de Asuntos Económicos y Transformación Digital, Gobierno de España; National Science Foundation","keywords":"Computer science; Task (project management); Information seeking; Selection (genetic algorithm); Information needs; Data science; Information retrieval; Machine learning; Economics; World Wide Web","score_opus":0.2097191521168497,"score_gpt":0.4257227571208137,"score_spread":0.216003605003964,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404412063","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9878486,0.00018046511,0.000020977683,0.0021808876,0.00010773637,0.00015113322,0.00010935695,0.00001330078,0.00938759],"genre_scores_gemma":[0.99766755,0.000017799048,0.0020611319,0.00006009605,0.000054483215,0.000003977992,2.1986962e-7,0.0000028367513,0.00013190234],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9948564,0.0000130353055,0.0010045144,0.00030512325,0.0036674067,0.00015347457],"domain_scores_gemma":[0.9967854,0.0014017586,0.0005625886,0.000020444353,0.0011849826,0.00004479486],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0072663273,0.00010711959,0.00024801982,0.00067278784,0.00017146225,0.00020738775,0.001937567,0.00010312147,0.000111180045],"category_scores_gemma":[0.0034405547,0.000059867605,0.00017264493,0.0020199525,0.0010682151,0.0020517295,0.00034661716,0.00019844383,0.000029492736],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020413469,0.00014948643,0.0063000764,0.000084313746,0.000059964725,3.415548e-8,0.0018631234,0.019751566,0.06607557,0.2796091,0.021280758,0.6046218],"study_design_scores_gemma":[0.00012555685,0.00012430716,0.040708825,0.0003117836,0.000015468137,0.000011334949,0.0009287444,0.040992305,0.050350595,0.8630739,0.0032271305,0.00013006435],"about_ca_topic_score_codex":0.00001548334,"about_ca_topic_score_gemma":3.10748e-7,"teacher_disagreement_score":0.6044918,"about_ca_system_score_codex":0.00004931204,"about_ca_system_score_gemma":0.00019236651,"threshold_uncertainty_score":0.4118914},"labels":[],"label_agreement":null},{"id":"W4404550038","doi":"10.1017/jdm.2024.25","title":"Sunk cost predictions as theory of mind","year":2024,"lang":"en","type":"article","venue":"Judgment and Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Sunk costs; Psychology; Social psychology; Economics; Econometrics; Cognitive psychology; Microeconomics","score_opus":0.13015267607432443,"score_gpt":0.4225366530408995,"score_spread":0.29238397696657503,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404550038","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9377269,0.0013830281,0.043016296,0.00016244591,0.0018768025,0.00023711676,0.000047224905,0.0000509761,0.015499182],"genre_scores_gemma":[0.9920098,0.000079666075,0.0066761905,0.0001190839,0.000115559604,0.000010710265,0.0000016598203,0.000017841265,0.00096947054],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9969812,0.00008062309,0.0009967978,0.00066967413,0.0010327402,0.00023894491],"domain_scores_gemma":[0.9929632,0.0060018767,0.00018795881,0.00056913256,0.00015571674,0.00012209304],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0035202545,0.00018515917,0.00035524243,0.00070819433,0.00019587248,0.0007455781,0.0004528535,0.00012827489,0.0021859433],"category_scores_gemma":[0.0015183826,0.00013046559,0.0001998523,0.0006859485,0.00014341855,0.000432024,0.00030691276,0.00018861161,0.0008364079],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010007752,0.000043523065,0.0010232045,0.0000031088414,0.000012590478,0.000028000743,0.0003049435,0.00017920653,0.00009640236,0.007942496,0.00679851,0.98346794],"study_design_scores_gemma":[0.00026059488,0.00012954924,0.0027967838,0.00043470348,0.000050868563,0.00006656531,0.0013773014,0.009590334,0.00016095699,0.911318,0.07360715,0.00020717482],"about_ca_topic_score_codex":0.0000039701376,"about_ca_topic_score_gemma":0.0000101483865,"teacher_disagreement_score":0.98326075,"about_ca_system_score_codex":0.00005320695,"about_ca_system_score_gemma":0.000087764005,"threshold_uncertainty_score":0.9999415},"labels":[],"label_agreement":null},{"id":"W4404601743","doi":"10.1017/jdm.2024.30","title":"Assessing patience and predictivity validity for mixed sign intertemporal choices","year":2024,"lang":"en","type":"article","venue":"Judgment and Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Patience; Sign (mathematics); Psychology; Social psychology; Economics; Mathematics","score_opus":0.24662188510376168,"score_gpt":0.45407229753884804,"score_spread":0.20745041243508636,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404601743","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.815989,0.00049013,0.18077049,0.00013193699,0.0018276165,0.00026795958,0.00002723088,0.00008246309,0.00041314622],"genre_scores_gemma":[0.97829634,0.000030472163,0.02123531,0.00012695385,0.00018159872,0.000026356674,0.000002113415,0.000019574712,0.00008129025],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99689186,0.00010008154,0.0008563337,0.0010274324,0.0008159651,0.00030833294],"domain_scores_gemma":[0.98984253,0.009240704,0.00023532142,0.00039137923,0.00014653303,0.00014352567],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0043436936,0.0002464765,0.00042425195,0.00042509014,0.00041245346,0.0044224546,0.00037763428,0.00013488892,0.00007145371],"category_scores_gemma":[0.0020716912,0.00017516498,0.00014892335,0.0003758385,0.00012954489,0.0018450891,0.0004156912,0.00018477191,0.000030451254],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006695563,0.000035680703,0.009317664,0.000012366178,0.0000063767493,0.000011453902,0.00018313913,0.000029245413,0.00012062007,0.0002509952,0.0037730944,0.9861924],"study_design_scores_gemma":[0.00069893216,0.00042405984,0.042797476,0.0010424608,0.000072666095,0.00004646685,0.0012009946,0.2018794,0.00020660018,0.7183502,0.032697998,0.00058277196],"about_ca_topic_score_codex":0.00000788436,"about_ca_topic_score_gemma":0.000026397955,"teacher_disagreement_score":0.98560965,"about_ca_system_score_codex":0.00006654318,"about_ca_system_score_gemma":0.000065256114,"threshold_uncertainty_score":0.99661106},"labels":[],"label_agreement":null},{"id":"W4404620139","doi":"10.1111/deci.12658","title":"Explanation seeking and anomalous recommendation adherence in human‐to‐human versus human‐to‐artificial intelligence interactions","year":2024,"lang":"en","type":"article","venue":"Decision Sciences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Saint Mary's University; Queen's University","funders":"","keywords":"Loss aversion; Set (abstract data type); Sunk costs; Preference; Computer science; Recommender system; Risk aversion (psychology); Bayesian inference; Human intelligence; Psychology; Artificial intelligence; Bayesian probability; Machine learning; Microeconomics; Economics; Expected utility hypothesis","score_opus":0.42825543025349877,"score_gpt":0.5369649849622157,"score_spread":0.1087095547087169,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404620139","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95025474,0.000037239854,0.04247229,0.0011008993,0.002855089,0.00033330472,0.000023883009,0.00009030375,0.0028322483],"genre_scores_gemma":[0.9943012,0.0000059236913,0.0051670484,0.00016496197,0.00015235308,0.000037988564,0.000008816449,0.000015142224,0.00014659451],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99508256,0.0001584239,0.001546199,0.0015277012,0.0012430613,0.00044204274],"domain_scores_gemma":[0.99531937,0.0034568629,0.00021677685,0.0004874812,0.00024908854,0.00027040578],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0064722076,0.00026590616,0.00037672083,0.002760384,0.0010816681,0.0032995765,0.0012215552,0.00010423113,0.0011249566],"category_scores_gemma":[0.0025309594,0.00022019495,0.0001022271,0.0036713637,0.00022984055,0.0016429351,0.0004983136,0.00031049122,0.0010996886],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000044273933,0.00006227806,0.0010179902,0.0000015963658,0.0000025307213,0.00001799149,0.0013652353,0.00057316123,0.0043242592,0.008265671,0.0016359314,0.9826891],"study_design_scores_gemma":[0.0004115217,0.0023783664,0.01808347,0.0008831272,0.000031486514,0.00006657654,0.013609317,0.03929663,0.0031428046,0.8792916,0.041419126,0.0013859716],"about_ca_topic_score_codex":0.00028700565,"about_ca_topic_score_gemma":0.0035404684,"teacher_disagreement_score":0.9813031,"about_ca_system_score_codex":0.00021630737,"about_ca_system_score_gemma":0.00009576217,"threshold_uncertainty_score":0.99978817},"labels":[],"label_agreement":null},{"id":"W4404637470","doi":"10.1017/jdm.2024.17","title":"Can simulated experience be harnessed to help people make investment decisions?","year":2024,"lang":"en","type":"article","venue":"Judgment and Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Saskatoon City Hospital Foundation","keywords":"Investment (military); Investment decisions; Business; Psychology; Marketing; Behavioral economics; Finance; Political science","score_opus":0.13787098019811217,"score_gpt":0.4121460722090689,"score_spread":0.27427509201095673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404637470","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97676307,0.0006193836,0.015949538,0.0024121588,0.0024255873,0.0005455735,0.00005258514,0.00021320063,0.0010188911],"genre_scores_gemma":[0.98190784,0.000062293984,0.01316331,0.0039631547,0.00014564052,0.00004128831,0.0000053272647,0.00005189556,0.00065925944],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9935506,0.000111735135,0.0016263445,0.00177613,0.0022674182,0.0006677818],"domain_scores_gemma":[0.9911174,0.00653159,0.00021267502,0.0012886628,0.00029121508,0.00055846374],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0026226537,0.0004829482,0.00072697666,0.0013079458,0.0008243828,0.002670707,0.001110761,0.00021256314,0.0010271476],"category_scores_gemma":[0.003698355,0.0003571342,0.0002668249,0.002246664,0.00009565054,0.00049461576,0.001449536,0.00030556775,0.0007285089],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016766299,0.00008913828,0.0026252728,0.0000039100905,0.000014613957,0.00014522682,0.004364976,0.0031600748,0.00045193426,0.0014482727,0.0151203945,0.97240853],"study_design_scores_gemma":[0.001153597,0.00045330744,0.014371414,0.0015038359,0.00007796227,0.0001335708,0.005959546,0.098022394,0.000526358,0.5490309,0.32723415,0.0015329767],"about_ca_topic_score_codex":0.000046136778,"about_ca_topic_score_gemma":0.00043514255,"teacher_disagreement_score":0.97087556,"about_ca_system_score_codex":0.0002294939,"about_ca_system_score_gemma":0.00014718714,"threshold_uncertainty_score":0.99988806},"labels":[],"label_agreement":null},{"id":"W4404644679","doi":"10.1017/jdm.2024.22","title":"Individual differences in overconfidence: A new measurement approach","year":2024,"lang":"en","type":"article","venue":"Judgment and Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"Social Sciences and Humanities Research Council of Canada; John Templeton Foundation","keywords":"Overconfidence effect; Psychology; Econometrics; Social psychology; Cognitive psychology; Statistics; Economics; Mathematics","score_opus":0.28457660396373097,"score_gpt":0.39786234791837083,"score_spread":0.11328574395463986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404644679","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9474083,0.0034581744,0.04349502,0.00025826736,0.001236235,0.00027640167,0.0000092979,0.00007938134,0.0037788749],"genre_scores_gemma":[0.9850369,0.00008322802,0.014263396,0.00020901271,0.00015989502,0.000013746429,9.056572e-7,0.000017329721,0.00021556867],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9944675,0.000092482784,0.0011463827,0.0010959848,0.002805535,0.00039213576],"domain_scores_gemma":[0.99716777,0.0018743195,0.00015480968,0.0005126866,0.000104386505,0.00018601246],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0056456816,0.00028318717,0.0005063528,0.0010239613,0.00015229752,0.0026970601,0.0007838423,0.00016192318,0.00047450114],"category_scores_gemma":[0.0012848752,0.00019502228,0.00015624154,0.0009929485,0.000072271876,0.0006622026,0.00045082407,0.0003296517,0.0002793851],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000051294515,0.000055849923,0.009954899,0.0000049309137,0.000009999509,0.000035054352,0.0007503953,0.000067803005,0.000033271303,0.0014436208,0.010186306,0.97740656],"study_design_scores_gemma":[0.0007030078,0.00013200675,0.07194483,0.0009995986,0.000041593292,0.000054783264,0.0018584662,0.02434974,0.000021728085,0.8853201,0.0140204625,0.00055363856],"about_ca_topic_score_codex":0.00004125352,"about_ca_topic_score_gemma":0.00008252226,"teacher_disagreement_score":0.97685295,"about_ca_system_score_codex":0.0001419944,"about_ca_system_score_gemma":0.00020653805,"threshold_uncertainty_score":0.9983382},"labels":[],"label_agreement":null},{"id":"W4404993706","doi":"10.1080/02699931.2024.2434149","title":"Up and down: counterfactual closeness is robust to direction of comparison","year":2024,"lang":"en","type":"article","venue":"Cognition & Emotion","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Counterfactual thinking; Closeness; Psychology; Social psychology; Luck; Outcome (game theory); Cognitive psychology; Developmental psychology; Economics; Mathematics; Microeconomics","score_opus":0.20871989929752488,"score_gpt":0.42354975180620025,"score_spread":0.21482985250867537,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404993706","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9527646,0.00014748807,0.042754184,0.00052470283,0.0020509737,0.00016488426,0.000092656395,0.00007404302,0.0014265227],"genre_scores_gemma":[0.998759,0.000029982093,0.0004112861,0.0001419594,0.00010510017,0.000006472084,0.000024630404,0.000011478165,0.0005100909],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99818027,0.000080376856,0.0006226453,0.00048355846,0.00049849454,0.00013462524],"domain_scores_gemma":[0.9987706,0.0004386539,0.00013324834,0.00021589507,0.00034975118,0.00009188663],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010946189,0.00012427689,0.00025553044,0.00041941344,0.000105725565,0.00042065844,0.00013620146,0.000099517645,0.00067568436],"category_scores_gemma":[0.00039604952,0.000105088366,0.00007862046,0.0005284726,0.00006479676,0.0004568401,0.000065741566,0.00010951969,0.0007281753],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000054446795,0.000055730565,0.00065057125,0.000012968743,0.000008149904,0.0000016837664,0.0011279125,0.00022325067,0.0024400807,0.000113008755,0.0131571265,0.9821551],"study_design_scores_gemma":[0.0028548464,0.0022465303,0.11213964,0.0027235968,0.0006239228,0.000264223,0.015445662,0.1680861,0.10798388,0.2225539,0.3628561,0.0022216013],"about_ca_topic_score_codex":0.000023877228,"about_ca_topic_score_gemma":0.000023038832,"teacher_disagreement_score":0.97993344,"about_ca_system_score_codex":0.00004880421,"about_ca_system_score_gemma":0.000031811607,"threshold_uncertainty_score":0.9359463},"labels":[],"label_agreement":null},{"id":"W4405353140","doi":"10.31234/osf.io/r5n6f","title":"Throwing good effort after bad: Evidence for a sunk-cost effect in cognitive effort-based decision-making","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Sunk costs; Throwing; Cognition; Cognitive psychology; Psychology; Economics; Microeconomics; Computer science; Social psychology; Engineering","score_opus":0.16579791328911866,"score_gpt":0.47948252502366395,"score_spread":0.3136846117345453,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405353140","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9572931,0.0014034692,0.02862433,0.00030265297,0.00520021,0.004274331,0.00036512586,0.00024380698,0.0022929667],"genre_scores_gemma":[0.98397285,0.000022381864,0.012188288,0.0007974163,0.00033444894,0.0020619624,0.00002468874,0.00014809231,0.00044985398],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98943514,0.000262865,0.0031066786,0.003780776,0.0022583492,0.0011561977],"domain_scores_gemma":[0.9448157,0.05142888,0.00076044915,0.001992535,0.0006930282,0.0003094106],"candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.013705255,0.0011747228,0.0021598113,0.0021559913,0.00024006118,0.0030843401,0.0024618388,0.0010823514,0.0015600696],"category_scores_gemma":[0.019356681,0.00086500664,0.0017429113,0.0012005991,0.00023588698,0.00048636546,0.0034106872,0.0017760998,0.0014794056],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0025490415,0.00022048314,0.05492717,0.00017972582,0.00007067435,0.000435127,0.00030770127,0.0033926757,0.00001011706,0.00006499585,0.0027260976,0.9351162],"study_design_scores_gemma":[0.0038561258,0.0015886674,0.042482756,0.060123306,0.0010277525,0.00004933402,0.00067527615,0.10318451,0.0009852999,0.77841735,0.0036506043,0.0039590397],"about_ca_topic_score_codex":0.0001588679,"about_ca_topic_score_gemma":0.0015768565,"teacher_disagreement_score":0.9311572,"about_ca_system_score_codex":0.0006929509,"about_ca_system_score_gemma":0.001015824,"threshold_uncertainty_score":0.99938005},"labels":[],"label_agreement":null},{"id":"W4405622067","doi":"10.1080/13546783.2024.2443149","title":"Jumping to fixations: jumping to conclusions is associated with less hypothesis generation and more fixation","year":2024,"lang":"en","type":"article","venue":"Thinking & Reasoning","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Jumping; Fixation (population genetics); Cognitive psychology; Psychology; Biology","score_opus":0.15750505677185578,"score_gpt":0.3852931347231377,"score_spread":0.22778807795128192,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405622067","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9701226,0.00017853553,0.023784645,0.0044237874,0.00047143435,0.00031842946,0.000031866053,0.00022831699,0.00044043618],"genre_scores_gemma":[0.9774055,0.000010647586,0.019677466,0.0019235372,0.00019414151,0.000033563938,0.000015424588,0.000042235657,0.0006975145],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99707335,0.0001312254,0.0006259734,0.00087793794,0.00095161493,0.00033987727],"domain_scores_gemma":[0.99698496,0.001817327,0.0002169937,0.00044887376,0.00033074556,0.00020110431],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0028948698,0.00023949041,0.00036853907,0.0006842135,0.0009905177,0.0021526592,0.00041857816,0.00013242704,0.000092996415],"category_scores_gemma":[0.004653274,0.00019101633,0.00008389613,0.0014283558,0.00004498697,0.00067901466,0.00027835913,0.00022703502,0.00016536907],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000340745,0.000046104848,0.0075063948,0.000008491468,0.00007076218,0.000052011535,0.034038976,0.011219106,0.0049173767,0.0019761624,0.007871522,0.932259],"study_design_scores_gemma":[0.0016107408,0.0009171814,0.12012105,0.013455375,0.00065836805,0.00025894248,0.022017231,0.7184421,0.0068868725,0.0769697,0.03494421,0.0037182611],"about_ca_topic_score_codex":0.00014065695,"about_ca_topic_score_gemma":0.00021366721,"teacher_disagreement_score":0.92854077,"about_ca_system_score_codex":0.00025997497,"about_ca_system_score_gemma":0.0001247114,"threshold_uncertainty_score":0.9988832},"labels":[],"label_agreement":null},{"id":"W4405692000","doi":"10.54254/2753-7102/2024.18309","title":"Emotion-impacted Decision-making under Risks","year":2024,"lang":"en","type":"article","venue":"Advances in Social Behavior Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Psychology","score_opus":0.4357159054239492,"score_gpt":0.6293428337450291,"score_spread":0.19362692832107986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405692000","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98622394,0.0021994081,0.001813455,0.00043199776,0.0021191416,0.0005112342,0.00006735449,0.0001557352,0.006477765],"genre_scores_gemma":[0.9969153,0.00033919574,0.0015258803,0.000051309766,0.00049218215,0.00011440827,0.000006451972,0.00005762806,0.00049768743],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9921017,0.0006974652,0.0012975103,0.0013192827,0.0035251812,0.0010588083],"domain_scores_gemma":[0.98938346,0.00882488,0.00013480532,0.0007656856,0.0006922157,0.00019896461],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.009684344,0.0003030694,0.0005581463,0.0020095352,0.0008837039,0.0018372897,0.0017087933,0.00033772358,0.0020804177],"category_scores_gemma":[0.003990575,0.00024067922,0.00032339004,0.0050998954,0.0006279311,0.0020492133,0.00059755595,0.0015122275,0.0023557057],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000059934086,0.00016410636,0.012608899,0.0000045882175,0.0000036113618,0.0002362284,0.0006817347,0.00017643905,0.00013226517,0.0032199903,0.0022790157,0.98043317],"study_design_scores_gemma":[0.00042015468,0.00019519434,0.09870071,0.00038557162,0.000024018133,0.000037637394,0.0062092617,0.00083712104,0.0000584982,0.8271243,0.06545728,0.0005502446],"about_ca_topic_score_codex":0.00007957117,"about_ca_topic_score_gemma":0.0003979233,"teacher_disagreement_score":0.97988296,"about_ca_system_score_codex":0.0007419266,"about_ca_system_score_gemma":0.00038183626,"threshold_uncertainty_score":0.9991989},"labels":[],"label_agreement":null},{"id":"W4406377952","doi":"10.2139/ssrn.5096511","title":"Prudence and Higher-Order Risk Attitudes in the Rank-Dependent Utility Model","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Prudence; Rank (graph theory); Order (exchange); Econometrics; Economics; Actuarial science; Psychology; Mathematics; Epistemology; Philosophy; Combinatorics; Finance","score_opus":0.09200350387610859,"score_gpt":0.40311880777933334,"score_spread":0.3111153039032247,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406377952","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.966406,0.0057346984,0.022601403,0.001952222,0.00094886235,0.00039028493,0.00006477324,0.000023839784,0.0018779215],"genre_scores_gemma":[0.98852587,0.008539874,0.0005655774,0.00020070275,0.00013277294,0.000019180934,0.000002125335,0.000012861738,0.0020010096],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99381626,0.0008073852,0.0013263249,0.0010099964,0.0014219144,0.0016181464],"domain_scores_gemma":[0.99627995,0.0012430627,0.0008455378,0.0011866478,0.00034844372,0.00009636307],"candidate_categories":["scholarly_communication","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.02444878,0.000389942,0.0006741911,0.00045122977,0.0004114018,0.0011375095,0.0030024108,0.00038041334,0.00007699288],"category_scores_gemma":[0.0013343832,0.00024263127,0.00027442566,0.00042039523,0.00018030462,0.00028126812,0.0010691434,0.007505729,0.000033588753],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016520014,0.00028120878,0.046086907,0.000009244121,0.000081963,0.000015843161,0.00059154973,0.01608954,0.0000032062476,0.010439388,0.0004908218,0.9257451],"study_design_scores_gemma":[0.00044030612,0.00005920421,0.014273326,0.00007988425,0.00006765816,0.000082879604,0.00061105203,0.010423028,0.0000017628562,0.973032,0.0006717694,0.0002571551],"about_ca_topic_score_codex":0.00039736222,"about_ca_topic_score_gemma":0.005524654,"teacher_disagreement_score":0.9625926,"about_ca_system_score_codex":0.00071947323,"about_ca_system_score_gemma":0.00449406,"threshold_uncertainty_score":0.9998994},"labels":[],"label_agreement":null},{"id":"W4406883415","doi":"10.1007/978-3-031-81068-8_2","title":"The Psychology Behind Bad Decisions","year":2025,"lang":"en","type":"book-chapter","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Psychology; Positive economics; Social psychology; Economics","score_opus":0.2191491167496161,"score_gpt":0.4647152490788309,"score_spread":0.2455661323292148,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406883415","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00039114204,0.0006249858,0.00184133,0.0038285302,0.003581706,0.0002520651,0.000087493856,0.00007012218,0.9893226],"genre_scores_gemma":[0.0014715915,0.0006996574,0.0013969216,0.0021313454,0.00015844086,0.000009137985,0.00000877011,0.000034067354,0.9940901],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99535763,0.00006647288,0.0017303672,0.0012464897,0.0012007804,0.00039827081],"domain_scores_gemma":[0.9842642,0.011361225,0.0005796856,0.003094747,0.00051710976,0.00018301823],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0032018607,0.0004400729,0.00073600566,0.0005822537,0.00073238625,0.00092430203,0.0035228855,0.0007205408,0.006296279],"category_scores_gemma":[0.0032317375,0.0002382736,0.00064590806,0.00010794906,0.00040609585,0.00012879931,0.00080744654,0.00075124705,0.01281506],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015490974,0.000008239159,0.000011673047,8.227441e-8,0.00001167743,0.0000113343185,0.0000068411628,0.0000018521282,5.226065e-7,0.073828615,0.37735957,0.5487441],"study_design_scores_gemma":[0.000081918304,0.000024028775,0.00007547106,0.000026502063,0.000020063084,0.000011152442,0.000012060384,0.000021783848,7.355005e-7,0.4693292,0.53024644,0.00015062444],"about_ca_topic_score_codex":0.000011723797,"about_ca_topic_score_gemma":0.0005430544,"teacher_disagreement_score":0.54859346,"about_ca_system_score_codex":0.00007289644,"about_ca_system_score_gemma":0.00027488885,"threshold_uncertainty_score":0.9946121},"labels":[],"label_agreement":null},{"id":"W4406883430","doi":"10.1007/978-3-031-81068-8_3","title":"Common Pitfalls in Personal Decision-Making","year":2025,"lang":"en","type":"book-chapter","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Psychology; Computer science","score_opus":0.09478779350757056,"score_gpt":0.39883302391993175,"score_spread":0.3040452304123612,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406883430","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013511891,0.00038195966,0.0010058376,0.0003150401,0.0018566876,0.00032782689,0.00011138891,0.00008392658,0.9824054],"genre_scores_gemma":[0.20900384,0.00009094984,0.00527516,0.0012980461,0.0001849867,0.0000083838895,0.000009718852,0.00006286749,0.784066],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99381715,0.000059576614,0.0022677393,0.0015395026,0.0018485324,0.00046748997],"domain_scores_gemma":[0.9876531,0.009815367,0.0006463704,0.0014072509,0.0003219748,0.00015594275],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002941538,0.00061614165,0.0014177971,0.0020419287,0.00017727682,0.0007640257,0.0021508804,0.0008246218,0.014797656],"category_scores_gemma":[0.0020181073,0.00048599782,0.00065751455,0.00028344998,0.0001727526,0.00030473692,0.0009368428,0.0009655243,0.004384457],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006603838,0.000036377587,0.000576722,0.0000026338387,0.000011313383,0.00014591849,0.00008435149,0.00003194674,6.79608e-7,0.024408808,0.060728367,0.9139068],"study_design_scores_gemma":[0.0002265593,0.00004270986,0.00036600768,0.00076415297,0.000020715413,0.000017715085,0.0000882932,0.0009638185,8.3154174e-7,0.685685,0.31134593,0.00047826694],"about_ca_topic_score_codex":0.000042112137,"about_ca_topic_score_gemma":0.0015532785,"teacher_disagreement_score":0.91342854,"about_ca_system_score_codex":0.00036291676,"about_ca_system_score_gemma":0.0003863652,"threshold_uncertainty_score":0.9997592},"labels":[],"label_agreement":null},{"id":"W4406961552","doi":"10.1177/19485506251314071","title":"Information Prioritization Underpins the Flexible Expression of Social Preferences Under Time Constraints","year":2025,"lang":"en","type":"article","venue":"Social Psychological and Personality Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"National Institute of Mental Health; Social Sciences and Humanities Research Council of Canada; Canada Research Chairs","keywords":"Prosocial behavior; Incentive; Prioritization; Psychology; Context (archaeology); Social psychology; Social environment; Social preferences; Perspective (graphical); Bridge (graph theory); Microeconomics; Computer science; Sociology; Economics","score_opus":0.1700602235043279,"score_gpt":0.4631918801271725,"score_spread":0.29313165662284457,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406961552","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9703069,0.000013576972,0.0028012819,0.004304053,0.00021726229,0.00013265146,0.00004129641,0.000023050328,0.02215994],"genre_scores_gemma":[0.9987096,0.0000032350729,0.00014176035,0.0008158615,0.00003709425,0.000003601665,0.0000032893342,9.411542e-7,0.00028462318],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99813217,0.00015807716,0.00046730263,0.0002936143,0.0007589824,0.00018988409],"domain_scores_gemma":[0.99881274,0.00043832572,0.0002432138,0.00014572928,0.00031419913,0.000045790985],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0030571187,0.00009520704,0.00019947015,0.0001230312,0.0011040492,0.00040805203,0.0006733797,0.000121464574,0.00041737166],"category_scores_gemma":[0.00068927946,0.000054075004,0.000068029294,0.0010427758,0.003035874,0.00064996915,0.00016254249,0.00014467069,0.000043771244],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010799748,0.00018679559,0.005606932,0.000007903894,0.000005261695,1.9925847e-7,0.0062887142,0.000011189469,0.0055543156,0.06531321,0.008098504,0.90881896],"study_design_scores_gemma":[0.00028706572,0.000070264156,0.4875061,0.000014896239,0.000008876315,0.000001738441,0.008021461,0.00017989082,0.00023423054,0.5012306,0.0023192812,0.00012562836],"about_ca_topic_score_codex":0.0000131663155,"about_ca_topic_score_gemma":0.0000035135986,"teacher_disagreement_score":0.9086934,"about_ca_system_score_codex":0.000033290038,"about_ca_system_score_gemma":0.00011953424,"threshold_uncertainty_score":0.9996773},"labels":[],"label_agreement":null},{"id":"W4407099084","doi":"10.1016/j.iref.2025.103899","title":"Subjective probabilities under behavioral heuristics","year":2025,"lang":"en","type":"article","venue":"International Review of Economics & Finance","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University; University of Toronto","funders":"Social Sciences and Humanities Research Council; Social Sciences and Humanities Research Council of Canada; York University","keywords":"Heuristics; Economics; Psychology; Econometrics; Computer science; Cognitive psychology; Mathematical economics; Mathematics; Mathematical optimization","score_opus":0.10601575220184753,"score_gpt":0.43052301643493485,"score_spread":0.3245072642330873,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407099084","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9630565,0.0058459262,0.0015473505,0.0025757814,0.0024678824,0.00031477844,0.00020175596,0.000015437729,0.023974562],"genre_scores_gemma":[0.9766355,0.015583282,0.0029018894,0.0013263114,0.000059999184,0.00003738542,0.0000143368125,0.0000109548055,0.0034303279],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9976608,0.000055698678,0.0014138119,0.0005026918,0.00020658114,0.00016040073],"domain_scores_gemma":[0.99714035,0.0008046795,0.000688096,0.0006289452,0.00070613896,0.0000317894],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014319804,0.00016739497,0.0005485735,0.00022879509,0.00005821538,0.0001152219,0.0012499285,0.0000698612,0.00031214106],"category_scores_gemma":[0.0013426343,0.00014895387,0.00027958487,0.00023691492,0.00018405612,0.00031265564,0.0002533189,0.00013826443,0.00016679663],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000049355876,0.00029100836,0.01208581,0.00012521046,0.000037194015,0.0000028604318,0.000055472363,0.0010357207,0.000008985384,0.34405357,0.010059899,0.63219494],"study_design_scores_gemma":[0.0002389269,0.00005938624,0.012016855,0.0018448529,0.00003083376,0.0000069991065,0.0000784869,0.00068186206,0.00016115874,0.75646085,0.22821076,0.00020903132],"about_ca_topic_score_codex":0.000042157266,"about_ca_topic_score_gemma":0.00006699207,"teacher_disagreement_score":0.6319859,"about_ca_system_score_codex":0.00024524925,"about_ca_system_score_gemma":0.00028661828,"threshold_uncertainty_score":0.6074163},"labels":[],"label_agreement":null},{"id":"W4407251648","doi":"10.1073/pnas.2416643122","title":"Robust inattentive discrete choice","year":2025,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Quest University Canada; Booth University College","funders":"","keywords":"Mathematics; Computer science","score_opus":0.20003304725416718,"score_gpt":0.4302897098713761,"score_spread":0.23025666261720892,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407251648","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9431298,0.00005965273,0.000014013161,0.006760111,0.00009440709,0.000122001606,0.000021216674,0.000009298687,0.04978954],"genre_scores_gemma":[0.9964556,0.0000064864535,0.0012156261,0.00046239028,0.000036856134,0.0000048054167,3.8351594e-8,0.000002083908,0.0018161273],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9967985,0.000012026789,0.0006905979,0.00041205625,0.0019304954,0.00015633507],"domain_scores_gemma":[0.9974078,0.0010779112,0.0007177305,0.00001861794,0.00074486056,0.000033065055],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004526733,0.00009871506,0.00023264144,0.00048351017,0.000307942,0.00015025558,0.0025551384,0.000086129476,0.000058209043],"category_scores_gemma":[0.006682459,0.000056297427,0.00015095186,0.0023112833,0.0010722334,0.0007930943,0.0004753824,0.00017766564,0.000017872086],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007668378,0.00028756534,0.22370863,0.000046568326,0.00005713398,2.2866162e-8,0.00060164765,0.0031683072,0.08510875,0.4842362,0.08424932,0.11845918],"study_design_scores_gemma":[0.00016899094,0.000021902651,0.1624525,0.00011926876,0.00001454917,0.000002074641,0.00063919864,0.0026229743,0.026468059,0.80350316,0.0038879516,0.00009936495],"about_ca_topic_score_codex":0.0000094432235,"about_ca_topic_score_gemma":3.5717702e-7,"teacher_disagreement_score":0.31926695,"about_ca_system_score_codex":0.000044724256,"about_ca_system_score_gemma":0.000058593927,"threshold_uncertainty_score":0.800001},"labels":[],"label_agreement":null},{"id":"W4407259673","doi":"10.1016/j.jmp.2025.102902","title":"Probabilistic models of delay discounting: “Fixed-endpoint” psychometric curves improve plausibility and performance","year":2025,"lang":"en","type":"article","venue":"Journal of Mathematical Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; McMaster University; Toronto Rehabilitation Institute; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Delay discounting; Discounting; Probabilistic logic; Computer science; Econometrics; Mathematics; Statistics; Economics","score_opus":0.142699480612111,"score_gpt":0.44354796999608126,"score_spread":0.30084848938397024,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407259673","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9601753,0.00060570054,0.03177557,0.0011623218,0.00066214585,0.00018178986,0.000009755612,0.000006718154,0.0054206946],"genre_scores_gemma":[0.9931559,0.000191331,0.0060892203,0.00033538556,0.00003570884,0.000003147335,2.3529121e-7,0.000008155473,0.00018093747],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99622095,0.00016025755,0.0023493804,0.0003883042,0.0006438015,0.00023733759],"domain_scores_gemma":[0.99502236,0.0024264604,0.0011859502,0.0006607214,0.00058384903,0.00012065854],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0065926625,0.00017559247,0.00090298906,0.00073434936,0.00006324166,0.0000771226,0.00081377686,0.00014733651,0.00020347054],"category_scores_gemma":[0.005830771,0.00011078766,0.00021254705,0.0008702748,0.00038165582,0.0004356518,0.00014323641,0.00038690513,0.000022911412],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017050597,0.0038248983,0.025110561,0.0010677197,0.0001858533,0.000030228788,0.0007260345,0.00043041274,0.0007847331,0.026640775,0.020247983,0.9192457],"study_design_scores_gemma":[0.00070661167,0.00053753244,0.016970193,0.00039427995,0.00007506131,0.00015294524,0.000107616834,0.0064556412,0.000050763265,0.9740821,0.00034015055,0.00012708381],"about_ca_topic_score_codex":9.3082906e-7,"about_ca_topic_score_gemma":0.000001443233,"teacher_disagreement_score":0.94744134,"about_ca_system_score_codex":0.000038609574,"about_ca_system_score_gemma":0.00009177579,"threshold_uncertainty_score":0.6980399},"labels":[],"label_agreement":null},{"id":"W4407402686","doi":"10.2139/ssrn.5075781","title":"Selten's Horse: an experiment on sequential rationality","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Rationality; Horse; Mathematical economics; Computer science; Economics; Philosophy; Biology; Epistemology","score_opus":0.13983361039605138,"score_gpt":0.4552288270786366,"score_spread":0.3153952166825852,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407402686","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9769882,0.0007296463,0.012695872,0.0016368601,0.0043661525,0.00031430318,0.000087679604,0.0000645817,0.0031167204],"genre_scores_gemma":[0.993019,0.0005104577,0.000716088,0.0003001656,0.0008757265,0.000024068742,0.00004177061,0.000025639449,0.004487093],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99277836,0.0007373715,0.0015326974,0.0011928783,0.0019060201,0.0018526709],"domain_scores_gemma":[0.99641746,0.0004168967,0.00097172515,0.0013520455,0.00059580896,0.00024604204],"candidate_categories":["metaepi_narrow","scholarly_communication","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.012667959,0.00046502694,0.00071975426,0.00064881763,0.0005093133,0.0013860549,0.0024423662,0.0004644608,0.000520894],"category_scores_gemma":[0.00076529523,0.00036758537,0.0005964777,0.0002883184,0.000100595564,0.0003545714,0.0006983749,0.005140898,0.00028289988],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005214735,0.00095375726,0.00069372985,0.0000051957063,0.000270997,0.000036006142,0.0005828444,0.015708223,0.000258579,0.115369834,0.0040936545,0.8615057],"study_design_scores_gemma":[0.00042872896,0.00029818952,0.0001506808,0.00006241734,0.000051678453,0.00010210615,0.0012299425,0.0011296624,0.0003023725,0.98841023,0.0074321744,0.0004018262],"about_ca_topic_score_codex":0.00010264575,"about_ca_topic_score_gemma":0.0005101742,"teacher_disagreement_score":0.8730404,"about_ca_system_score_codex":0.0029208194,"about_ca_system_score_gemma":0.010049672,"threshold_uncertainty_score":0.99987763},"labels":[],"label_agreement":null},{"id":"W4407594617","doi":"10.1111/ecin.13279","title":"Underpowered studies and exaggerated effects: A replication and re‐evaluation of the magnitude of anchoring effects","year":2025,"lang":"en","type":"article","venue":"Economic Inquiry","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"California Air Resources Board; National Institute of Food and Agriculture; National Science Foundation","keywords":"Anchoring; Replication (statistics); Magnitude (astronomy); Economics; Econometrics; Psychology; Positive economics; Social psychology; Statistics; Mathematics; Physics","score_opus":0.2327895439360776,"score_gpt":0.47645863059627397,"score_spread":0.24366908666019638,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407594617","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9953323,0.0018397348,0.00009360053,0.00022277978,0.0016489062,0.00043266645,0.0000030814642,0.000009367495,0.00041755734],"genre_scores_gemma":[0.99941903,0.00009689739,0.00024454793,0.00006850307,0.00005046964,0.000027350083,5.556519e-7,0.00000528838,0.00008738099],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9983202,0.00028737486,0.0006479696,0.00046341112,0.00018130163,0.00009969989],"domain_scores_gemma":[0.9960558,0.0024688868,0.0004532504,0.00076502806,0.00023284873,0.000024189816],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004485398,0.00010972173,0.00037196913,0.0001953073,0.00010321786,0.000064687985,0.00025088657,0.00006912628,0.0000100307425],"category_scores_gemma":[0.004586335,0.00007732774,0.00005591853,0.00018624419,0.00029307322,0.00019252734,0.00023517296,0.000070129696,0.000006127982],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008555128,0.00005602223,0.036626264,0.00014098278,0.00011967731,4.560001e-7,0.0029877974,0.00067986886,0.0061017433,0.0015389851,0.0041323435,0.9475303],"study_design_scores_gemma":[0.002665174,0.00025350234,0.5689038,0.001164289,0.00040628607,0.000005480925,0.004806749,0.012245685,0.052895702,0.35562614,0.0006743287,0.00035282937],"about_ca_topic_score_codex":0.000020237994,"about_ca_topic_score_gemma":0.000037530706,"teacher_disagreement_score":0.94717747,"about_ca_system_score_codex":0.00011886628,"about_ca_system_score_gemma":0.000102458886,"threshold_uncertainty_score":0.5490602},"labels":[],"label_agreement":null},{"id":"W4407595967","doi":"10.1016/j.mar.2025.100926","title":"Decoding effort: Toward a measure – and a better understanding – of effort intensity in accounting research","year":2025,"lang":"en","type":"article","venue":"Management Accounting Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Universiteit van Amsterdam; Universiteit Maastricht; University of Western Australia; Australian Research Council; Monash University","keywords":"Measure (data warehouse); Accounting; Decoding methods; Intensity (physics); Computer science; Business; Data mining; Telecommunications","score_opus":0.401533717327208,"score_gpt":0.4939215773199443,"score_spread":0.0923878599927363,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407595967","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9669177,0.00013120679,0.0011321818,0.0017532668,0.0003291355,0.0007239327,0.0000024102956,0.000034377947,0.028975798],"genre_scores_gemma":[0.9978452,0.000048160262,0.0011258393,0.000119715995,0.000060452705,0.000038595208,0.0000018520133,0.000023182616,0.000737024],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.992554,0.00028215713,0.0012797224,0.0011918253,0.0035262257,0.0011660623],"domain_scores_gemma":[0.9946596,0.0027805779,0.00022528858,0.0009953164,0.0012449471,0.00009428952],"candidate_categories":["metaresearch","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.05959557,0.00022984824,0.00061803276,0.0056740837,0.0007571359,0.0017373436,0.0016583876,0.00018806438,0.000096310505],"category_scores_gemma":[0.0033172306,0.00020112627,0.00012550467,0.0051936475,0.0005305466,0.0007682828,0.003512572,0.001174885,0.00008029201],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001864454,0.00010175517,0.6968867,0.00015751588,0.00004278247,0.000065223394,0.00084668316,0.000037891594,0.00016960822,0.0055029737,0.0063993866,0.28960305],"study_design_scores_gemma":[0.0019968003,0.00013010444,0.41515017,0.0025194346,0.00004250823,0.0000079365145,0.049606927,0.011680269,0.00047456552,0.5085309,0.009265306,0.00059508445],"about_ca_topic_score_codex":0.0004831408,"about_ca_topic_score_gemma":0.00042274292,"teacher_disagreement_score":0.5030279,"about_ca_system_score_codex":0.0007083486,"about_ca_system_score_gemma":0.0001189821,"threshold_uncertainty_score":0.99929893},"labels":[],"label_agreement":null},{"id":"W4407905155","doi":"10.1037/pspa0000436","title":"Reactions to undesired outcomes: Evidence for the opposer’s loss effect.","year":2025,"lang":"en","type":"article","venue":"Journal of Personality and Social Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Ambivalence; Social psychology; Framing (construction); Psychology; Feeling; Preference; Framing effect; Phenomenon; Negativity effect; Salience (neuroscience); PsycINFO; Opposition (politics); Negativity bias; Positive economics; Persuasion; Politics; Economics; Cognitive psychology; Political science; Epistemology; Law; Microeconomics; MEDLINE; Philosophy","score_opus":0.45593075665749677,"score_gpt":0.5792925075382016,"score_spread":0.12336175088070483,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407905155","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8910122,0.00018764226,0.009582905,0.09684994,0.0019081896,0.0001654646,0.000012224144,0.0000045985416,0.00027683054],"genre_scores_gemma":[0.99248904,0.000033638655,0.0004010604,0.0060469,0.00020516511,0.000006452619,1.5982562e-7,0.000003834607,0.0008137395],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99828315,0.0003060837,0.00070413866,0.00022972941,0.0003149353,0.00016196907],"domain_scores_gemma":[0.99086493,0.008159204,0.00036607566,0.00020145523,0.00033989226,0.00006841785],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0067016114,0.00009984694,0.00041330338,0.00017455283,0.00048624317,0.00018309044,0.000579479,0.00012735974,0.00006561754],"category_scores_gemma":[0.0040328326,0.00005741173,0.00032597693,0.00027574366,0.00019384631,0.00018515406,0.00005490154,0.00023131855,0.000015571175],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002041918,0.00023159877,0.06097962,0.000018969451,0.00020432023,0.0000137572315,0.0043611038,0.000027871632,0.00045145437,0.0067323674,0.10489236,0.82004464],"study_design_scores_gemma":[0.0013135461,0.0005625366,0.6270956,0.00006454016,0.00015779756,0.000060168088,0.002426361,0.00003091664,0.00001328582,0.16057366,0.20755585,0.00014576186],"about_ca_topic_score_codex":0.00002672302,"about_ca_topic_score_gemma":0.00004382329,"teacher_disagreement_score":0.8198989,"about_ca_system_score_codex":0.000058621616,"about_ca_system_score_gemma":0.00009621289,"threshold_uncertainty_score":0.48279685},"labels":[],"label_agreement":null},{"id":"W4407918527","doi":"10.2139/ssrn.5150894","title":"Knightian Uncertainty and Bayesian Entrepreneurship","year":2025,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Knightian uncertainty; Entrepreneurship; Bayesian probability; Econometrics; Economics; Computer science; Artificial intelligence; Ambiguity; Finance","score_opus":0.032894695993148884,"score_gpt":0.35124482054388007,"score_spread":0.3183501245507312,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407918527","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9770414,0.0015118474,0.011290097,0.0039447765,0.0006434763,0.000082850485,0.0000029578953,0.000028337592,0.0054542534],"genre_scores_gemma":[0.9929159,0.0005580509,0.00010517029,0.0002983014,0.000100033,0.0000017762939,7.025006e-7,0.000008566692,0.0060114632],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9968979,0.00019292843,0.0006307132,0.0004482361,0.00045367915,0.0013765543],"domain_scores_gemma":[0.99847376,0.0005959629,0.000222331,0.0004176083,0.00015709418,0.00013321145],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005381735,0.00016317611,0.00029186445,0.00042821353,0.0003675555,0.0005796199,0.00075000146,0.00010071825,0.00017114278],"category_scores_gemma":[0.000982499,0.000118073076,0.00014920547,0.00048186246,0.00009439758,0.00026397617,0.0001241446,0.0011484692,0.00010037301],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000484154,0.000035102614,0.015255076,5.1461615e-7,0.000025383659,0.000006242453,0.00007348701,0.00009369287,0.0000403344,0.053277936,0.0008716095,0.9302722],"study_design_scores_gemma":[0.00038153672,0.00009555297,0.0018069191,0.000017385077,0.000022799517,0.0001896728,0.0013520002,0.00047963628,0.000026559666,0.97818726,0.017315023,0.00012562393],"about_ca_topic_score_codex":0.000050503284,"about_ca_topic_score_gemma":0.0012638378,"teacher_disagreement_score":0.9301466,"about_ca_system_score_codex":0.0004311508,"about_ca_system_score_gemma":0.0016254085,"threshold_uncertainty_score":0.5589288},"labels":[],"label_agreement":null},{"id":"W4408162041","doi":"10.3758/s13423-025-02656-y","title":"Sunk-cost judgments across the child to adult lifespan","year":2025,"lang":"en","type":"article","venue":"Psychonomic Bulletin & Review","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kwantlen Polytechnic University; Simon Fraser University; University of Victoria; Wilfrid Laurier University","funders":"","keywords":"Sunk costs; Psychology; Developmental psychology; Sample (material); Economics; Microeconomics","score_opus":0.08143731676681784,"score_gpt":0.453041351198806,"score_spread":0.3716040344319882,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408162041","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2896168,0.05866038,0.001446094,0.5363288,0.012204178,0.0056588403,0.00025560573,0.00023699169,0.09559232],"genre_scores_gemma":[0.47547174,0.065136924,0.0031161706,0.41410097,0.0010173272,0.0012577696,0.000029561877,0.00014179671,0.03972773],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9958677,0.00028538154,0.0016650785,0.0011053439,0.0005051195,0.0005713752],"domain_scores_gemma":[0.99583215,0.00093068025,0.00043898963,0.0022992538,0.0002715081,0.00022745221],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.004797252,0.00034502338,0.0008152422,0.00013627674,0.00053354964,0.00062081317,0.0028663853,0.0001056447,0.002835015],"category_scores_gemma":[0.0025174,0.00021604657,0.0004520836,0.00087993935,0.00012025646,0.00007792852,0.0005176044,0.00038059996,0.029108573],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018755672,0.000049430888,0.0005167855,0.000021013444,0.000010551254,0.0000010296767,0.00004548173,0.00000886907,0.000001421382,0.00019077328,0.46092016,0.53821576],"study_design_scores_gemma":[0.00030612084,0.000027826363,0.0030543392,0.0019353585,0.000036610876,0.000010866011,0.00012703982,0.000009772943,0.000008915573,0.0019993447,0.9922444,0.00023940216],"about_ca_topic_score_codex":0.0000659783,"about_ca_topic_score_gemma":0.00007229809,"teacher_disagreement_score":0.5379763,"about_ca_system_score_codex":0.00011554251,"about_ca_system_score_gemma":0.0000630427,"threshold_uncertainty_score":0.99807656},"labels":[],"label_agreement":null},{"id":"W4408273049","doi":"10.1017/bca.2024.39","title":"Economic Evaluation Under Ambiguity and Structural Uncertainties","year":2024,"lang":"en","type":"article","venue":"Journal of Benefit-Cost Analysis","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Social Sciences and Humanities Research Council of Canada; The Graduate School, Northwestern University; University of Alberta","keywords":"Ambiguity; Econometrics; Economics; Computer science","score_opus":0.11257570239479595,"score_gpt":0.43621619406841794,"score_spread":0.32364049167362197,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408273049","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99515843,0.001450646,0.0012808733,0.0007327648,0.0010386042,0.00006176377,0.00003375737,0.00001003175,0.00023313594],"genre_scores_gemma":[0.99903363,0.00008414384,0.00038313548,0.000054852248,0.00021293225,0.0000012820965,0.0000048225265,0.000009245535,0.00021598123],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9971375,0.00011433695,0.0012471809,0.00036649435,0.0009557705,0.00017874067],"domain_scores_gemma":[0.9976759,0.0007368918,0.00057579717,0.00035195347,0.00050813623,0.00015130985],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.005000179,0.00016294542,0.0005976797,0.0015201877,0.00014162206,0.0013756049,0.0004579842,0.00009115294,0.0013159873],"category_scores_gemma":[0.0003083105,0.00011092611,0.0006110812,0.0009169652,0.00008300378,0.0008444397,0.00008639504,0.00021915013,0.000085953005],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000036534024,0.000009660776,0.020149492,0.00000170809,0.0005425162,0.00001022383,0.00024847593,0.14537372,0.000044545483,0.00049646455,0.00091849477,0.83216816],"study_design_scores_gemma":[0.0004025255,0.00011081241,0.1755712,0.000041574425,0.0034738884,0.00017127793,0.0016384772,0.44727093,0.00008976328,0.36848122,0.0024480347,0.00030028986],"about_ca_topic_score_codex":0.00011292361,"about_ca_topic_score_gemma":0.0008278342,"teacher_disagreement_score":0.8318679,"about_ca_system_score_codex":0.00032081798,"about_ca_system_score_gemma":0.00018626901,"threshold_uncertainty_score":0.9996611},"labels":[],"label_agreement":null},{"id":"W4408646938","doi":"10.1002/bdm.70013","title":"When Certainty Backfires: The Effects of Unwarranted Precision on Consumer Loyalty","year":2025,"lang":"en","type":"article","venue":"Journal of Behavioral Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Certainty; Loyalty; Business; Psychology; Advertising; Marketing; Economics; Econometrics; Mathematics","score_opus":0.06292381277000407,"score_gpt":0.4205145747289105,"score_spread":0.35759076195890643,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408646938","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9822609,0.0007353435,0.010699152,0.00034500877,0.00493921,0.00042979402,0.000018350482,0.000020397312,0.0005518795],"genre_scores_gemma":[0.99316776,0.000083995335,0.0058397204,0.00037906357,0.00010271724,0.0000054355905,6.2894384e-7,0.000029686347,0.00039098042],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9917327,0.0006789525,0.0035998938,0.0006371319,0.0028955706,0.0004557358],"domain_scores_gemma":[0.9738084,0.020028785,0.0026915486,0.0015397541,0.0017550323,0.00017649577],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0065869945,0.00042727042,0.0012781003,0.0015549512,0.0003960484,0.0005424159,0.002835466,0.0003131765,0.00043447767],"category_scores_gemma":[0.010101506,0.00023961697,0.0009783666,0.0013537217,0.0003159391,0.0005475428,0.00050083897,0.0008939736,0.00011770086],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001323269,0.0005071188,0.0092154415,0.000010415824,0.00003291985,0.000114332535,0.000470733,0.00053070183,0.0012751307,0.00019037093,0.02837975,0.9579498],"study_design_scores_gemma":[0.009345301,0.0050611943,0.14013632,0.013921177,0.0012029246,0.00041201,0.0041627535,0.003070273,0.00969601,0.7313896,0.080168046,0.0014344032],"about_ca_topic_score_codex":0.00002813447,"about_ca_topic_score_gemma":0.000041536347,"teacher_disagreement_score":0.95651543,"about_ca_system_score_codex":0.00023049161,"about_ca_system_score_gemma":0.00034176165,"threshold_uncertainty_score":0.99823684},"labels":[],"label_agreement":null},{"id":"W4409181118","doi":"10.1101/2025.04.04.647306","title":"Individual differences in sequential decision-making","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"National Institute of Mental Health; National Institute on Drug Abuse; Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science","score_opus":0.08284271355758638,"score_gpt":0.3400366456333159,"score_spread":0.25719393207572955,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409181118","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98646545,0.00064038724,0.0046284623,0.00017724681,0.0062369974,0.0006648102,0.00083867664,0.0002568605,0.00009110825],"genre_scores_gemma":[0.98637235,0.00009081881,0.01261438,0.00031587214,0.0004012291,0.000121315956,2.7253537e-7,0.00006641474,0.000017350723],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.990751,0.0005227356,0.0026590507,0.0027850748,0.002293342,0.0009887794],"domain_scores_gemma":[0.99132824,0.0030286429,0.0012999751,0.0031563868,0.0008603171,0.0003264535],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0057032434,0.0009421945,0.0017162781,0.0025408987,0.00032210053,0.0025745616,0.004745159,0.0012132166,0.0004799162],"category_scores_gemma":[0.006249199,0.00085823925,0.0005179829,0.0021880183,0.0002771648,0.00052242994,0.003843567,0.0017710866,0.00042309114],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008565773,0.002625047,0.9298249,0.00033739,0.0006661436,0.0018236337,0.00040709446,0.0040013585,0.013300609,0.0053682136,0.014888253,0.025900781],"study_design_scores_gemma":[0.002022378,0.00017165608,0.9544436,0.005962192,0.0003600796,1.3293526e-7,0.00008884892,0.005670029,0.0059607066,0.009461879,0.011811672,0.0040468606],"about_ca_topic_score_codex":0.0000851636,"about_ca_topic_score_gemma":0.00006570549,"teacher_disagreement_score":0.024618667,"about_ca_system_score_codex":0.0005148456,"about_ca_system_score_gemma":0.001723023,"threshold_uncertainty_score":0.99938685},"labels":[],"label_agreement":null},{"id":"W4409331128","doi":"10.1111/cdep.12546","title":"Possibility Judgments in Childhood: Is Uncertainty Monitoring the Missing Link?","year":2025,"lang":"en","type":"article","venue":"Child Development Perspectives","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Psychology; Link (geometry); Cognitive psychology; Developmental psychology; Computer science","score_opus":0.06933968025993942,"score_gpt":0.3922721990038862,"score_spread":0.3229325187439468,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409331128","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9736936,0.0009669109,0.00027163688,0.011204758,0.0008616792,0.0003221969,0.000005051405,0.00005124271,0.012622887],"genre_scores_gemma":[0.9964038,0.00003982264,0.0018870481,0.0006341491,0.00010429127,0.000019499059,0.0000013334665,0.000011043029,0.00089898525],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99667495,0.0001621031,0.0009847046,0.0010340228,0.0007375683,0.0004066644],"domain_scores_gemma":[0.997782,0.00077142956,0.0002228246,0.00089594774,0.00023764011,0.000090141766],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002705228,0.00027223246,0.00039644216,0.0004957053,0.00078093936,0.0006718589,0.0012208028,0.000119152566,0.0001791425],"category_scores_gemma":[0.0016848921,0.00017751721,0.00014946102,0.001224016,0.00017751497,0.00034006892,0.00042240965,0.00044968186,0.00013940323],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000036198395,0.00027563373,0.19728164,0.0000028614859,0.000034443587,0.000005452936,0.0317393,0.00017521714,0.000015868167,0.00026979265,0.00073910435,0.7694245],"study_design_scores_gemma":[0.00045448178,0.000012005113,0.92035455,0.00023257572,0.0000075926664,0.000003139819,0.018020133,0.00011939054,0.0008243485,0.050437957,0.009290148,0.00024370388],"about_ca_topic_score_codex":0.000057790105,"about_ca_topic_score_gemma":0.00005016134,"teacher_disagreement_score":0.7691808,"about_ca_system_score_codex":0.0006465934,"about_ca_system_score_gemma":0.0004314742,"threshold_uncertainty_score":0.7238942},"labels":[],"label_agreement":null},{"id":"W4409516416","doi":"10.1017/jdm.2025.8","title":"Using conventional framing to offset bias against algorithmic errors","year":2025,"lang":"en","type":"article","venue":"Judgment and Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Framing (construction); Offset (computer science); Computer science; Social psychology; Psychology; Econometrics; Mathematics; Geography","score_opus":0.22116958783016885,"score_gpt":0.4507252767246763,"score_spread":0.22955568889450748,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409516416","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8116712,0.00018281351,0.18331437,0.00025212517,0.0016797014,0.00026669487,0.000023888337,0.00004720477,0.002561993],"genre_scores_gemma":[0.89819896,0.000014589277,0.09932127,0.0017809864,0.00010302141,0.000010114179,0.0000031661627,0.000017413178,0.00055049366],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9959938,0.00009873067,0.0013201796,0.00096393924,0.0012143466,0.0004090053],"domain_scores_gemma":[0.9960436,0.002484646,0.00033885182,0.00065988593,0.0002922136,0.00018078713],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0031456382,0.0002857375,0.000522181,0.0011275094,0.00069119467,0.001216586,0.00068514,0.00016919278,0.00032119136],"category_scores_gemma":[0.0020993801,0.00023356396,0.00022417719,0.0012023308,0.00008148283,0.00039325107,0.00074277533,0.0002268465,0.00025549837],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009072134,0.000058002584,0.0051461644,0.0000027624749,0.000012538838,0.000019861423,0.0000888178,0.0027086516,0.00024724565,0.0006282523,0.011650026,0.97934693],"study_design_scores_gemma":[0.0017463345,0.00012225006,0.014004495,0.0014054325,0.00007565663,0.00003323178,0.0021886453,0.24179368,0.0002599533,0.61565566,0.12178498,0.00092970737],"about_ca_topic_score_codex":0.000016305072,"about_ca_topic_score_gemma":0.000028846922,"teacher_disagreement_score":0.9784173,"about_ca_system_score_codex":0.00016860296,"about_ca_system_score_gemma":0.00012405688,"threshold_uncertainty_score":0.99982023},"labels":[],"label_agreement":null},{"id":"W4409595690","doi":"10.1016/j.newideapsych.2025.101164","title":"Doing things intentionally: Probability raising and control","year":2025,"lang":"en","type":"article","venue":"New Ideas in Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Raising (metalworking); Psychology; Control (management); Psychoanalysis; Artificial intelligence; Computer science; Mathematics","score_opus":0.10256733902360389,"score_gpt":0.4578738178928898,"score_spread":0.3553064788692859,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409595690","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89404327,0.0003765181,0.06814645,0.00791413,0.00170701,0.00022427032,0.0000028123,0.00003870543,0.02754681],"genre_scores_gemma":[0.98468524,0.000012556112,0.009651142,0.0049029337,0.000041448613,0.000006893857,6.4987853e-7,0.0000057314387,0.0006933909],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99778056,0.00019807051,0.000817114,0.0007251999,0.00023876765,0.00024029722],"domain_scores_gemma":[0.9977461,0.0013460041,0.00017025114,0.00053423084,0.00012430748,0.0000790928],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032141989,0.0001268683,0.00036137283,0.0004478421,0.00009023101,0.00019196517,0.00051457586,0.00016413277,0.00022973964],"category_scores_gemma":[0.0025375332,0.000104898456,0.00008388691,0.0005017249,0.0001746475,0.0002869075,0.00012973571,0.00027425683,0.00009195505],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011382614,0.00006068633,0.0671388,0.0000015641448,0.0000057444868,0.000007410575,0.00011452438,0.000029724646,0.00025627593,0.007869458,0.004777689,0.9196243],"study_design_scores_gemma":[0.0011566294,0.00003126382,0.09539803,0.000039916988,0.000006423047,0.000016483596,0.00004713425,0.00015150152,0.0000062843064,0.85513896,0.04792152,0.00008588011],"about_ca_topic_score_codex":0.000081813756,"about_ca_topic_score_gemma":0.0001250654,"teacher_disagreement_score":0.91953844,"about_ca_system_score_codex":0.000049219874,"about_ca_system_score_gemma":0.00010017746,"threshold_uncertainty_score":0.4277635},"labels":[],"label_agreement":null},{"id":"W4409758193","doi":"10.31234/osf.io/yagn5_v1","title":"Demand Avoidance in Value-Based Choice Under Risk: A Behavioral and Pupillometric Examination","year":2025,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Psychology; Behavioral economics; Economics; Microeconomics","score_opus":0.1448529730028883,"score_gpt":0.4307436567416938,"score_spread":0.2858906837388055,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409758193","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9742475,0.0004981339,0.020447392,0.00023301796,0.0010538542,0.0005231125,0.00012564911,0.00007134968,0.0027999836],"genre_scores_gemma":[0.99169797,0.000077301906,0.0053156,0.00017132978,0.00004906536,0.000058473448,0.000019491004,0.000017257438,0.0025935282],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9948348,0.0006604509,0.0014164613,0.0016241561,0.0010860104,0.00037813114],"domain_scores_gemma":[0.9930335,0.004456788,0.0007660138,0.0012466623,0.0003414489,0.00015553497],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0065687206,0.00042513516,0.0008332331,0.0033178537,0.00017183577,0.0010002911,0.0011717641,0.00059526355,0.00024476022],"category_scores_gemma":[0.0033978845,0.00035269046,0.00020921433,0.002034511,0.00014807607,0.00029281157,0.0010739203,0.0009742242,0.00007706995],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026998438,0.00038205087,0.22309442,0.000019399775,0.000008056274,0.000013825336,0.00014027467,0.02510218,0.000011058103,0.00026889835,0.0005497163,0.75038314],"study_design_scores_gemma":[0.0011393704,0.000104110935,0.85353285,0.00024073769,0.00009684619,0.000003073943,0.0002851665,0.051241264,0.00011706867,0.09125594,0.001320387,0.00066318683],"about_ca_topic_score_codex":0.0018332071,"about_ca_topic_score_gemma":0.0015917928,"teacher_disagreement_score":0.7497199,"about_ca_system_score_codex":0.00032735016,"about_ca_system_score_gemma":0.0003616301,"threshold_uncertainty_score":0.99989253},"labels":[],"label_agreement":null},{"id":"W4409885850","doi":"10.1016/j.econlet.2025.112333","title":"An ordinal solution to King Solomon’s dilemma","year":2025,"lang":"en","type":"article","venue":"Economics Letters","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Dilemma; Ordinal optimization; Mathematical economics; Mathematics; Economics; Ordinal data; Econometrics; Statistics; Geometry","score_opus":0.08090749598835148,"score_gpt":0.39206883872427095,"score_spread":0.31116134273591944,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409885850","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9653351,0.0000063884236,0.016841553,0.013326596,0.0021398226,0.00015375207,0.00001988207,0.00006265464,0.0021142636],"genre_scores_gemma":[0.98378575,0.0000022215672,0.004430286,0.011288071,0.00018473541,0.000015327409,0.000006087511,0.000015514715,0.0002719836],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9977673,0.0000823937,0.000796869,0.0008120436,0.00015112889,0.00039020836],"domain_scores_gemma":[0.9982149,0.00038187558,0.00020013939,0.0009487108,0.00007575338,0.00017862028],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001721662,0.00019249287,0.0003510977,0.00062975555,0.0002686792,0.0008897346,0.0011550747,0.00009369661,0.00019624106],"category_scores_gemma":[0.0003386796,0.0001864859,0.00015664664,0.00032554904,0.000067505694,0.00068385847,0.00022461163,0.00016216848,0.0010648136],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009441588,0.00008232834,0.024801673,0.0000014447586,0.000019290675,0.0000106765865,0.00032566529,0.019859621,0.006841845,0.0026956405,0.044475757,0.90079165],"study_design_scores_gemma":[0.0020077403,0.00042528426,0.102149695,0.0001145886,0.00009278125,0.000041810832,0.0018616992,0.06543186,0.0043381783,0.16300274,0.658425,0.0021086135],"about_ca_topic_score_codex":0.0001603985,"about_ca_topic_score_gemma":0.0003205334,"teacher_disagreement_score":0.898683,"about_ca_system_score_codex":0.00030411093,"about_ca_system_score_gemma":0.00007887392,"threshold_uncertainty_score":0.99971294},"labels":[],"label_agreement":null},{"id":"W4409986538","doi":"10.31234/osf.io/7axzk_v1","title":"Effects of initial experiences on risky choice","year":2025,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Economic and Social Research Council; Alberta Gambling Research Institute, University of Calgary; Natural Sciences and Engineering Research Council of Canada; Leverhulme Trust","keywords":"Psychology; Social psychology; Economics","score_opus":0.13562861103111365,"score_gpt":0.48749342041110116,"score_spread":0.35186480937998754,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409986538","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94110316,0.0000991698,0.0009832841,0.00011747891,0.005288042,0.0003401161,0.000035851564,0.000056907258,0.051975995],"genre_scores_gemma":[0.9942962,0.00002036283,0.0011248797,0.0003121739,0.00017540855,0.00008503886,0.0000033121125,0.000008423507,0.003974201],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9961501,0.000222486,0.0011917384,0.0010502245,0.0011462285,0.00023924235],"domain_scores_gemma":[0.9893832,0.008313095,0.000658639,0.0012403703,0.0002975999,0.00010707426],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013339123,0.00031318518,0.00084208715,0.0006533107,0.000095283634,0.0003486984,0.002215865,0.0004008022,0.0008907343],"category_scores_gemma":[0.006076314,0.00021641627,0.00040101938,0.00038270367,0.00018579226,0.00011854454,0.0015015372,0.000490964,0.00031666653],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000930527,0.0003549549,0.00094882544,0.000046187317,0.000025046875,0.000019137497,0.0022977781,0.0007651597,0.000039272636,0.0007132547,0.01722701,0.97747034],"study_design_scores_gemma":[0.0032611166,0.0016862366,0.022156887,0.0034014368,0.0003399569,0.000008282828,0.012507801,0.005826339,0.12601267,0.6926983,0.12887442,0.0032265512],"about_ca_topic_score_codex":0.00030119455,"about_ca_topic_score_gemma":0.00005172693,"teacher_disagreement_score":0.97424376,"about_ca_system_score_codex":0.00005422264,"about_ca_system_score_gemma":0.00028952566,"threshold_uncertainty_score":0.9752916},"labels":[],"label_agreement":null},{"id":"W4409990368","doi":"10.1101/2025.04.28.650827","title":"Is the whole the sum of its parts? Neural computation of consumer bundle valuation in humans","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"National Institute of Mental Health; Social Sciences and Humanities Research Council; National Institute on Drug Abuse; Social Sciences and Humanities Research Council of Canada; California Institute of Technology","keywords":"Valuation (finance); Bundle; Computation; Computer science; Mathematical economics; Artificial intelligence; Mathematics; Econometrics; Economics; Algorithm; Finance; Materials science","score_opus":0.11650533807189031,"score_gpt":0.35634101721745204,"score_spread":0.23983567914556173,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409990368","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9948248,0.0008965075,0.0009252835,0.0009597372,0.001315553,0.0007096382,0.00031875432,0.000029679803,0.000020014528],"genre_scores_gemma":[0.9992468,0.0000677607,0.00033327492,0.00020222054,0.000058879632,0.00005432773,2.719999e-7,0.0000196915,0.000016809487],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9959777,0.0005336235,0.0015269442,0.0007466513,0.0009498193,0.00026523587],"domain_scores_gemma":[0.99457777,0.0012588801,0.0013411025,0.0014628611,0.0013024193,0.000056991845],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004790899,0.00029831988,0.0006391055,0.00042993732,0.00016701256,0.0002831244,0.0014819695,0.0002788992,0.00005010804],"category_scores_gemma":[0.0015482957,0.00019617513,0.00024079812,0.0010033372,0.00027255548,0.0001894537,0.00063050556,0.000524817,0.000052188916],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00056050764,0.0035767057,0.6317826,0.00097535155,0.0006537659,0.00003263846,0.0029663541,0.15222488,0.16959956,0.008281222,0.02363502,0.0057114395],"study_design_scores_gemma":[0.0013742363,0.00017376244,0.8190647,0.0013389506,0.0003469738,2.2311713e-8,0.00023475525,0.08726559,0.07658689,0.0020731385,0.010539002,0.0010020122],"about_ca_topic_score_codex":0.00010356762,"about_ca_topic_score_gemma":0.000037002763,"teacher_disagreement_score":0.18728212,"about_ca_system_score_codex":0.00010387871,"about_ca_system_score_gemma":0.00053781545,"threshold_uncertainty_score":0.799979},"labels":[],"label_agreement":null},{"id":"W4410105204","doi":"10.1016/j.cognition.2025.106166","title":"Who benefits from debiasing?","year":2025,"lang":"en","type":"article","venue":"Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"Social Sciences and Humanities Research Council of Canada; Fondation Fyssen","keywords":"Debiasing; Psychology; Cognitive psychology; Social psychology","score_opus":0.1522446181558466,"score_gpt":0.4132383597284898,"score_spread":0.2609937415726432,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410105204","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.948439,0.0001797695,0.003044921,0.0005221911,0.00076757924,0.00007222681,0.00006686322,0.00004901617,0.04685845],"genre_scores_gemma":[0.99724066,0.000014811823,0.00059133745,0.0009615005,0.00006124202,0.000005529145,0.000023606535,0.0000051548254,0.001096143],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9987432,0.00005303968,0.0003923281,0.00037644,0.0003071038,0.00012788571],"domain_scores_gemma":[0.99834174,0.0009174907,0.000107975306,0.00033826483,0.0002460021,0.00004855431],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005311684,0.00008777526,0.00017965457,0.0002281313,0.00014786233,0.0003615968,0.00032119613,0.000089192974,0.0006954018],"category_scores_gemma":[0.0013758331,0.000073147094,0.00008678089,0.0004137091,0.000043506156,0.00024574625,0.00009427054,0.00008739711,0.0016338214],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018538549,0.000031803826,0.0024268979,3.279662e-7,0.000004094796,0.0000022874112,0.000036801364,0.000019536503,0.0001819694,0.00036228265,0.009793521,0.98712194],"study_design_scores_gemma":[0.00048709867,0.000027108852,0.070822865,0.00015615512,0.000045830195,0.0000017692157,0.0002899021,0.0011457445,0.00444318,0.87814826,0.044256605,0.00017551011],"about_ca_topic_score_codex":0.000017339646,"about_ca_topic_score_gemma":0.00006505462,"teacher_disagreement_score":0.9869464,"about_ca_system_score_codex":0.00002755113,"about_ca_system_score_gemma":0.000043390024,"threshold_uncertainty_score":0.99914354},"labels":[],"label_agreement":null},{"id":"W4410211897","doi":"10.1080/19345747.2026.2682772","title":"External Validity Bias of Purposive and Random Site Selection When Sites Can Opt Out: Evidence from the Head Start Program","year":2025,"lang":"en","type":"preprint","venue":"Journal of Research on Educational Effectiveness","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bell (Canada)","funders":"Institute of Education Sciences","keywords":"Selection (genetic algorithm); Selection bias; Head (geology); Head start; Statistics; Site selection; Psychology; Computer science; Econometrics; Mathematics; Political science; Artificial intelligence; Biology; Law; Developmental psychology","score_opus":0.5488848819157832,"score_gpt":0.5824548225167185,"score_spread":0.03356994060093532,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410211897","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.987843,0.0013877612,0.001054192,0.006151148,0.001696465,0.0015620812,0.0002562986,0.0000073170013,0.00004176783],"genre_scores_gemma":[0.9957762,0.00023442697,0.0027631125,0.000044239692,0.0007384627,0.00019185359,0.000012031231,0.000013781923,0.00022589265],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.98823476,0.0060560587,0.0013200652,0.0007232549,0.0033378135,0.00032806437],"domain_scores_gemma":[0.91805303,0.073863715,0.0013790953,0.00061132625,0.0058742613,0.00021859148],"candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.02888066,0.000288102,0.00090300327,0.0010243981,0.00039078156,0.0010110474,0.001597009,0.00024266816,0.0001426543],"category_scores_gemma":[0.02895594,0.00017859746,0.0004257961,0.0006226071,0.00047633916,0.00037744382,0.0007151061,0.0019716471,0.000016315107],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.007139451,0.001762889,0.64802283,0.00018374374,0.00027976706,0.000017255521,0.0038873425,0.0071419217,0.0025018866,0.0002229844,0.006268329,0.3225716],"study_design_scores_gemma":[0.0011045464,0.0013316153,0.62428194,0.006282316,0.00010253813,0.000031746164,0.0005050019,0.0008414562,0.0038706404,0.3603476,0.0010657102,0.0002348764],"about_ca_topic_score_codex":0.0016975221,"about_ca_topic_score_gemma":0.0009857527,"teacher_disagreement_score":0.36012462,"about_ca_system_score_codex":0.0006390821,"about_ca_system_score_gemma":0.003864633,"threshold_uncertainty_score":0.99997175},"labels":[],"label_agreement":null},{"id":"W4410344498","doi":"10.3758/s13414-025-03084-9","title":"Reducing the low prevalence effect: Does similarity search translate to binary decisions?","year":2025,"lang":"en","type":"article","venue":"Attention Perception & Psychophysics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Similarity (geometry); Psychology; Binary number; Cognitive psychology; Computer science; Social psychology; Communication; Artificial intelligence; Mathematics; Arithmetic","score_opus":0.06338854389383163,"score_gpt":0.4271059002496588,"score_spread":0.36371735635582714,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410344498","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9705529,0.000029042852,0.018813018,0.005922418,0.0026070348,0.00074699527,0.000041710657,0.00009906625,0.0011878173],"genre_scores_gemma":[0.99295884,0.0001002142,0.0010796745,0.0011335554,0.0001858582,0.00006344271,0.000011259778,0.000022223001,0.0044449163],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99549603,0.0006178374,0.0010141492,0.0011701969,0.0012672486,0.00043451984],"domain_scores_gemma":[0.9957861,0.0017366456,0.0001806558,0.001644966,0.00047914963,0.00017251655],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0039666537,0.00031046692,0.00040963315,0.00045319457,0.00087621046,0.00079096487,0.0014329792,0.00017149202,0.0007591124],"category_scores_gemma":[0.0005890532,0.00018477209,0.00048281293,0.0019959174,0.00019176475,0.0006526254,0.00021699596,0.00048226002,0.002555747],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021936985,0.00022876928,0.005541684,0.000015470165,0.000016460941,0.0000026387854,0.0007177461,0.0019094467,0.03806123,0.00012365647,0.011398302,0.94176525],"study_design_scores_gemma":[0.0017753587,0.0006032258,0.8573902,0.001138589,0.00019439685,0.000010430916,0.0024713452,0.010670422,0.0010683192,0.11118447,0.012555946,0.0009372656],"about_ca_topic_score_codex":0.000043369295,"about_ca_topic_score_gemma":0.000020712654,"teacher_disagreement_score":0.94082797,"about_ca_system_score_codex":0.00012966641,"about_ca_system_score_gemma":0.00007858673,"threshold_uncertainty_score":0.99822086},"labels":[],"label_agreement":null},{"id":"W4410346241","doi":"10.31235/osf.io/4dynh_v1","title":"What Makes a Decision Fair? Relative Earnings, Gender, and Justifications for Couples’ Decision Making","year":2018,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Earnings; Economics; Business; Actuarial science; Psychology; Accounting","score_opus":0.2408080043185134,"score_gpt":0.4574832723146353,"score_spread":0.2166752679961219,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410346241","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4971034,0.001151074,0.4930769,0.00030069222,0.0054730047,0.0012107458,0.00016192003,0.00015755711,0.0013647182],"genre_scores_gemma":[0.72187275,0.0008886531,0.27460217,0.00026642682,0.00040094194,0.00018046187,0.00004613863,0.00009481733,0.001647606],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9917546,0.00019339331,0.0025554916,0.003045034,0.0017840961,0.00066738797],"domain_scores_gemma":[0.9742137,0.01914036,0.0017262355,0.002588363,0.0019948427,0.00033645384],"candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0068333386,0.00076348067,0.0012623696,0.0012366348,0.0010229175,0.0054830047,0.0021862416,0.0010725918,0.00095725217],"category_scores_gemma":[0.015972821,0.0005896805,0.0006133966,0.0006163453,0.00048659692,0.0016259776,0.0028158992,0.0008629309,0.0007785587],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003028607,0.00011041649,0.0014768923,0.000016624976,0.00004310229,0.0000068419918,0.001256391,0.00105465,0.000021695138,0.0016718112,0.029506342,0.9645324],"study_design_scores_gemma":[0.00063887046,0.00016533579,0.009066776,0.0010583879,0.00017306593,0.00003641436,0.0046559144,0.039510243,0.0000330572,0.8971468,0.046648026,0.0008670603],"about_ca_topic_score_codex":0.000015105235,"about_ca_topic_score_gemma":0.00011083412,"teacher_disagreement_score":0.9636653,"about_ca_system_score_codex":0.00025950614,"about_ca_system_score_gemma":0.00038173283,"threshold_uncertainty_score":0.99999946},"labels":[],"label_agreement":null},{"id":"W4410359562","doi":"10.1287/mnsc.2022.00304","title":"Using AI and Behavioral Finance to Cope with Limited Attention and Reduce Overdraft Fees","year":2025,"lang":"en","type":"article","venue":"Management Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Overdraft; Behavioral economics; Business; Finance; Actuarial science; Economics","score_opus":0.12849858642739093,"score_gpt":0.44677504819091796,"score_spread":0.31827646176352703,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410359562","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9879542,0.00003064968,0.008470702,0.0010426214,0.00027718197,0.0002835056,0.0000032859432,0.000024262055,0.0019136003],"genre_scores_gemma":[0.986226,0.000011517643,0.011124399,0.00057024736,0.0000075772364,0.00000809451,2.8925223e-7,0.0000043675595,0.0020475108],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9978641,0.000026383706,0.0003142605,0.0008586475,0.00065773685,0.00027884307],"domain_scores_gemma":[0.9991062,0.000057636793,0.000104966624,0.0004980649,0.00014337881,0.00008974294],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0015338688,0.00013218485,0.00018265213,0.0006835097,0.00050480524,0.0011476375,0.0005920518,0.000027158187,0.000013898021],"category_scores_gemma":[0.00010276816,0.00010055674,0.000020805004,0.002083998,0.000436965,0.0007707432,0.00071296963,0.00006980041,0.000023121394],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000087854416,0.00011076463,0.085423894,0.000008356605,0.000005199282,0.00003215714,0.00023478884,0.0010833727,0.0029366896,0.0044465885,0.001902901,0.9037274],"study_design_scores_gemma":[0.0009100034,0.0003162218,0.9459059,0.0003548771,0.00008500174,0.000020120055,0.0016010489,0.02383509,0.0007006923,0.012144266,0.01360307,0.00052366604],"about_ca_topic_score_codex":0.000040712024,"about_ca_topic_score_gemma":0.00002739268,"teacher_disagreement_score":0.9032038,"about_ca_system_score_codex":0.00007252975,"about_ca_system_score_gemma":0.000042183026,"threshold_uncertainty_score":0.99988925},"labels":[],"label_agreement":null},{"id":"W4410455261","doi":"10.1152/jn.00563.2024","title":"Indecision under time pressure arises from suboptimal switching behavior","year":2025,"lang":"en","type":"article","venue":"Journal of Neurophysiology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"National Science Foundation Graduate Research Fellowship Program; Natural Sciences and Engineering Research Council of Canada","keywords":"Stimulus (psychology); Psychology; Econometrics; Cognitive psychology; Economics","score_opus":0.07470895694054341,"score_gpt":0.38633868561251494,"score_spread":0.31162972867197153,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410455261","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.994473,0.00011882237,0.002019581,0.00069734675,0.002272004,0.0000852982,0.00002144496,0.000016136248,0.00029636963],"genre_scores_gemma":[0.99624807,0.000028902357,0.0020845756,0.0006919708,0.0002603653,0.0000016017626,0.00000156323,0.000015996702,0.0006669569],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9967637,0.00034827422,0.0015067123,0.00047887038,0.0006386116,0.00026385405],"domain_scores_gemma":[0.9949103,0.0028062416,0.000985476,0.0006444772,0.0005245609,0.00012895545],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049338856,0.00021859721,0.000781652,0.0006188308,0.0001664775,0.0002605805,0.0014386964,0.00020221274,0.0006932208],"category_scores_gemma":[0.0014871333,0.00015050046,0.0003806185,0.00045554753,0.00009639935,0.00044347713,0.00038248478,0.0006333815,0.00040951787],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00088092196,0.0005755931,0.002660274,0.0000018400582,0.00008693174,0.0003367065,0.00011839679,0.015987525,0.47070873,0.00015103052,0.011871875,0.49662018],"study_design_scores_gemma":[0.0017980868,0.001158952,0.6014864,0.00011421471,0.0004314662,0.00016927076,0.0002536919,0.0046228534,0.0020545742,0.35216746,0.035290156,0.0004528715],"about_ca_topic_score_codex":0.000021744992,"about_ca_topic_score_gemma":0.0000016658288,"teacher_disagreement_score":0.5988261,"about_ca_system_score_codex":0.000036852725,"about_ca_system_score_gemma":0.00019483123,"threshold_uncertainty_score":0.7590282},"labels":[],"label_agreement":null},{"id":"W4410489681","doi":"10.1016/j.tics.2025.04.004","title":"A timeline of cognitive costs in decision-making","year":2025,"lang":"en","type":"review","venue":"Trends in Cognitive Sciences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; University of Alberta","funders":"","keywords":"Timeline; Psychology; Cognition; Cognitive science; Cognitive psychology; Neuroscience","score_opus":0.4353459263007651,"score_gpt":0.5888044144914303,"score_spread":0.1534584881906652,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410489681","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0047737584,0.94242996,0.00037621692,0.00002521971,0.0010824553,0.00064862415,0.00095059216,0.000029918,0.049683243],"genre_scores_gemma":[0.08826093,0.9091698,0.0012627934,0.00010742866,0.00008774845,0.00013356197,0.000055854343,0.000034052497,0.0008878454],"study_design_codex":"design_other","study_design_gemma":"systematic_review","domain_scores_codex":[0.99048537,0.00090089155,0.0037069153,0.0022185305,0.0019476461,0.0007406653],"domain_scores_gemma":[0.9361071,0.060781308,0.0017781695,0.0005555384,0.0006555937,0.00012230274],"candidate_categories":["metaresearch","metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.010169059,0.00070844765,0.003609531,0.010101192,0.00019054255,0.00040136022,0.0025884716,0.00047999446,0.0016684363],"category_scores_gemma":[0.033405755,0.0005086356,0.00080414227,0.015207264,0.001350636,0.00058578653,0.0009087468,0.0007897903,0.0002502664],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000045178775,0.000232006,0.00053391315,0.00008782771,0.000013434021,0.0000722226,0.00016469904,0.00000730847,1.9676069e-8,0.000060026257,0.00028099935,0.9985024],"study_design_scores_gemma":[0.003787164,0.0013962304,0.0031904478,0.7556358,0.0012160963,0.00014304343,0.00915928,0.0012025015,0.000006432219,0.10769455,0.11267673,0.0038916972],"about_ca_topic_score_codex":0.00009517994,"about_ca_topic_score_gemma":0.0014872671,"teacher_disagreement_score":0.99461067,"about_ca_system_score_codex":0.0002763078,"about_ca_system_score_gemma":0.0012406387,"threshold_uncertainty_score":0.99973655},"labels":[],"label_agreement":null},{"id":"W4410529655","doi":"10.1016/j.semperi.2025.152051","title":"Perinatal decision making as a decision scientist","year":2025,"lang":"en","type":"review","venue":"Seminars in Perinatology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Michael's Hospital","funders":"","keywords":"Medicine; Clinical decision making; Intensive care medicine","score_opus":0.07389584849984555,"score_gpt":0.4781563051040902,"score_spread":0.40426045660424464,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410529655","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0066642216,0.97548205,0.00045509543,0.00002799227,0.0066545038,0.0008439198,0.00043336095,0.00009063637,0.009348245],"genre_scores_gemma":[0.0015705669,0.9851837,0.009656393,0.00011925778,0.00009141511,0.00022116225,0.00004948576,0.000086081585,0.0030219383],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9894792,0.0006502548,0.0038106248,0.0031732093,0.0017271754,0.0011595795],"domain_scores_gemma":[0.97323716,0.022087723,0.0012592091,0.0028223612,0.0003584736,0.00023507398],"candidate_categories":["metaresearch","metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.004813205,0.0010775799,0.0046517956,0.005159251,0.0004623213,0.00090296974,0.0052959938,0.0015680679,0.006017429],"category_scores_gemma":[0.02485846,0.00086315535,0.0013696087,0.0046199053,0.0006322439,0.00043579127,0.0032074146,0.0014591778,0.003991549],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000062631065,0.00010600056,0.00006235283,0.00044810053,0.000012807327,0.0012971841,0.00006800882,0.0000074580375,2.9083164e-8,0.0008776616,0.011647577,0.9854102],"study_design_scores_gemma":[0.0002539413,0.000117338815,0.000017435541,0.03696685,0.000084521875,0.00179615,0.00013919627,0.00007201501,2.40254e-7,0.06719143,0.8926613,0.00069963076],"about_ca_topic_score_codex":0.000019415038,"about_ca_topic_score_gemma":0.00014112456,"teacher_disagreement_score":0.9847106,"about_ca_system_score_codex":0.0008199331,"about_ca_system_score_gemma":0.0014801135,"threshold_uncertainty_score":0.9997281},"labels":[],"label_agreement":null},{"id":"W4410543962","doi":"10.3758/s13423-025-02713-6","title":"Evidence for some form of abstract logical intuition","year":2025,"lang":"en","type":"article","venue":"Psychonomic Bulletin & Review","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Intuition; Psychology; Cognitive science; Cognitive psychology; Epistemology; Philosophy","score_opus":0.3690713961149358,"score_gpt":0.5045738420001691,"score_spread":0.1355024458852333,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410543962","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.48832253,0.38476864,0.017736368,0.07464744,0.0078916745,0.005660226,0.00017879483,0.00017591692,0.020618428],"genre_scores_gemma":[0.8883176,0.093155585,0.0065992298,0.009337791,0.0002339751,0.00030381742,0.000011284271,0.000026010304,0.0020147248],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9970878,0.00007060741,0.0016950795,0.0006385208,0.00027189852,0.00023611139],"domain_scores_gemma":[0.9951096,0.003061335,0.00065993407,0.00087909104,0.00021308147,0.00007696994],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0047759204,0.00018484512,0.00076227705,0.0001711094,0.000086572996,0.00010480069,0.0010373527,0.000088824236,0.0028317038],"category_scores_gemma":[0.0038727722,0.00013556467,0.00048305225,0.0002699237,0.00010443959,0.00016862422,0.00011301011,0.0001430467,0.001384902],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000053550295,0.00006921924,0.00010988109,0.0002046643,0.000006961211,4.3962027e-7,0.000006814609,0.0000031023833,0.000039658524,0.0022081288,0.20379223,0.7935054],"study_design_scores_gemma":[0.00027861728,0.00008487729,0.0017931864,0.0054666097,0.000053437507,0.000004135737,0.000016939603,0.000026641868,0.000055059536,0.21937846,0.7726863,0.00015572392],"about_ca_topic_score_codex":0.0000100799725,"about_ca_topic_score_gemma":0.0000029192402,"teacher_disagreement_score":0.7933496,"about_ca_system_score_codex":0.000078729485,"about_ca_system_score_gemma":0.00008339344,"threshold_uncertainty_score":0.9993926},"labels":[],"label_agreement":null},{"id":"W4411006547","doi":"10.1111/1911-3838.12406","title":"Earnings Disclosures and Investor Judgments: The Joint Effect of Incidental Affect and Emotion‐Understanding Ability<sup>*</sup>","year":2025,"lang":"en","type":"article","venue":"Accounting Perspectives","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Affect (linguistics); Earnings; Psychology; Joint (building); Business; Accounting; Communication","score_opus":0.061525651496332386,"score_gpt":0.3578897002055685,"score_spread":0.2963640487092361,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411006547","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99658275,0.00054871966,0.00041931262,0.00084148766,0.00017638203,0.00032325913,0.00000750669,0.000036787143,0.0010637736],"genre_scores_gemma":[0.99956477,0.000030212483,0.00014018074,0.000064478925,0.000050365787,0.000009689565,6.858712e-7,0.000011690566,0.00012793225],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9976714,0.0003657041,0.0005486218,0.00066333456,0.00051713875,0.00023376959],"domain_scores_gemma":[0.9954398,0.0035838173,0.00034265115,0.00044556343,0.00013411997,0.000054010437],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004938505,0.00022130307,0.0004716338,0.00038331532,0.00056406745,0.0006407995,0.00037395113,0.00008982721,0.000046738045],"category_scores_gemma":[0.0067826035,0.00013596109,0.00014027694,0.00051186077,0.0007790465,0.0006041786,0.00046594194,0.00025997462,0.000008341161],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010921952,0.000071171904,0.9503645,0.000038518665,0.00007386851,0.0000028648676,0.019301342,0.00019177626,0.0015949095,0.0031837472,0.00086166314,0.02420644],"study_design_scores_gemma":[0.0011836978,0.0003778026,0.78506744,0.00033973437,0.00014094087,0.000022011634,0.14084728,0.003207056,0.0008939841,0.067236416,0.00033127517,0.0003523425],"about_ca_topic_score_codex":0.0001902516,"about_ca_topic_score_gemma":0.000028266064,"teacher_disagreement_score":0.16529702,"about_ca_system_score_codex":0.00021067125,"about_ca_system_score_gemma":0.00004586241,"threshold_uncertainty_score":0.81198996},"labels":[],"label_agreement":null},{"id":"W4411007051","doi":"10.1111/bjop.70000","title":"Higher‐pitched voices are perceived as financially trustworthy","year":2025,"lang":"en","type":"article","venue":"British Journal of Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Trustworthiness; Perception; Psychology; Risk perception; Social psychology","score_opus":0.07755412290037801,"score_gpt":0.43577947062635936,"score_spread":0.35822534772598136,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411007051","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9734958,0.0015795225,0.00050315185,0.0041035037,0.005418077,0.00006974083,0.000013709454,0.000016446269,0.014800086],"genre_scores_gemma":[0.9897682,0.00039487434,0.0012965032,0.0037407784,0.0003455897,0.0000020801028,7.6479796e-7,0.0000124188045,0.0044387756],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9968988,0.00027904534,0.0015137198,0.00044975124,0.00054762844,0.00031106497],"domain_scores_gemma":[0.99686,0.00067940744,0.0011231888,0.00041850403,0.00077289075,0.00014600456],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0024928474,0.00015667532,0.00070092175,0.00050532474,0.00018773356,0.00044779113,0.0014533089,0.00024930437,0.0017577732],"category_scores_gemma":[0.0022194267,0.00015082424,0.00036948422,0.00061914726,0.00018366586,0.00035424964,0.000103105755,0.00052755955,0.0003900146],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016169931,0.00019636509,0.008424885,0.0000014194931,0.000024966088,0.001151119,0.000065567714,0.000024468627,0.0002876388,0.00017245243,0.13301222,0.8564772],"study_design_scores_gemma":[0.001192252,0.00020370052,0.6098689,0.00017290999,0.00003273945,0.001902109,0.00023607173,0.0000056920658,0.000017796945,0.14735852,0.23885803,0.0001512939],"about_ca_topic_score_codex":0.000051150557,"about_ca_topic_score_gemma":0.0002464414,"teacher_disagreement_score":0.8563259,"about_ca_system_score_codex":0.000050164275,"about_ca_system_score_gemma":0.00020763982,"threshold_uncertainty_score":0.99915475},"labels":[],"label_agreement":null},{"id":"W4412055620","doi":"10.1145/3719160.3735655","title":"Values in the Loop: Designing Interactive Optimization with Conversational Feedback","year":2025,"lang":"en","type":"article","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Feedback loop; Computer science; Loop (graph theory); Human–computer interaction; Control theory (sociology); Artificial intelligence; Mathematics; Control (management); World Wide Web","score_opus":0.07985621415196145,"score_gpt":0.38552600601176634,"score_spread":0.3056697918598049,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412055620","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.57290804,0.00001246783,0.38561496,0.0022137244,0.00026464363,0.00020908401,0.0000024496737,0.000023008348,0.038751584],"genre_scores_gemma":[0.97830147,0.000001918161,0.019012237,0.00097447546,0.000013560606,0.000009014161,0.0000029834387,0.0000031874854,0.0016811467],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987275,0.00015588017,0.0003415098,0.00028208402,0.0003868951,0.00010614445],"domain_scores_gemma":[0.99694276,0.0024647426,0.000111958725,0.00026279612,0.00020021544,0.000017534094],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016207244,0.00008208078,0.00013327258,0.00026930784,0.00010276149,0.00041230395,0.00046951367,0.00003851013,0.0005596591],"category_scores_gemma":[0.00070351234,0.00004269975,0.000036386038,0.0006878819,0.00007131445,0.0004358369,0.00005416846,0.00010938275,0.00011022573],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00042778565,0.0002847728,0.06602746,0.000002020807,0.000029505247,0.000019973457,0.004210772,0.54958457,0.00005409573,0.007200192,0.023245322,0.34891352],"study_design_scores_gemma":[0.002710695,0.00031401252,0.056521222,0.00022292757,0.000057799392,0.000029354098,0.063183285,0.6148397,0.0011306303,0.25578558,0.004631175,0.00057366013],"about_ca_topic_score_codex":0.00003871602,"about_ca_topic_score_gemma":0.000053850592,"teacher_disagreement_score":0.4053934,"about_ca_system_score_codex":0.0000570593,"about_ca_system_score_gemma":0.00010079151,"threshold_uncertainty_score":0.6127875},"labels":[],"label_agreement":null},{"id":"W4412459220","doi":"10.1167/jov.25.9.1880","title":"Deep Reinforcement Learning's Struggle with Visuospatial Reasoning: Insights from the Same-Different Task","year":2025,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Task (project management); Reinforcement learning; Reinforcement; Cognitive psychology; Psychology; Computer science; Cognitive science; Artificial intelligence; Social psychology; Engineering","score_opus":0.03132511678826457,"score_gpt":0.34724241570343756,"score_spread":0.315917298915173,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412459220","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96451175,0.00035228152,0.032104585,0.0010212663,0.0009632125,0.00010991803,9.904275e-7,0.000011467489,0.0009245549],"genre_scores_gemma":[0.99804085,0.00005562205,0.00087315834,0.0002984676,0.00019700151,0.000001285236,0.00000253054,0.000010373611,0.0005206979],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9967517,0.000250865,0.001157727,0.0003014284,0.0013482753,0.00018995344],"domain_scores_gemma":[0.995971,0.0017268829,0.0011573822,0.0004983827,0.0005227187,0.00012363259],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010665875,0.00019553083,0.00046981234,0.0002734752,0.00035572777,0.0006304842,0.0009973147,0.00009934195,0.00030656162],"category_scores_gemma":[0.0013555051,0.00008848041,0.00021569806,0.0004148256,0.000090556096,0.00039436968,0.00022964395,0.0005499797,0.000061321516],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015306036,0.00029461604,0.024082605,0.0000023496034,0.00011394772,0.0000828821,0.0021063588,0.07024514,0.0020924883,0.00058780896,0.01723787,0.8816233],"study_design_scores_gemma":[0.006961833,0.006921276,0.4877543,0.0022432613,0.00045823492,0.000107877604,0.009694469,0.15821168,0.0025586172,0.11696445,0.20717178,0.0009522245],"about_ca_topic_score_codex":0.000069375674,"about_ca_topic_score_gemma":0.00013951401,"teacher_disagreement_score":0.8806711,"about_ca_system_score_codex":0.00013386182,"about_ca_system_score_gemma":0.00014860874,"threshold_uncertainty_score":0.6079774},"labels":[],"label_agreement":null},{"id":"W4412530079","doi":"10.1038/s41467-025-61960-2","title":"Estimation-uncertainty affects decisions with and without learning opportunities","year":2025,"lang":"en","type":"article","venue":"Nature Communications","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Israel Science Foundation; Carnegie Mellon University","keywords":"Estimation; Computer science; Econometrics; Data science; Mathematics; Economics","score_opus":0.15519798356545453,"score_gpt":0.4369713376031308,"score_spread":0.2817733540376762,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412530079","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93071294,0.0032041825,0.009565181,0.014847459,0.00032822596,0.00040678485,0.000028505874,0.00019533018,0.040711407],"genre_scores_gemma":[0.9748554,0.0003841226,0.022017807,0.00056043756,0.000009765582,0.000033478504,0.000028412129,0.00001096847,0.0020995755],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99833345,0.00029585863,0.00040352883,0.0003657456,0.00042357546,0.00017782724],"domain_scores_gemma":[0.9915323,0.0056361333,0.00023071562,0.0020849358,0.000408356,0.000107561915],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015108549,0.00016541533,0.0002984071,0.00047860327,0.0010219913,0.00054418866,0.0015778297,0.00022018257,0.0000364168],"category_scores_gemma":[0.005251898,0.00011748023,0.00006216001,0.0007487254,0.0003837786,0.00035168248,0.000668654,0.0009560043,0.000033944696],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000034176865,0.000076757606,0.03255233,0.0000015057634,0.000024094621,0.0000014479549,0.0002757205,0.0023945589,0.000017966973,0.03539681,0.007831438,0.9213932],"study_design_scores_gemma":[0.0011645824,0.00017660888,0.05233701,0.00045641183,0.00015851446,0.00005438854,0.0058169398,0.15054934,0.000049397684,0.13534567,0.6532704,0.0006207165],"about_ca_topic_score_codex":0.000021495023,"about_ca_topic_score_gemma":0.0006975814,"teacher_disagreement_score":0.9207725,"about_ca_system_score_codex":0.000054600805,"about_ca_system_score_gemma":0.00021884932,"threshold_uncertainty_score":0.7860434},"labels":[],"label_agreement":null},{"id":"W4412557757","doi":"10.2139/ssrn.5361638","title":"Speaking of Inflation: The Influence of Fed Speeches on Expectations","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Government of Canada; Bank of Canada","funders":"","keywords":"Inflation (cosmology); Economics; Monetary economics; Keynesian economics; Physics; Theoretical physics","score_opus":0.0732826693842516,"score_gpt":0.39193106678777734,"score_spread":0.31864839740352574,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412557757","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.994119,0.0006178538,0.0018456504,0.0006803414,0.0005142447,0.00018778301,0.000023217182,0.000011141746,0.002000753],"genre_scores_gemma":[0.99861383,0.0003998116,0.00034136832,0.00004171742,0.00012764176,0.0000049361925,0.0000021722005,0.000009715284,0.0004587831],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99587476,0.0002826148,0.0016184082,0.0004045955,0.0010933363,0.00072630984],"domain_scores_gemma":[0.99419147,0.0019198401,0.0021040412,0.00091350457,0.00082596147,0.000045180124],"candidate_categories":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0058814255,0.00022909614,0.00055971026,0.0006282144,0.00023267891,0.0002104064,0.0020069315,0.00020120673,0.00004605866],"category_scores_gemma":[0.0029207459,0.00014691877,0.0004096537,0.00056468695,0.00016731347,0.00018234318,0.00043918146,0.002629415,0.000030320112],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022376145,0.0001618364,0.00500161,0.000012480957,0.0001913928,0.0000029304192,0.0025024521,0.1317256,0.0002355683,0.040260486,0.00020304012,0.81947887],"study_design_scores_gemma":[0.00022799274,0.00018012554,0.005041322,0.00029349508,0.000062254025,0.00003122509,0.006367114,0.000377136,0.00037097163,0.98643917,0.00044995346,0.00015924565],"about_ca_topic_score_codex":0.00010725301,"about_ca_topic_score_gemma":0.00069460255,"teacher_disagreement_score":0.9461787,"about_ca_system_score_codex":0.00049211987,"about_ca_system_score_gemma":0.0041588866,"threshold_uncertainty_score":0.9996716},"labels":[],"label_agreement":null},{"id":"W4412588131","doi":"10.1007/s11238-025-10073-9","title":"A duality between utility transforms and probability distortions","year":2025,"lang":"en","type":"article","venue":"Theory and Decision","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Duality (order theory); Expected utility hypothesis; Mathematical economics; Mathematics; Utility theory; Applied mathematics; Mathematical optimization; Economics; Discrete mathematics","score_opus":0.10523689138528741,"score_gpt":0.41825811575637145,"score_spread":0.31302122437108404,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412588131","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8876761,0.00023550486,0.107698746,0.00024221349,0.00023081715,0.0002419898,0.00006854994,0.000046720714,0.0035593603],"genre_scores_gemma":[0.9981323,0.000026755499,0.0013801678,0.00012027928,0.00002437919,0.000008983259,0.0000035138748,0.0000050694784,0.0002985777],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9972777,0.00037729455,0.00092055777,0.0007705418,0.00043407845,0.00021984517],"domain_scores_gemma":[0.99123585,0.0075086514,0.00012581203,0.0008097662,0.00015114572,0.00016877083],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01266882,0.00018187248,0.00046340187,0.00022088799,0.00047077084,0.00030633717,0.00038003395,0.0001560068,0.00020137388],"category_scores_gemma":[0.0038187397,0.00012027974,0.0001238634,0.00047837125,0.00046085494,0.00039978384,0.00023938039,0.0001996038,0.00004186143],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000318352,0.000065260065,0.037517034,0.0000040671057,0.000006110262,0.0000011727317,0.0002217416,0.000001630178,0.000014887682,0.029178571,0.00027653566,0.9323946],"study_design_scores_gemma":[0.00029392465,0.000039640538,0.21818627,0.000026939939,0.000025383039,0.0000026208609,0.00021879759,0.000067775065,0.00005372085,0.775118,0.0058630314,0.000103909515],"about_ca_topic_score_codex":0.000014966848,"about_ca_topic_score_gemma":0.000043367007,"teacher_disagreement_score":0.93229073,"about_ca_system_score_codex":0.000036077163,"about_ca_system_score_gemma":0.00006355959,"threshold_uncertainty_score":0.49048656},"labels":[],"label_agreement":null},{"id":"W4412721440","doi":"10.1080/13546783.2025.2536581","title":"Jumping to conclusions predicts truncated searches even in uncongenial contexts","year":2025,"lang":"en","type":"article","venue":"Thinking & Reasoning","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Psychology; Jumping; Cognitive psychology; Social psychology; Medicine","score_opus":0.08133237262939795,"score_gpt":0.41803366666766867,"score_spread":0.3367012940382707,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412721440","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98291236,0.0001711737,0.002309223,0.0013644086,0.001122082,0.00037809944,0.00001550756,0.0001585075,0.011568626],"genre_scores_gemma":[0.9927903,0.0000062125164,0.004339061,0.0008857599,0.000105411134,0.000022559523,0.0000062889594,0.000021413149,0.0018230211],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99619967,0.00032671753,0.0010257957,0.0008722543,0.0009875569,0.00058803597],"domain_scores_gemma":[0.99587595,0.0026258682,0.00021411091,0.0007715886,0.00030537407,0.00020709819],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0060908706,0.00025391148,0.0006027689,0.0010241505,0.00055028027,0.0006915208,0.0014455412,0.00018982803,0.00014041121],"category_scores_gemma":[0.008893559,0.00021775812,0.00015402038,0.0019121877,0.00010067393,0.00038341933,0.00097100314,0.00048815887,0.00032974826],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002025346,0.00010772943,0.06725571,0.000005556739,0.000029707791,0.000089501016,0.00886407,0.0032491947,0.0015240022,0.0051744096,0.0049159983,0.90858155],"study_design_scores_gemma":[0.0040922486,0.00036981003,0.21982013,0.0046541956,0.00010412947,0.000048612153,0.0064174435,0.02647874,0.0025832294,0.6863024,0.047658987,0.0014700738],"about_ca_topic_score_codex":0.0005037099,"about_ca_topic_score_gemma":0.0007501318,"teacher_disagreement_score":0.9071115,"about_ca_system_score_codex":0.0003333378,"about_ca_system_score_gemma":0.0003916478,"threshold_uncertainty_score":0.999455},"labels":[],"label_agreement":null},{"id":"W4412946543","doi":"10.1016/j.cognition.2025.106277","title":"When metrics matter: How reasoning in different metrics impacts judgments of uncertainty","year":2025,"lang":"en","type":"article","venue":"Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Anderson School of Management, University of California, Los Angeles","keywords":"Psychology; Cognitive psychology","score_opus":0.10502722961546704,"score_gpt":0.38219777149260753,"score_spread":0.2771705418771405,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412946543","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9893977,0.00015234925,0.0039174305,0.00064935925,0.00050104514,0.00018786459,0.000051448438,0.000017215636,0.0051256055],"genre_scores_gemma":[0.9986342,0.000033675402,0.0005719947,0.00025238885,0.00001869215,0.000009869008,0.000022744154,0.00000775642,0.0004486775],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9978821,0.00014710827,0.00066100527,0.00041204045,0.00066043634,0.00023730323],"domain_scores_gemma":[0.9972811,0.0015140536,0.00037321536,0.0003973391,0.00035710985,0.000077203294],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015534081,0.0001574885,0.00041905366,0.0019717007,0.000068133086,0.00028340844,0.00043544613,0.00012118132,0.00023285991],"category_scores_gemma":[0.005369562,0.000119842574,0.00013115696,0.0021422985,0.000052794676,0.0003089111,0.00017986877,0.00016468142,0.00010028769],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000110445195,0.00038789248,0.23971014,0.000021546195,0.000025080873,0.000010380471,0.00023748484,0.00015038581,0.0008382848,0.00017931603,0.015227592,0.7431015],"study_design_scores_gemma":[0.0034192905,0.00027920256,0.54173476,0.0010345863,0.00021834833,0.000007824233,0.0026446912,0.012067939,0.012802658,0.41896367,0.0061418223,0.00068519707],"about_ca_topic_score_codex":0.00003653962,"about_ca_topic_score_gemma":0.000060685154,"teacher_disagreement_score":0.74241626,"about_ca_system_score_codex":0.00017849891,"about_ca_system_score_gemma":0.000059952574,"threshold_uncertainty_score":0.64282554},"labels":[],"label_agreement":null},{"id":"W4412954780","doi":"10.3390/jrfm18080433","title":"Hot-Hand Belief and Loss Aversion in Individual Portfolio Decisions: Evidence from a Financial Experiment","year":2025,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Bentham-Moxon Trust; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Loss aversion; Portfolio; Economics; Psychology; Actuarial science; Financial economics; Finance","score_opus":0.06118379063070264,"score_gpt":0.3531415984111768,"score_spread":0.2919578077804742,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412954780","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98266155,0.004736992,0.0111250235,0.00016104878,0.00096807315,0.00017346888,0.000025963343,0.000003956336,0.00014395214],"genre_scores_gemma":[0.9878662,0.008238148,0.0034555816,0.00020954816,0.00010865683,0.00000462748,8.0396137e-7,0.0000054784036,0.00011094491],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9971368,0.00012570368,0.0012494712,0.00045094194,0.0008019757,0.0002351576],"domain_scores_gemma":[0.99755704,0.0012301975,0.000613777,0.00031190537,0.00016060556,0.00012649105],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030839383,0.00019495195,0.0005376997,0.0010177408,0.00026196116,0.0004506282,0.00057526183,0.00012732786,0.000054807897],"category_scores_gemma":[0.0028710624,0.00014912742,0.00013165452,0.0006398453,0.00014177058,0.0005248435,0.0006092958,0.00030996237,0.000012177369],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005172109,0.0001384854,0.067323774,0.0000026006128,0.000008126407,0.00026684845,0.0008978959,0.00006457803,0.000014799407,0.00038987276,0.004755009,0.9256208],"study_design_scores_gemma":[0.0018451491,0.0002766078,0.81004626,0.0009195064,0.00010583565,0.000015207914,0.0011414374,0.000078961,0.000107473286,0.13103333,0.05421467,0.00021557338],"about_ca_topic_score_codex":0.0001292532,"about_ca_topic_score_gemma":0.00014037997,"teacher_disagreement_score":0.9254052,"about_ca_system_score_codex":0.000083503815,"about_ca_system_score_gemma":0.00012545871,"threshold_uncertainty_score":0.60812396},"labels":[],"label_agreement":null},{"id":"W4413079922","doi":"10.3982/te5799","title":"Anticomonotonicity for preference axioms: The natural counterpart to comonotonicity","year":2025,"lang":"en","type":"article","venue":"Theoretical Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Axiom; Ambiguity; Mathematical economics; Expected utility hypothesis; Preference; Ambiguity aversion; Subjective expected utility; Variation (astronomy); Mathematics; Arbitrage; Risk aversion (psychology); Economics; Computer science; Financial economics; Statistics","score_opus":0.08505154140543643,"score_gpt":0.39912897660677527,"score_spread":0.31407743520133885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413079922","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95845544,0.000038949984,0.022455845,0.00797684,0.0016452349,0.0008907076,0.000112309266,0.000056303536,0.008368388],"genre_scores_gemma":[0.9931019,0.000020138577,0.0013863472,0.0048655183,0.00007461492,0.00009025571,0.0000048839097,0.000016915856,0.00043940102],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99724793,0.00014649243,0.0010649355,0.0008251963,0.00020056161,0.0005149046],"domain_scores_gemma":[0.99250406,0.005497755,0.0002014397,0.0013676133,0.00026109625,0.00016806148],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0038017728,0.000270742,0.00059712183,0.00019557372,0.00040061993,0.00077776134,0.0023235045,0.00014730531,0.00023865054],"category_scores_gemma":[0.003072321,0.00017485938,0.00030208993,0.0003316944,0.0008151658,0.00021361423,0.0005892888,0.00030253347,0.0004539365],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033001474,0.00007068396,0.0003472797,0.0000021217681,0.000018594244,4.2393768e-7,0.00014456296,0.0004590322,0.0000350983,0.886855,0.0022032512,0.10953392],"study_design_scores_gemma":[0.00042023824,0.000100728015,0.0014277218,0.000022786686,0.000033020533,0.000003478136,0.0002727831,0.07045988,0.00081087876,0.88250965,0.04369214,0.00024666815],"about_ca_topic_score_codex":0.000016930015,"about_ca_topic_score_gemma":0.00007733123,"teacher_disagreement_score":0.109287255,"about_ca_system_score_codex":0.00019876088,"about_ca_system_score_gemma":0.0002280124,"threshold_uncertainty_score":0.749997},"labels":[],"label_agreement":null},{"id":"W4413301883","doi":"10.1007/978-3-0348-0692-3_84-1","title":"Noncommutative Choquet Theory: A Survey","year":2025,"lang":"en","type":"book-chapter","venue":"Operator Theory","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Noncommutative geometry; Mathematics; Pure mathematics; Algebra over a field; Linguistics; Philosophy","score_opus":0.14204643408497225,"score_gpt":0.405006721419416,"score_spread":0.26296028733444377,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413301883","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0051463936,0.00089456217,0.0014723932,0.00011033582,0.0021251494,0.00045992105,0.0018689568,0.00009862275,0.98782367],"genre_scores_gemma":[0.04513502,0.000084294865,0.000369878,0.0012907829,0.00018365451,0.000021724993,0.00010930005,0.00009411303,0.9527112],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99451417,0.001385566,0.0013659134,0.0013398221,0.0009921121,0.00040241022],"domain_scores_gemma":[0.98352784,0.012538422,0.00059292774,0.0022481477,0.0008666628,0.00022602608],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.017613824,0.00068500306,0.0013092223,0.0006792309,0.00038826725,0.00090426294,0.0026191534,0.000677247,0.013223762],"category_scores_gemma":[0.00515621,0.000504447,0.0004994042,0.00021826442,0.0004956069,0.000289732,0.0008084144,0.0009258743,0.0070214868],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000267633,0.00003545098,0.00006381785,0.0000025680897,0.000078179546,0.0000442721,0.00025922392,0.000010039773,0.0000041680196,0.53233737,0.03229884,0.43459845],"study_design_scores_gemma":[0.00024037875,0.00007128214,0.00009598241,0.00013783216,0.000050071656,0.0000063909574,0.00016641307,0.000016550479,0.000026821233,0.7134684,0.28525254,0.00046734224],"about_ca_topic_score_codex":0.000023041046,"about_ca_topic_score_gemma":0.00013877344,"teacher_disagreement_score":0.43413112,"about_ca_system_score_codex":0.00020925692,"about_ca_system_score_gemma":0.00067575584,"threshold_uncertainty_score":0.9997407},"labels":[],"label_agreement":null},{"id":"W4413345108","doi":"10.2139/ssrn.5389511","title":"Mandates, Latent Conditions, and Error Avoidance in Performance Evaluations","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Psychology; Econometrics; Cognitive psychology; Computer science; Economics","score_opus":0.0899130050134964,"score_gpt":0.42704822944249277,"score_spread":0.33713522442899635,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413345108","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9911293,0.0038350166,0.0013736888,0.00150411,0.001055231,0.0002784484,0.00007744639,0.000021322356,0.000725457],"genre_scores_gemma":[0.98692036,0.008466297,0.00029829703,0.00010946595,0.00010946935,0.000029248646,0.000021823751,0.000012969001,0.004032066],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9956092,0.000291762,0.0012692254,0.0007014993,0.00079394673,0.0013343412],"domain_scores_gemma":[0.9977771,0.00048655752,0.0006631786,0.00060927565,0.00035985408,0.00010400066],"candidate_categories":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0107155815,0.0002894779,0.00054556556,0.00088106754,0.00037201354,0.0005610512,0.0010735187,0.00026620415,0.00014738376],"category_scores_gemma":[0.00083511457,0.00023997508,0.00017286792,0.00040151592,0.000109644905,0.00034582085,0.00055920455,0.0040255385,0.00011196933],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000082259496,0.00016319996,0.045640174,0.000015023814,0.000069547714,0.000009655672,0.00031873086,0.013619236,0.0000169823,0.008178561,0.0012806894,0.93060595],"study_design_scores_gemma":[0.0005956525,0.00010611722,0.022687946,0.00028728833,0.000053413172,0.00017100088,0.0006637612,0.011197027,0.0000115595085,0.96150357,0.002420988,0.00030166222],"about_ca_topic_score_codex":0.000061583094,"about_ca_topic_score_gemma":0.0018259457,"teacher_disagreement_score":0.95332503,"about_ca_system_score_codex":0.0012622245,"about_ca_system_score_gemma":0.0050012497,"threshold_uncertainty_score":0.99827224},"labels":[],"label_agreement":null},{"id":"W4413417374","doi":"10.1080/13504851.2025.2549513","title":"Do generalizations of expected utility explain more than the zero effect?","year":2025,"lang":"en","type":"article","venue":"Applied Economics Letters","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Zero (linguistics); Economics; Econometrics; Mathematical economics; Mathematics","score_opus":0.05143792888537318,"score_gpt":0.34328807341875806,"score_spread":0.29185014453338487,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413417374","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.984175,0.000029607925,0.0073293215,0.0030171408,0.00061992474,0.00037469447,0.00004112461,0.000038292055,0.0043748966],"genre_scores_gemma":[0.9965868,0.000010864737,0.0006119226,0.0025374298,0.000044785524,0.00006437399,0.000013337143,0.00001520783,0.00011526853],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99785054,0.00010296177,0.0009609825,0.0006344048,0.0001778574,0.00027327385],"domain_scores_gemma":[0.9964668,0.0016476987,0.00038545168,0.0013799157,0.000055933597,0.00006418561],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001456747,0.00021870116,0.00047466313,0.0002937458,0.00025731014,0.00029411097,0.0012627973,0.0001064443,0.00016377107],"category_scores_gemma":[0.0002517969,0.00015603018,0.00021601908,0.00047411857,0.0002866443,0.00014309397,0.00027280807,0.00016274887,0.00010544644],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003591256,0.00023500921,0.0621739,0.000017222006,0.0002066323,0.0000034737839,0.002700402,0.039691463,0.01415882,0.05343153,0.14561883,0.6814036],"study_design_scores_gemma":[0.0055628205,0.00018230068,0.21690321,0.00012030166,0.00043341206,0.000018940425,0.009340205,0.01975205,0.059648823,0.5632583,0.12220668,0.002572989],"about_ca_topic_score_codex":0.00004951045,"about_ca_topic_score_gemma":0.000044768625,"teacher_disagreement_score":0.6788306,"about_ca_system_score_codex":0.00008489154,"about_ca_system_score_gemma":0.000058417514,"threshold_uncertainty_score":0.6362726},"labels":[],"label_agreement":null},{"id":"W4413422965","doi":"10.1016/j.joep.2025.102845","title":"The impact of language on decision-making: Auction winners are less cursed in a foreign language","year":2025,"lang":"en","type":"article","venue":"Journal of Economic Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"University of Chicago; National Science Foundation","keywords":"Linguistics; Foreign language; Economics; Business","score_opus":0.07771835826783256,"score_gpt":0.495459282025436,"score_spread":0.4177409237576034,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413422965","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9893586,0.00031908858,0.00062750065,0.0006359107,0.0019153309,0.00010560353,0.000016362033,0.000005167854,0.0070164134],"genre_scores_gemma":[0.9991885,0.000048831524,0.00023969787,0.0002558726,0.00012071516,0.0000021704127,3.7595947e-7,0.00001086873,0.00013301232],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99728715,0.00021488608,0.0017039903,0.0003250922,0.00020203073,0.00026686743],"domain_scores_gemma":[0.99417347,0.003229072,0.0017038553,0.0007011611,0.00012555474,0.000066872584],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0037672273,0.00017229242,0.0006479985,0.0010979124,0.000083535655,0.00012393974,0.0011829885,0.00016392118,0.00017345251],"category_scores_gemma":[0.0017241898,0.00010424924,0.00046310594,0.00036794573,0.00015541547,0.00023613521,0.000073286785,0.00039026604,0.00007007381],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002020606,0.00024439528,0.03759966,0.0000014190083,0.000077586876,0.000089262045,0.0007464929,0.013558862,0.00027439484,0.0008034553,0.034184597,0.91039926],"study_design_scores_gemma":[0.0059451675,0.0015808764,0.48074374,0.0006811432,0.00005411051,0.00042579934,0.026739309,0.0036699092,0.00021103083,0.475303,0.0041764164,0.00046951536],"about_ca_topic_score_codex":0.00004351368,"about_ca_topic_score_gemma":0.000202166,"teacher_disagreement_score":0.90992975,"about_ca_system_score_codex":0.0003422055,"about_ca_system_score_gemma":0.00020720801,"threshold_uncertainty_score":0.42511606},"labels":[],"label_agreement":null},{"id":"W4413438112","doi":"10.1111/1911-3846.13076","title":"Motivating low performers with input‐based relative performance feedback","year":2025,"lang":"en","type":"article","venue":"Contemporary Accounting Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Universiteit van Amsterdam","keywords":"Psychology","score_opus":0.1845137332592009,"score_gpt":0.4340190936804423,"score_spread":0.24950536042124138,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413438112","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91950935,0.00012857151,0.0009626078,0.0020071135,0.00030105267,0.00047860964,0.000012665443,0.00008370506,0.076516315],"genre_scores_gemma":[0.99264723,0.0000047698472,0.0011994808,0.0003322733,0.00009283021,0.000039219136,0.000010932479,0.000030808482,0.005642432],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9944301,0.00044115545,0.0010684248,0.001089086,0.002210126,0.0007610547],"domain_scores_gemma":[0.9901954,0.0061333035,0.00037964171,0.0011736999,0.001973403,0.00014457897],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.014311206,0.00028789463,0.00051739585,0.0015778174,0.0013749239,0.001309557,0.0017183222,0.00019429953,0.0002937252],"category_scores_gemma":[0.007001628,0.00020702358,0.00013241508,0.0037646848,0.00062081526,0.0022919218,0.00052125036,0.001268766,0.00058700534],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006031103,0.0001651669,0.70657116,0.00005270272,0.000032483833,0.000022999715,0.00046942933,0.0008506104,0.00036863517,0.0003512771,0.02102009,0.26949233],"study_design_scores_gemma":[0.00971285,0.0020520336,0.50646394,0.007871725,0.00004156903,0.000028321712,0.017923774,0.23873647,0.011197313,0.036652356,0.16663903,0.0026805997],"about_ca_topic_score_codex":0.00008383882,"about_ca_topic_score_gemma":0.000015378959,"teacher_disagreement_score":0.26681173,"about_ca_system_score_codex":0.0002510229,"about_ca_system_score_gemma":0.0016423393,"threshold_uncertainty_score":0.99992514},"labels":[],"label_agreement":null},{"id":"W4413473869","doi":"10.1093/jcr/ucaf049","title":"The Confirmation Nudge: Prompts to Change or Confirm Initial Preferences Steer Consumer Choice","year":2025,"lang":"en","type":"article","venue":"Journal of Consumer Research","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Psychology; Consumer choice; Advertising; Economics; Social psychology; Microeconomics; Business","score_opus":0.621304329678497,"score_gpt":0.6006559536574757,"score_spread":0.02064837602102132,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413473869","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9766342,0.001424178,0.00016148419,0.013699156,0.0019272197,0.0008249198,0.00002588984,0.000013142118,0.005289783],"genre_scores_gemma":[0.9944555,0.00030387822,0.00021221493,0.00081354927,0.00020604864,0.000036516314,8.8583505e-7,0.000012534003,0.003958886],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99360573,0.0011351446,0.0016399672,0.00037049397,0.0026845983,0.0005640913],"domain_scores_gemma":[0.9807115,0.013153251,0.0005718457,0.00069398497,0.0045629544,0.0003064543],"candidate_categories":["metaresearch","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.015106513,0.0001853698,0.000513449,0.0011233576,0.00074583094,0.0017723173,0.0020710328,0.00015192552,0.00074423966],"category_scores_gemma":[0.016352264,0.0000964505,0.00016245942,0.0015288487,0.0005350585,0.0006788984,0.00038118268,0.00091879984,0.0007672588],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011002852,0.00012626412,0.0071573053,0.000008080113,0.00006688689,0.000035997295,0.00065442605,0.0000038650146,0.0002282744,0.0005352229,0.11739362,0.8726898],"study_design_scores_gemma":[0.0009795744,0.00040675804,0.017279997,0.00017274826,0.000030995805,0.000056806133,0.0017404194,0.00011434101,0.000992431,0.0138591295,0.9642086,0.00015821963],"about_ca_topic_score_codex":0.000101196965,"about_ca_topic_score_gemma":0.0005044058,"teacher_disagreement_score":0.87253153,"about_ca_system_score_codex":0.00012652615,"about_ca_system_score_gemma":0.0012509628,"threshold_uncertainty_score":0.99926394},"labels":[],"label_agreement":null},{"id":"W4413812304","doi":"10.2139/ssrn.5413975","title":"Modulating a neural marker of outcome valence as a function of intention: Feedback-related negativity (FRN) reduction when wins are treated as losses","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Negativity effect; Valence (chemistry); Psychology; Reduction (mathematics); Outcome (game theory); Function (biology); Control theory (sociology); Social psychology; Computer science; Physics; Mathematics; Artificial intelligence; Biology; Quantum mechanics; Mathematical economics; Control (management)","score_opus":0.07017870171894461,"score_gpt":0.36494849407638,"score_spread":0.2947697923574354,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413812304","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9919395,0.00062365684,0.0033803345,0.0005993723,0.0021407222,0.0003714973,0.000048588787,0.00004897087,0.0008473535],"genre_scores_gemma":[0.99356204,0.00037137378,0.00020934045,0.00002166045,0.000110120476,0.00000951893,0.000017014887,0.000026485639,0.0056724385],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9931462,0.0006804687,0.002868527,0.000929396,0.0012698869,0.0011055272],"domain_scores_gemma":[0.992567,0.0005151193,0.004385242,0.00091006403,0.0014997954,0.00012274971],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.006495802,0.00047210115,0.0012213427,0.0010437308,0.00027799443,0.00029420457,0.0011860458,0.00066245283,0.0003984638],"category_scores_gemma":[0.0030262358,0.00039135697,0.0009085936,0.00084805075,0.00022840046,0.0006481787,0.0005875072,0.004466277,0.00004448737],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014092863,0.00051867997,0.124999456,0.00007039363,0.0006054859,0.000013164666,0.0005404017,0.013655728,0.00094195065,0.0023065945,0.0002203319,0.8547185],"study_design_scores_gemma":[0.00092706544,0.00064684666,0.037478868,0.0008330029,0.00040923248,0.00053263264,0.0040030344,0.0058860076,0.00022721934,0.9485596,0.000067779554,0.00042871342],"about_ca_topic_score_codex":0.00087115687,"about_ca_topic_score_gemma":0.000490367,"teacher_disagreement_score":0.946253,"about_ca_system_score_codex":0.001155296,"about_ca_system_score_gemma":0.0019295003,"threshold_uncertainty_score":0.99985385},"labels":[],"label_agreement":null},{"id":"W4414275592","doi":"10.1287/mnsc.2024.04870","title":"Measuring Probabilistic Risk Attitudes","year":2025,"lang":"en","type":"article","venue":"Management Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Weighting; Attractiveness; Probabilistic logic; Heuristic; Independence (probability theory); Agency (philosophy); Function (biology); Prospect theory","score_opus":0.15957894677218382,"score_gpt":0.40584462154633544,"score_spread":0.24626567477415162,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414275592","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8564857,0.000037021895,0.010299302,0.00035054807,0.0011495968,0.00027434464,0.0000028132047,0.000079187615,0.13132145],"genre_scores_gemma":[0.99043417,0.000012582703,0.0042059775,0.0001909402,0.00001509815,0.000017025195,1.566739e-7,0.0000036150768,0.0051204367],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9968019,0.000059126793,0.00051418494,0.0009172322,0.0013453111,0.00036221262],"domain_scores_gemma":[0.9980839,0.00035521254,0.00017234912,0.0011145842,0.00018443348,0.00008950867],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0077065197,0.00012598984,0.00018809995,0.00086485676,0.0007017278,0.0011935009,0.00249595,0.000025092972,0.00014086529],"category_scores_gemma":[0.0022828386,0.000094047726,0.00007793549,0.0028032353,0.00052186404,0.0005574744,0.0010210436,0.00010682825,0.00088893936],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007944725,0.0000861661,0.059576165,0.0000065479558,0.0000060636567,0.00000864233,0.000052719875,0.002650215,0.00006405838,0.02270347,0.0024095287,0.9124285],"study_design_scores_gemma":[0.00030001835,0.00003308541,0.4227336,0.000089642876,0.000039637704,0.0000014479514,0.00040677292,0.0071445056,0.00025354137,0.52803826,0.04068507,0.00027441987],"about_ca_topic_score_codex":0.000024035024,"about_ca_topic_score_gemma":0.000033109685,"teacher_disagreement_score":0.9121541,"about_ca_system_score_codex":0.00015960235,"about_ca_system_score_gemma":0.000065369335,"threshold_uncertainty_score":0.99988896},"labels":[],"label_agreement":null},{"id":"W4414482117","doi":"10.1016/j.jmateco.2025.103181","title":"Prudence and higher-order risk attitudes in the rank-dependent utility model","year":2025,"lang":"en","type":"article","venue":"Journal of Mathematical Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Actua; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Weighting; Prudence; Generality; Stochastic dominance; Consistency (knowledge bases); Differentiable function; Expected utility hypothesis; Probability measure; Function (biology); Monotonic function","score_opus":0.12133564214320712,"score_gpt":0.4065820069671549,"score_spread":0.2852463648239478,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414482117","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97755927,0.00014825544,0.015570766,0.00221766,0.00024528027,0.00012146109,0.000009242923,0.000004000521,0.004124073],"genre_scores_gemma":[0.99119383,0.000184041,0.007914367,0.00040897567,0.000034767596,0.0000026382636,8.736802e-8,0.000005689732,0.00025561568],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99749774,0.00014878582,0.0015953918,0.00026131663,0.0003120826,0.00018466932],"domain_scores_gemma":[0.99525356,0.0033122408,0.0006788183,0.00049701746,0.00017772305,0.00008066409],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0086999815,0.00014373094,0.0005542457,0.00023928143,0.00009956686,0.00044719997,0.0010520011,0.00010786535,0.000158879],"category_scores_gemma":[0.0024969624,0.00008341336,0.00015355126,0.00019348339,0.000172903,0.0004027802,0.00018073867,0.00042725474,0.000044627912],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048716646,0.0018130449,0.062459644,0.000064179134,0.0001180804,0.000051470382,0.002121061,0.0272835,0.000029669043,0.11680331,0.005171866,0.783597],"study_design_scores_gemma":[0.00049978757,0.000040890915,0.015834784,0.000055834935,0.000035172066,0.000039813778,0.00033352114,0.051351923,0.000011980387,0.9309202,0.0007834941,0.00009262923],"about_ca_topic_score_codex":0.0000047130384,"about_ca_topic_score_gemma":0.000032637967,"teacher_disagreement_score":0.81411684,"about_ca_system_score_codex":0.0000729406,"about_ca_system_score_gemma":0.000164884,"threshold_uncertainty_score":0.43123597},"labels":[],"label_agreement":null},{"id":"W4414636012","doi":"10.1007/978-3-031-96041-3_13","title":"Preferences, Habits, and Free Choice","year":2025,"lang":"en","type":"book-chapter","venue":"Synthese Library/Synthese library","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Skepticism; Appeal; Ideal (ethics); Reflexivity; Deliberation; Compatibilism; Power (physics); Free will","score_opus":0.07528863137639227,"score_gpt":0.30673187520705836,"score_spread":0.23144324383066608,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414636012","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011103368,0.0060368916,0.000029809056,0.008354452,0.0018973934,0.0010484093,0.0032313657,0.0010858374,0.9672125],"genre_scores_gemma":[0.015136463,0.0024519367,0.0064770947,0.0027196575,0.0012244199,0.00008476703,0.0002075607,0.00046300318,0.9712351],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.990329,0.00042281742,0.0028635878,0.0033560805,0.0019687596,0.0010597561],"domain_scores_gemma":[0.9752034,0.017084075,0.0014424992,0.0052985484,0.00009793795,0.000873555],"candidate_categories":["metaepi_narrow","scholarly_communication","open_science","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","insufficient_payload"],"category_scores_codex":[0.0010677314,0.00169488,0.0025695614,0.0022710497,0.00048985163,0.003726017,0.007351721,0.0017833281,0.024909109],"category_scores_gemma":[0.003929755,0.0013466895,0.00092817267,0.0005858196,0.000951733,0.00786237,0.0061310045,0.0017283328,0.0023520393],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016654907,0.00008892248,0.0018435466,0.00006724199,0.0001302003,0.00009730557,0.000109399334,0.0000036066644,0.0000073493434,0.067907125,0.38265705,0.54692173],"study_design_scores_gemma":[0.00022005693,0.00007300112,0.00034616012,0.0009770003,0.00009301455,0.000021554086,0.00003743318,0.000089230794,0.00018580515,0.45457125,0.5425264,0.0008590839],"about_ca_topic_score_codex":0.000022108883,"about_ca_topic_score_gemma":0.000016513037,"teacher_disagreement_score":0.54606265,"about_ca_system_score_codex":0.000044479148,"about_ca_system_score_gemma":0.0009863789,"threshold_uncertainty_score":0.9995798},"labels":[],"label_agreement":null},{"id":"W4414871809","doi":"10.1016/j.mathsocsci.2025.102469","title":"Note on intertemporal preference with loss aversion","year":2025,"lang":"en","type":"article","venue":"Mathematical Social Sciences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Ministry of Science and ICT, South Korea; National Research Foundation of Korea","keywords":"Equivalence (formal languages); Monotonic function; Preference; Monotone polygon; Extension (predicate logic); Loss aversion; Intertemporal choice; Time preference","score_opus":0.2307279006708502,"score_gpt":0.45048028913524263,"score_spread":0.21975238846439243,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414871809","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8468238,0.0000039195465,0.011435938,0.004148853,0.00023023027,0.00014475682,0.0000061273026,0.000050277362,0.1371561],"genre_scores_gemma":[0.9952786,6.9620967e-7,0.0022489629,0.0005428239,0.000039525657,0.0000071145387,4.152023e-7,0.0000037335758,0.0018781348],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99740225,0.000102224745,0.00048160387,0.00055325025,0.0011590726,0.0003015909],"domain_scores_gemma":[0.99797976,0.0014074879,0.00016974327,0.00025683336,0.0001167939,0.000069370864],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0022792632,0.00015142978,0.0003333314,0.00021257317,0.00069477386,0.0006135226,0.0011891825,0.0000952447,0.0006006139],"category_scores_gemma":[0.001115146,0.000084014624,0.000105990504,0.0011110897,0.00087032054,0.00028055185,0.00021724933,0.0001576531,0.0009453761],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001738552,0.0005183491,0.0055022174,0.000013831241,0.000010941905,0.000020418849,0.0020163516,0.000074233234,0.0000770133,0.27231538,0.018315151,0.70096225],"study_design_scores_gemma":[0.0002393746,0.00024631867,0.0022616338,0.00011849903,0.000011607626,0.0000028092013,0.0009705904,0.002397636,0.00024805407,0.98725414,0.0060669505,0.00018239995],"about_ca_topic_score_codex":0.000016677759,"about_ca_topic_score_gemma":0.000030476702,"teacher_disagreement_score":0.71493876,"about_ca_system_score_codex":0.00007417843,"about_ca_system_score_gemma":0.00014083432,"threshold_uncertainty_score":0.9998325},"labels":[],"label_agreement":null},{"id":"W4414897807","doi":"10.31234/osf.io/yagn5_v2","title":"Demand Avoidance in Value-Based Choice Under Risk: A Behavioral and Pupillometric Examination","year":2025,"lang":"en","type":"article","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Preference; Cognition; Context (archaeology); Demand characteristics; Control (management); Self-control; Value (mathematics); Behavioral economics; Empirical research","score_opus":0.09298270197935536,"score_gpt":0.41719464944656065,"score_spread":0.3242119474672053,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414897807","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9775409,0.00020810253,0.01834954,0.00028553302,0.0003120515,0.00018588497,0.00000834495,0.000036764457,0.003072861],"genre_scores_gemma":[0.9957336,0.000014917538,0.0020886378,0.000243586,0.000013345174,0.00001413719,0.0000018574805,0.000007185722,0.0018826865],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9976783,0.00027419985,0.00067637424,0.0006338176,0.00050094,0.00023636423],"domain_scores_gemma":[0.99627095,0.0028266124,0.00020098548,0.0004739463,0.00014907598,0.000078422236],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0037018592,0.00015581856,0.0003064794,0.0017556845,0.00015311269,0.000425518,0.00042547393,0.00013048507,0.00016364396],"category_scores_gemma":[0.0021519735,0.00012200545,0.00006887563,0.0027039594,0.00009768366,0.00037628142,0.00012587721,0.00020526735,0.00007636643],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014058095,0.00018051949,0.38747957,0.0000018354202,0.0000018698764,0.0000042079446,0.00004433783,0.0015406744,0.000068534115,0.00068903185,0.00039141203,0.6095839],"study_design_scores_gemma":[0.00089920155,0.00007047255,0.945268,0.000029306522,0.00002012225,0.000001447502,0.000269643,0.016311135,0.00025753613,0.035295356,0.0014068778,0.00017091438],"about_ca_topic_score_codex":0.00053437287,"about_ca_topic_score_gemma":0.000847491,"teacher_disagreement_score":0.609413,"about_ca_system_score_codex":0.00012395535,"about_ca_system_score_gemma":0.000092600654,"threshold_uncertainty_score":0.49752378},"labels":[],"label_agreement":null},{"id":"W4414979665","doi":"10.1017/esa.2025.10018","title":"Choosing portfolios of rival risky options: evidence that most people violate the no safety schools theorem","year":2025,"lang":"en","type":"article","venue":"Journal of the Economic Science Association","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Dynamic inconsistency","score_opus":0.056872071037368244,"score_gpt":0.38142131235120436,"score_spread":0.3245492413138361,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414979665","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9873513,0.00017792065,0.00071726664,0.005413329,0.004703659,0.00019345027,0.000014712953,0.0000066354346,0.0014217005],"genre_scores_gemma":[0.99804616,0.00026784392,0.00047726248,0.0002779061,0.00016049074,0.0000018333413,1.2687505e-7,0.00000557418,0.0007628099],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99629414,0.0003543647,0.0016033077,0.00033182406,0.001112019,0.0003043276],"domain_scores_gemma":[0.98959863,0.0034132423,0.0051106894,0.00079480425,0.0009994869,0.00008315294],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.028604204,0.00014308232,0.00044900476,0.00045731568,0.0008535175,0.00088623405,0.003308783,0.00009441572,0.00011424299],"category_scores_gemma":[0.022134364,0.0000783848,0.00037065073,0.0012393886,0.00023597381,0.0023027211,0.0004253391,0.0004380402,0.00012958107],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002059846,0.00007454354,0.7904458,0.0000038995586,0.00007853652,0.0000010291773,0.00095440156,0.03554908,0.0036454333,0.0037973695,0.016404128,0.14883979],"study_design_scores_gemma":[0.00060554757,0.000085900305,0.7959264,0.00049208594,0.000150599,0.000033331835,0.0024748784,0.013923565,0.0025942426,0.18060139,0.002887325,0.00022472898],"about_ca_topic_score_codex":0.00008308864,"about_ca_topic_score_gemma":0.00006196243,"teacher_disagreement_score":0.17680402,"about_ca_system_score_codex":0.0021988591,"about_ca_system_score_gemma":0.0017475995,"threshold_uncertainty_score":0.9913704},"labels":[],"label_agreement":null},{"id":"W4416332095","doi":"10.1287/mnsc.2023.01558","title":"Nonadditivity of Subjective Expectations over Different Time Intervals","year":2025,"lang":"en","type":"article","venue":"Management Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"German; Stock price; Perception; Stock (firearms); Quarter (Canadian coin); Additive function; Interval (graph theory); Degree (music)","score_opus":0.051311032008727706,"score_gpt":0.39820018670743484,"score_spread":0.3468891546987071,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416332095","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9184829,0.000009908131,0.0071490384,0.00021108153,0.00049512554,0.00019546741,0.000018214276,0.000024141365,0.073414095],"genre_scores_gemma":[0.9924416,0.0000021073718,0.0006994386,0.0001103249,0.00000790917,0.000015482823,8.7387866e-7,0.0000028266707,0.006719439],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.997658,0.000061404186,0.0005016416,0.00060532236,0.0009463693,0.00022723997],"domain_scores_gemma":[0.99824846,0.0005960613,0.00020862001,0.000707254,0.00018111819,0.000058486516],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017363583,0.000113038346,0.00024308701,0.00090446655,0.00023255333,0.00029600484,0.0013820556,0.000023090433,0.00070262386],"category_scores_gemma":[0.000684676,0.000083525905,0.00010766566,0.0018714146,0.0005039683,0.00048573414,0.0007702012,0.00006148206,0.00033972264],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000039478065,0.00049953704,0.023968317,0.000008613203,0.000028130371,0.000009634201,0.0007968511,0.00021988814,0.0029604936,0.02525665,0.013450506,0.9327619],"study_design_scores_gemma":[0.0004548619,0.00008707145,0.76322985,0.00011090653,0.000037990852,7.329598e-7,0.0024168906,0.008547198,0.0058987667,0.21438187,0.004573483,0.000260366],"about_ca_topic_score_codex":0.000015703912,"about_ca_topic_score_gemma":0.00002069241,"teacher_disagreement_score":0.93250155,"about_ca_system_score_codex":0.00012334589,"about_ca_system_score_gemma":0.000041103074,"threshold_uncertainty_score":0.7693239},"labels":[],"label_agreement":null},{"id":"W4416527734","doi":"10.1017/9781009322737.008","title":"Deviating from Plans","year":2025,"lang":"","type":"book-chapter","venue":"Cambridge University Press eBooks","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"","score_opus":0.0892036669322929,"score_gpt":0.2887299620391261,"score_spread":0.1995262951068332,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416527734","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021182358,0.00020849693,0.0052932194,0.000055169505,0.0027440188,0.000636138,0.0065254914,0.00016472723,0.9631904],"genre_scores_gemma":[0.04275975,0.00021084765,0.0011544971,0.0002486533,0.00030288153,8.3659245e-7,0.000114086746,0.00006281317,0.95514566],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9935687,0.0002364234,0.0015131469,0.0025847843,0.0013043213,0.0007926248],"domain_scores_gemma":[0.99137425,0.003255494,0.0015129973,0.002528614,0.000751648,0.0005770033],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0009585289,0.0011029238,0.0017191941,0.0009897051,0.001195818,0.0009117897,0.004027792,0.0013046686,0.00016420083],"category_scores_gemma":[0.00044731042,0.0012344562,0.0010824259,0.0000649444,0.00071147026,0.00045002095,0.002860906,0.0014393271,0.0005366572],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004222716,0.000052976175,0.0001400883,0.000024304672,0.00028566955,0.0010307918,0.00016834187,0.000041187748,0.000058450547,0.51379806,0.0362474,0.44773048],"study_design_scores_gemma":[0.0010999099,0.00009451873,0.00011237068,0.0009806991,0.00071629457,0.000011389638,0.000525879,0.0015327313,0.00024678637,0.0008048375,0.9926061,0.0012684526],"about_ca_topic_score_codex":0.0015742369,"about_ca_topic_score_gemma":0.00004778852,"teacher_disagreement_score":0.95635873,"about_ca_system_score_codex":0.0005841107,"about_ca_system_score_gemma":0.00067782594,"threshold_uncertainty_score":0.99999183},"labels":[],"label_agreement":null},{"id":"W4416995107","doi":"10.1037/pha0000809","title":"Delay discounting violations vary by adolescent sociodemographics: Excluding nonsystematic data may bias conclusions.","year":2025,"lang":"en","type":"article","venue":"Experimental and Clinical Psychopharmacology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health; University of Toronto","funders":"National Institutes of Health","keywords":"Discounting; Receipt; Delay discounting; Addiction; Cognition; Valuation (finance); Psychological science; Cognitive bias","score_opus":0.2939852141856397,"score_gpt":0.5620577036864968,"score_spread":0.26807248950085705,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416995107","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98350036,0.0026623274,0.0034795506,0.0027622844,0.005076464,0.00048178833,0.00013772472,0.000062207764,0.0018373061],"genre_scores_gemma":[0.9939584,0.00014655595,0.00075761543,0.004314431,0.00020426251,0.000028401502,0.000040435043,0.000015441587,0.0005344155],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9950758,0.00071421877,0.0021686745,0.0012240127,0.00042380844,0.00039343932],"domain_scores_gemma":[0.9940265,0.0041999486,0.000540922,0.0008901825,0.000092278926,0.00025017958],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004877771,0.0002667013,0.0007280401,0.00024285537,0.00067458523,0.00027536173,0.0013916466,0.00025073285,0.00071212125],"category_scores_gemma":[0.0008077577,0.00020423894,0.00022610507,0.0005032153,0.0005496989,0.00041025173,0.0014351171,0.0004965382,0.00019487142],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046991507,0.003173264,0.21902016,0.00002988024,0.00027263266,0.00003521071,0.00031305468,0.000013482527,0.006916444,0.00095419097,0.5738138,0.19498795],"study_design_scores_gemma":[0.037672147,0.0023113384,0.063979395,0.0021882828,0.0018088344,0.00022654263,0.0365234,0.13785554,0.0032150268,0.10690377,0.6024302,0.004885509],"about_ca_topic_score_codex":0.000017701945,"about_ca_topic_score_gemma":0.000007896591,"teacher_disagreement_score":0.19010244,"about_ca_system_score_codex":0.00006034161,"about_ca_system_score_gemma":0.00009796981,"threshold_uncertainty_score":0.83286226},"labels":[],"label_agreement":null},{"id":"W49927985","doi":"10.1016/b978-0-12-800283-4.00003-4","title":"Probability Matching, Fast and Slow","year":2014,"lang":"en","type":"book-chapter","venue":"˜The œPsychology of learning and motivation/˜The œpsychology of learning and motivation","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Matching (statistics); Computer science; Mathematics; Statistics","score_opus":0.09388659606299772,"score_gpt":0.36238487309312317,"score_spread":0.26849827703012547,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W49927985","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95361394,0.0007690708,0.01076707,0.0029681432,0.00062829704,0.0006556107,0.0000154096,0.00010187499,0.030480575],"genre_scores_gemma":[0.9401065,0.0005295164,0.000806276,0.00043783663,0.00016106728,0.000021010857,0.00004441688,0.0000800149,0.05781336],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9941692,0.0011005541,0.0019661412,0.0015830543,0.0007174677,0.0004636021],"domain_scores_gemma":[0.9901154,0.0052020303,0.0029686484,0.0009237654,0.0006359382,0.00015422172],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0072549568,0.0006496171,0.001277826,0.0007030799,0.0009885159,0.00015556472,0.0007237666,0.0010167303,0.00017795723],"category_scores_gemma":[0.0022217853,0.00045101542,0.00024557265,0.00024922038,0.002619613,0.00018203745,0.00031654708,0.0022281948,0.000036164914],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004665824,0.00014812053,0.21643552,0.0000747192,0.00022152749,0.000004206237,0.003193212,0.0010408422,0.0010083416,0.0035149623,0.0035373901,0.77035457],"study_design_scores_gemma":[0.0026331216,0.0016664003,0.43987763,0.00053427456,0.00028741473,0.0003054254,0.0013369726,0.00052423344,0.00001666981,0.17628339,0.37553352,0.0010009266],"about_ca_topic_score_codex":0.000037320682,"about_ca_topic_score_gemma":0.000031238782,"teacher_disagreement_score":0.7693536,"about_ca_system_score_codex":0.000024807072,"about_ca_system_score_gemma":0.000059643688,"threshold_uncertainty_score":0.9997942},"labels":[],"label_agreement":null},{"id":"W564510426","doi":"","title":"Data Dispersion in Economics (I) - Possibility of Restrictions","year":2012,"lang":"en","type":"article","venue":"Review of Economics and Finance","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Economics; Mathematical economics; Dispersion (optics); Equity (law); Equity premium puzzle; Econometrics; Risk aversion (psychology); Expected utility hypothesis; Utility theory; Prospect theory; Scale (ratio); Microeconomics; Neoclassical economics; Risk premium; Physics; Political science; Law; Quantum mechanics","score_opus":0.2253657623444704,"score_gpt":0.411302887468271,"score_spread":0.1859371251238006,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W564510426","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96359473,0.03446763,0.00002409774,0.00026765128,0.00027266148,0.0001549499,0.000346397,0.0000017954738,0.00087006204],"genre_scores_gemma":[0.6302113,0.3685245,0.0011310481,0.000066338034,0.0000230837,0.0000021387614,0.000010514488,0.000004548847,0.000026539858],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980121,0.000050480063,0.0013279361,0.00039474663,0.00004868725,0.00016599524],"domain_scores_gemma":[0.9974168,0.0004279281,0.0007360342,0.001314436,0.00005560455,0.00004921753],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034523532,0.00010772776,0.0006173657,0.000121029654,0.000035971087,0.000023357927,0.0006967976,0.00006122854,0.000032278243],"category_scores_gemma":[0.0006798143,0.000091071146,0.000088809276,0.00018758226,0.00011205048,0.00071024033,0.00037266573,0.000082659746,0.000018842746],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013769747,0.00015866247,0.057508714,0.000106691434,0.000003970167,1.6098267e-7,0.000038956437,0.00009699191,0.00000251673,0.009182988,0.0007268936,0.93215966],"study_design_scores_gemma":[0.0005961958,0.00011625011,0.25355372,0.0019694786,0.000053296946,0.000019359728,0.00014647344,0.0123672625,0.000060773385,0.05759346,0.6730534,0.00047035393],"about_ca_topic_score_codex":0.00006593781,"about_ca_topic_score_gemma":0.00010549099,"teacher_disagreement_score":0.9316893,"about_ca_system_score_codex":0.000040701736,"about_ca_system_score_gemma":0.00007429275,"threshold_uncertainty_score":0.37137735},"labels":[],"label_agreement":null},{"id":"W621487820","doi":"10.1016/j.cogpsych.2015.05.001","title":"What makes us think? A three-stage dual-process model of analytic engagement","year":2015,"lang":"en","type":"article","venue":"Cognitive Psychology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":483,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cued speech; Decoupling (probability); Psychology; Cognitive psychology; Social psychology; Computer science","score_opus":0.5084308370774361,"score_gpt":0.5253165416008257,"score_spread":0.016885704523389666,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W621487820","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9627094,0.00028707134,0.021891288,0.00051035464,0.0013253312,0.00025413893,0.00007977142,0.000038072816,0.012904562],"genre_scores_gemma":[0.9965498,0.000042934767,0.00070697116,0.0015859178,0.000057467892,0.000019259494,0.000009238297,0.000020746744,0.0010076733],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99682176,0.00024961357,0.000925327,0.00087650446,0.000766675,0.00036010423],"domain_scores_gemma":[0.99634933,0.0009707721,0.0005235612,0.00069270324,0.0012396724,0.00022393811],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0037157112,0.00023475764,0.0005851687,0.00048276095,0.00009617887,0.00022745143,0.00070546026,0.00017794814,0.00048305758],"category_scores_gemma":[0.002619438,0.00018487191,0.00017423143,0.00057315803,0.00039804922,0.00067949435,0.00019819934,0.00028955835,0.0008484448],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010602779,0.0011668535,0.02874513,0.000012479102,0.0001370441,0.00015059976,0.009650537,0.0054255207,0.0004049279,0.0008983339,0.007795307,0.944553],"study_design_scores_gemma":[0.004133555,0.0009883128,0.012658904,0.0001707108,0.00018634838,0.00004265042,0.028577613,0.06601157,0.00069551467,0.88353115,0.002237531,0.0007661076],"about_ca_topic_score_codex":0.000009288997,"about_ca_topic_score_gemma":0.00008606641,"teacher_disagreement_score":0.94378686,"about_ca_system_score_codex":0.00003669123,"about_ca_system_score_gemma":0.00015491647,"threshold_uncertainty_score":0.9999295},"labels":[],"label_agreement":null},{"id":"W644796199","doi":"10.1177/02601079x01001200202","title":"Choosing from a Moral Point of View","year":2001,"lang":"en","type":"article","venue":"Journal of Interdisciplinary Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Morality; Sketch; Epistemology; Rationality; Sociology; Politics; Perspective (graphical); Point (geometry); Democracy; Law and economics; Law; Philosophy; Computer science; Political science; Mathematics","score_opus":0.13430021566020212,"score_gpt":0.40903632348821606,"score_spread":0.27473610782801394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W644796199","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99138236,0.00032913126,0.0016743494,0.0013635063,0.0019169714,0.00006517485,0.000034440065,0.0000065432687,0.0032275175],"genre_scores_gemma":[0.9947729,0.00018956496,0.004345868,0.00013489439,0.00039488226,6.9437533e-7,0.0000017385248,0.000020522633,0.00013895184],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9963326,0.00009554518,0.002736934,0.00031928986,0.00028666967,0.00022895903],"domain_scores_gemma":[0.9956044,0.00082236144,0.0024047145,0.00059853063,0.00037041126,0.00019957498],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023910156,0.00020224783,0.00092264847,0.0005278525,0.0001029215,0.00024257664,0.0012967365,0.000113647206,0.00080633344],"category_scores_gemma":[0.00033916126,0.00015315769,0.00062758394,0.00022507859,0.00012858928,0.0010819536,0.0007326708,0.0003087189,0.0001881919],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008491324,0.00040731073,0.041661985,0.0000037607845,0.0001091247,0.00016839975,0.00202666,0.004566406,0.00052246975,0.0002945167,0.006755987,0.9426342],"study_design_scores_gemma":[0.0017105921,0.0011001056,0.032681488,0.00045056513,0.00010399076,0.0012368762,0.007547521,0.008254348,0.0009384708,0.930282,0.015172586,0.00052146683],"about_ca_topic_score_codex":0.000013083782,"about_ca_topic_score_gemma":0.000054914894,"teacher_disagreement_score":0.9421128,"about_ca_system_score_codex":0.00020033019,"about_ca_system_score_gemma":0.00014426379,"threshold_uncertainty_score":0.8828786},"labels":[],"label_agreement":null},{"id":"W67782583","doi":"10.17705/1jais.00350","title":"Confirmation Biases in the Financial Analysis of IT Investments","year":2014,"lang":"en","type":"article","venue":"Journal of the Association for Information Systems","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Confirmation bias; Dual (grammatical number); Confirmatory factor analysis; Finance; Investment (military); Actuarial science; Economics; Psychology; Business; Marketing; Social psychology; Political science","score_opus":0.11960179813248308,"score_gpt":0.3830250843241907,"score_spread":0.26342328619170763,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W67782583","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9902278,0.000012626128,0.0042644553,0.0010913616,0.0015657223,0.00029883944,0.000055989512,0.0000027413946,0.0024804582],"genre_scores_gemma":[0.9992578,0.0000026722878,0.000054788234,0.0005119979,0.000065118205,0.0000059210192,0.000006869394,0.0000016155926,0.0000932257],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9960565,0.0004025393,0.002100393,0.00004957928,0.0012865883,0.00010441738],"domain_scores_gemma":[0.9896851,0.0029721442,0.0058623576,0.00024819138,0.001206974,0.000025232257],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.016097646,0.00006720712,0.00037177105,0.00075210177,0.000109583605,0.0003526576,0.0006949601,0.00008577894,0.0000055854775],"category_scores_gemma":[0.018442877,0.000034627206,0.0003524611,0.0013148956,0.00001506374,0.0012257358,0.000025870637,0.00009991078,0.00001689357],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018744425,0.00021719701,0.29053026,0.000029732233,0.0004745455,1.9124838e-7,0.024645733,0.48436716,0.000052383264,0.018414864,0.08526537,0.09581512],"study_design_scores_gemma":[0.0018112297,0.00018005853,0.47278127,0.00013362734,0.00058888743,0.000008399154,0.00870638,0.17908733,0.0000875631,0.009050318,0.3273859,0.00017905328],"about_ca_topic_score_codex":0.000026787742,"about_ca_topic_score_gemma":0.000042762244,"teacher_disagreement_score":0.30527985,"about_ca_system_score_codex":0.00021457762,"about_ca_system_score_gemma":0.00008281847,"threshold_uncertainty_score":0.9898252},"labels":[],"label_agreement":null},{"id":"W6924731324","doi":"10.15468/dl.yp8rms","title":"Occurrence Download","year":2023,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Download; Matching (statistics); Range (aeronautics); Set (abstract data type); Data set","score_opus":0.09468375118358023,"score_gpt":0.3351634873542873,"score_spread":0.24047973617070706,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6924731324","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005772582,0.000006755836,0.0000073189576,0.00024139369,0.0027063165,0.00025604022,0.99073887,0.00015279565,0.000117924814],"genre_scores_gemma":[0.000026168656,0.00003449174,0.0000023116386,0.00041842274,0.0000030734182,0.0000031131271,0.9995114,2.5029957e-8,9.60475e-7],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99589914,0.00013420786,0.0012298668,0.0005488512,0.0017828393,0.00040508734],"domain_scores_gemma":[0.99641764,0.00032000802,0.00086141523,0.0014037548,0.00072679785,0.00027036679],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002274838,0.0003608449,0.00055922306,0.00037506234,0.00044426168,0.0010722,0.0022131251,0.0005269324,0.0021207363],"category_scores_gemma":[0.003062139,0.00031282878,0.00036829378,0.0012067239,0.0002437578,0.0017256635,0.0010845823,0.00039156404,0.91743356],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003598839,0.000027511558,0.00074818474,0.000010995557,0.000010237002,0.0000055510195,0.000024394809,0.000035150304,7.971804e-9,5.1119454e-8,0.9432741,0.055827875],"study_design_scores_gemma":[0.00022776442,0.000035727575,0.00021018204,0.0000028636534,0.000031717664,0.000005188306,0.0003044334,7.6917473e-7,3.9892905e-7,0.00011137935,0.99873525,0.0003343],"about_ca_topic_score_codex":0.00073760666,"about_ca_topic_score_gemma":0.00007777579,"teacher_disagreement_score":0.9153128,"about_ca_system_score_codex":0.00038235664,"about_ca_system_score_gemma":0.00025149898,"threshold_uncertainty_score":0.9999648},"labels":[],"label_agreement":null},{"id":"W6929554722","doi":"10.5061/dryad.zgmsbcc7n","title":"Data from: An Early Devonian actinostelic euphyllophyte with secondary growth from the Emsian of Gaspé (Canada) and the importance of tracheid wall thickening patterns in early euphyllophyte systematics","year":2020,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Tracheid; Devonian; Thickening; Secondary growth; Tetrapod (structure)","score_opus":0.09828615955832866,"score_gpt":0.304638773355391,"score_spread":0.20635261379706238,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6929554722","genre_codex":"dataset","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3918322,0.00011123493,0.000074764816,0.0004684262,0.00009814952,0.0004765535,0.6066849,0.000028583794,0.00022517586],"genre_scores_gemma":[0.674456,0.000117061645,0.0001690252,0.00042490195,0.0001447374,2.0475943e-7,0.32419363,0.00048091545,0.0000135161645],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9941601,0.0013986494,0.0014393696,0.0010629736,0.0015933212,0.00034556526],"domain_scores_gemma":[0.993615,0.0012574361,0.0015457696,0.0027586813,0.0006170983,0.00020602508],"candidate_categories":["scholarly_communication","open_science","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002976324,0.00035438826,0.00086652965,0.00019953579,0.0007174054,0.0013023366,0.006692956,0.00019942792,0.0014888162],"category_scores_gemma":[0.0027304224,0.00022270017,0.00007311906,0.0007874181,0.00047983872,0.0006125988,0.002678946,0.0012453798,0.00024334047],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00088791846,0.0001561072,0.0038569195,0.00018060437,0.00020958082,0.00012427881,0.0042019514,0.000015567499,0.000047822738,0.00005885999,0.9699347,0.020325715],"study_design_scores_gemma":[0.0031319687,0.00079085823,0.12469542,0.0012338217,0.00025143198,0.000056784575,0.004669514,0.00094288454,0.000057974332,0.0019676127,0.8612836,0.00091812096],"about_ca_topic_score_codex":0.050233673,"about_ca_topic_score_gemma":0.026765848,"teacher_disagreement_score":0.28262383,"about_ca_system_score_codex":0.0000957748,"about_ca_system_score_gemma":0.00009969686,"threshold_uncertainty_score":0.9997344},"labels":[],"label_agreement":null},{"id":"W6930566533","doi":"10.5281/zenodo.14897636","title":"\"I Want to Know What Love Is\": Problematising Vector Semantics for the Analysis of Discourse in the Late Middle Ages","year":2024,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Ambiguity; Middle Ages; Period (music); Semantics (computer science); Perspective (graphical); Dimension (graph theory); Discourse analysis","score_opus":0.15398071234294186,"score_gpt":0.3846839521584887,"score_spread":0.23070323981554686,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6930566533","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9445083,0.0008175014,0.018906077,0.030358333,0.000486077,0.0014419344,0.0005946966,0.00014203592,0.0027450495],"genre_scores_gemma":[0.9978553,0.0001417638,0.00028804163,0.00021399914,0.000050553423,1.1438942e-7,0.000067396635,0.00024488434,0.0011379623],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9978459,0.00027811946,0.000550059,0.00040067916,0.0006690636,0.00025617963],"domain_scores_gemma":[0.9978147,0.0008222178,0.0001379489,0.0007380529,0.0004207854,0.00006628746],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0042032655,0.00011907467,0.00024851412,0.0006399798,0.0005754156,0.004282441,0.0017703905,0.00004159953,0.002591481],"category_scores_gemma":[0.0015459013,0.000067963774,0.00017101744,0.0026803256,0.00013533316,0.00048463405,0.0006173326,0.00016913137,0.0025550998],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000070989554,0.00014243087,0.000015884862,0.00004204635,0.00016167253,0.000012270274,0.032720257,0.0047708163,0.0010000952,0.002178695,0.10056873,0.8583161],"study_design_scores_gemma":[0.0002443539,0.00025445863,0.0022263443,0.00035426533,0.0003519629,0.000019579871,0.022880185,0.060957864,0.0003414933,0.008488596,0.9036206,0.0002603224],"about_ca_topic_score_codex":0.000015010463,"about_ca_topic_score_gemma":0.000008480559,"teacher_disagreement_score":0.8580558,"about_ca_system_score_codex":0.0000643732,"about_ca_system_score_gemma":0.0000071931368,"threshold_uncertainty_score":0.9983203},"labels":[],"label_agreement":null},{"id":"W6949826937","doi":"10.5281/zenodo.16794826","title":"ResearchBox 490, 'When Metrics Matter: Impact of Elicitation Metric', https://researchbox.org/490","year":2025,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Backup; Expert elicitation; Metric (unit); Measure (data warehouse); Preference elicitation; Selection (genetic algorithm)","score_opus":0.1557771206082407,"score_gpt":0.40697131721126306,"score_spread":0.25119419660302233,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6949826937","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007051765,0.00058548944,0.0051691565,0.0005882105,0.00052479515,0.0012805109,0.0027483625,0.00066667027,0.98138505],"genre_scores_gemma":[0.1673377,0.0009836267,0.002750648,0.00020910983,0.0006601227,6.1160887e-7,0.0032504178,0.009584081,0.8152237],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9910024,0.0019897784,0.0014122541,0.0014573891,0.0032223135,0.000915856],"domain_scores_gemma":[0.9913262,0.0012044662,0.0010202498,0.0023371014,0.0036071294,0.0005048227],"candidate_categories":["metaresearch","metaepi_narrow","sts","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.008424944,0.0005015847,0.0009565289,0.008477785,0.001409315,0.0023618226,0.005685086,0.0004682129,0.22569682],"category_scores_gemma":[0.025669098,0.00043248406,0.00048134945,0.006799317,0.0005372275,0.0004436211,0.0038556145,0.0012324967,0.07121818],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008275491,0.00018637528,0.00010231934,0.0000406371,0.00009985642,0.000014274582,0.00020580545,0.000036077727,0.00013265038,0.0003225215,0.70467424,0.2941025],"study_design_scores_gemma":[0.0006328478,0.0004913153,0.0017869613,0.00018307783,0.000044328834,0.000019020721,0.00033723758,0.0003334778,0.000081206694,0.004753614,0.9909245,0.0004124071],"about_ca_topic_score_codex":0.0008230291,"about_ca_topic_score_gemma":0.0000044260555,"teacher_disagreement_score":0.2936901,"about_ca_system_score_codex":0.00071668613,"about_ca_system_score_gemma":0.0001088061,"threshold_uncertainty_score":0.9998907},"labels":[],"label_agreement":null},{"id":"W6955178274","doi":"10.58079/myss","title":"Canadá y el mundo desde 1867","year":2019,"lang":"es","type":"article","venue":"Industrias Culturais (Universidade de Coimbra)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Context (archaeology); Perspective (graphical); Field (mathematics); Identity (music); Subject (documents)","score_opus":0.06939182876057931,"score_gpt":0.3230653144046877,"score_spread":0.2536734856441084,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6955178274","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91671866,0.00020814383,0.00007975522,0.008113763,0.0027162246,0.0006683715,0.0004636717,0.0001517314,0.07087969],"genre_scores_gemma":[0.9484403,0.000071205184,0.00041911047,0.00080453884,0.00039660383,0.0000054785883,0.00005615143,0.00007072334,0.049735878],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99384177,0.00047882923,0.0010980418,0.0016579477,0.0015353624,0.0013880654],"domain_scores_gemma":[0.99425715,0.0014533983,0.00095145253,0.0017518239,0.0006312667,0.0009549311],"candidate_categories":["metaepi_narrow","scholarly_communication","research_integrity","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0018059845,0.000767489,0.0011599679,0.0009741885,0.00066875777,0.002089875,0.0030896384,0.0014219898,0.008959816],"category_scores_gemma":[0.0012864112,0.0007137602,0.0006565249,0.002350379,0.00038496868,0.0017538622,0.00072991475,0.0015883987,0.011221121],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005816171,0.0005666808,0.061390318,0.000037182148,0.00037783748,0.0010919289,0.0027956122,0.0024069438,0.007290794,0.016075527,0.3101498,0.59723574],"study_design_scores_gemma":[0.004940871,0.00061862596,0.21026099,0.00059802015,0.00037029467,0.00034188028,0.018742869,0.0028606555,0.0012201068,0.0055096564,0.7523385,0.0021975052],"about_ca_topic_score_codex":0.008051589,"about_ca_topic_score_gemma":0.0010451074,"teacher_disagreement_score":0.59503824,"about_ca_system_score_codex":0.0012750047,"about_ca_system_score_gemma":0.0013960949,"threshold_uncertainty_score":0.99987435},"labels":[],"label_agreement":null},{"id":"W6958536954","doi":"10.6084/m9.figshare.29093727.v1","title":"Additional file 4 of Hybrid sequencing reveals the genome of a Chrysochromulina parva virus and highlight its distinct replication strategy","year":2025,"lang":"en","type":"other","venue":"Figshare","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University of Waterloo","funders":"","keywords":"Genome; DNA sequencing; Replication (statistics); Whole genome sequencing; Gene; Sequence assembly","score_opus":0.1338857762694849,"score_gpt":0.3532302597434573,"score_spread":0.2193444834739724,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6958536954","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0001002122,0.00031904894,0.0000011633941,0.000024506176,0.000032128493,0.00025987343,0.87921906,0.000026507552,0.12001749],"genre_scores_gemma":[0.0036070156,0.000015572847,0.00023480761,0.000058086538,0.00017291584,0.00033784827,0.7266969,0.00007431859,0.2688025],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9978286,0.00009558008,0.00075797824,0.00064834545,0.0005162407,0.00015326154],"domain_scores_gemma":[0.99280185,0.0042982795,0.0014020423,0.0010728398,0.0003654333,0.000059566286],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00024931214,0.00021505442,0.0005049116,0.00024088989,0.00007883441,0.00010131333,0.0008303243,0.00014599597,0.98765033],"category_scores_gemma":[0.012117048,0.00014692616,0.00015019419,0.00030850165,0.00004130901,0.000084002655,0.00026000087,0.0001634284,0.0018178836],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000041515445,0.0000146827015,3.402333e-7,0.00004408543,0.000013041607,0.000005416932,0.000007113128,0.000005479119,0.00003435734,0.000013129856,0.9839797,0.015878525],"study_design_scores_gemma":[0.00005590728,0.000033115466,0.00052272395,0.0027628564,0.000013895592,0.000010528881,0.00001906676,0.00008640549,0.00010954423,0.0014947354,0.9947399,0.00015132254],"about_ca_topic_score_codex":0.00002097472,"about_ca_topic_score_gemma":0.00004734397,"teacher_disagreement_score":0.98583245,"about_ca_system_score_codex":0.000055864974,"about_ca_system_score_gemma":0.0003981685,"threshold_uncertainty_score":0.9989593},"labels":[],"label_agreement":null},{"id":"W6962642118","doi":"10.17605/osf.io/4pjm7","title":"Ingroup biases and cognitive load (Experiment 2)","year":2020,"lang":"en","type":"other","venue":"Open Science Framework","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Preference; Task (project management); Ingroups and outgroups; Cognition; Order (exchange); Cognitive load; Term (time); Social preferences","score_opus":0.22007016658005057,"score_gpt":0.4821796696564969,"score_spread":0.2621095030764463,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6962642118","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.020747587,0.0013001196,0.0019441572,0.00126066,0.0028634511,0.0012439403,0.00019166914,0.00013274161,0.9703157],"genre_scores_gemma":[0.5671428,0.00031771482,0.072763525,0.00725279,0.0011557285,0.00015977416,0.000013128942,0.0005336193,0.35066095],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99457186,0.00010457297,0.0006356797,0.002001517,0.00220751,0.00047884946],"domain_scores_gemma":[0.99537814,0.002015158,0.00065607665,0.0012011104,0.00023313903,0.00051634986],"candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0032393087,0.00037835294,0.00077143626,0.00047748783,0.00042286687,0.00560851,0.005789209,0.0003389061,0.008804082],"category_scores_gemma":[0.017390702,0.00028239505,0.00009422137,0.001989488,0.0015254628,0.00063830067,0.004004526,0.000502801,0.0027821667],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031489602,0.000072617004,0.0005481929,0.0000017859659,0.000010078991,0.00003949134,0.00071530265,0.0000011928125,0.000036863752,0.0012461051,0.22489084,0.77240604],"study_design_scores_gemma":[0.0003811654,0.0002714452,0.000472646,0.001674681,0.000044206736,0.000019989358,0.0021453404,0.00024373179,0.00027798561,0.078266725,0.91528684,0.0009152504],"about_ca_topic_score_codex":0.00036660372,"about_ca_topic_score_gemma":0.000086589454,"teacher_disagreement_score":0.7714908,"about_ca_system_score_codex":0.00010582126,"about_ca_system_score_gemma":0.00083603896,"threshold_uncertainty_score":0.9999628},"labels":[],"label_agreement":null},{"id":"W6964038355","doi":"10.25384/sage.22002279","title":"Supplemental Material - Cognitive and Behavioral Impacts of Two Decision-Support Modes for Judgmental Bootstrapping","year":2023,"lang":"en","type":"article","venue":"Sage Journals Data","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Bootstrapping (finance); Cognition; Cognitive reframing; Cognitive bias; Cognitive ergonomics; Context (archaeology)","score_opus":0.30830048852391634,"score_gpt":0.5025163609703954,"score_spread":0.1942158724464791,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6964038355","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9555565,0.00014679211,0.0036392023,0.00012909077,0.00067383796,0.0003868373,0.039390866,0.000028699076,0.000048189293],"genre_scores_gemma":[0.99512863,0.00033955072,0.0033792844,0.00006700541,0.00017744272,0.000011016769,0.0008246611,0.000026647234,0.00004576822],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9964216,0.00008462526,0.0013832529,0.00068850303,0.00095701107,0.00046503125],"domain_scores_gemma":[0.99677396,0.0013848305,0.00062947255,0.0007652636,0.00018359548,0.00026290235],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004870434,0.00022756204,0.000543739,0.00053210097,0.00028208242,0.0007909339,0.001261266,0.00008580723,0.0046523907],"category_scores_gemma":[0.0008194028,0.0001808743,0.00013838947,0.000420497,0.00015677896,0.0015193645,0.0012822106,0.00014913305,0.00008350894],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028595128,0.00014294272,0.012025129,0.000004529002,0.000031519387,0.000059896076,0.00024630118,0.0000144881105,0.012252084,0.000003886781,0.014175464,0.9607578],"study_design_scores_gemma":[0.050819453,0.007654034,0.26413566,0.008520729,0.0023471154,0.0028986859,0.097575076,0.05069435,0.0883921,0.39521012,0.025912367,0.005840309],"about_ca_topic_score_codex":0.00010572969,"about_ca_topic_score_gemma":0.00017780346,"teacher_disagreement_score":0.9549175,"about_ca_system_score_codex":0.00003813531,"about_ca_system_score_gemma":0.00013116348,"threshold_uncertainty_score":0.9962575},"labels":[],"label_agreement":null},{"id":"W6969330350","doi":"10.5281/zenodo.7916227","title":"Nouveaux modèles, mêmes problèmes : Comment les modèles commerciaux de libre accès des cinq grands éditeurs perpétuent les inégalités dans la communication savante","year":2023,"lang":"fr","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Limiting; Research methodology; Information center","score_opus":0.1745406210549176,"score_gpt":0.3572944150570281,"score_spread":0.18275379400211048,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6969330350","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9064906,0.002936559,0.012566376,0.021355132,0.00050710555,0.0011582931,0.001686383,0.0017585481,0.051540997],"genre_scores_gemma":[0.98405915,0.005506988,0.003097668,0.000321623,0.00013398696,8.6213083e-7,0.0014511518,0.0013855227,0.004043046],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9930405,0.0029461398,0.0011085256,0.0009262958,0.0010438748,0.00093463936],"domain_scores_gemma":[0.99547696,0.00091774133,0.000453657,0.0015692073,0.0011239816,0.00045844328],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.005563983,0.00045995164,0.00055356004,0.0007466384,0.0071593868,0.0042803874,0.0042672874,0.00033010764,0.005950239],"category_scores_gemma":[0.0024260725,0.000457749,0.00026534265,0.0017825641,0.0018389222,0.001067667,0.0044501317,0.00083481893,0.0073576584],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011238647,0.00046636254,0.0004795771,0.00007797858,0.00005874939,0.000034720364,0.010098606,0.0018830595,0.00069031015,0.0071617593,0.12664263,0.85229385],"study_design_scores_gemma":[0.00085704535,0.00029705625,0.009221865,0.00048824598,0.00007349616,0.00019374574,0.018043654,0.019574368,0.00027344917,0.017892765,0.93255633,0.0005279782],"about_ca_topic_score_codex":0.00063132466,"about_ca_topic_score_gemma":0.000052974894,"teacher_disagreement_score":0.8517659,"about_ca_system_score_codex":0.00065935066,"about_ca_system_score_gemma":0.000048122012,"threshold_uncertainty_score":0.99978745},"labels":[],"label_agreement":null},{"id":"W6977820985","doi":"10.6084/m9.figshare.26735628.v1","title":"Additional file 1 of Assessing the relationship between delay discounting and decisions to engage in various protective behaviors during COVID-19","year":2024,"lang":"en","type":"article","venue":"Figshare","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto; York University","funders":"","keywords":"Discounting; Delay discounting","score_opus":0.28433852563632733,"score_gpt":0.45068734059734333,"score_spread":0.166348814961016,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6977820985","genre_codex":"dataset","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21406955,0.00002310759,0.000061642335,0.00015507729,0.000033016473,0.0002926068,0.78508985,0.00003351967,0.00024165196],"genre_scores_gemma":[0.93488604,8.893437e-8,0.0013298602,0.000051240197,0.00006276035,0.00059919996,0.06287167,0.000018303825,0.00018085908],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.99788094,0.00019910453,0.00062716025,0.0005166402,0.0005695705,0.00020661665],"domain_scores_gemma":[0.9254143,0.0736979,0.00020576769,0.00038390426,0.00012858432,0.00016952498],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0008088529,0.00013947772,0.00022235187,0.00048495026,0.0005300846,0.000774548,0.00045488024,0.00010826195,0.670563],"category_scores_gemma":[0.13725093,0.0000976347,0.00009338238,0.001075519,0.00002938656,0.00057075336,0.00036213783,0.00047419572,0.0009799773],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005117147,0.000022934271,0.0048818095,0.000015860289,0.0000046200403,0.000062725856,0.0011760662,0.00031737195,0.000006987498,0.000017923016,0.94644266,0.047045894],"study_design_scores_gemma":[0.00011439687,0.000032852564,0.82262,0.0035609624,0.000012149162,0.00004372284,0.001339434,0.0005776696,0.000009020411,0.018974764,0.15246813,0.00024691864],"about_ca_topic_score_codex":0.000029295903,"about_ca_topic_score_gemma":0.00014518366,"teacher_disagreement_score":0.8177382,"about_ca_system_score_codex":0.00015928554,"about_ca_system_score_gemma":0.00035604267,"threshold_uncertainty_score":0.9997979},"labels":[],"label_agreement":null},{"id":"W6980014832","doi":"","title":"Are there behavioral hallmarks of configural and elemental evaluation in multi-attribute decision-making?","year":2023,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Noise (video); Perception; Evaluation methods; Identification (biology)","score_opus":0.1445970853040476,"score_gpt":0.4164015540022347,"score_spread":0.2718044686981871,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6980014832","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9915102,0.0003436597,5.9853477e-7,0.000011014414,0.0025037692,0.0012642366,0.0028700216,0.00009902641,0.0013974665],"genre_scores_gemma":[0.9972392,0.000093615454,0.0008631826,0.0000606834,0.000026970274,0.00015328087,0.0005252455,0.00016833015,0.0008695225],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.98942,0.0008349122,0.003440771,0.0021157626,0.0033697593,0.00081881584],"domain_scores_gemma":[0.99087006,0.0025758273,0.003280744,0.0013715951,0.001598389,0.00030336995],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.009035613,0.0009145138,0.0017584038,0.0018845998,0.0006598253,0.0004106766,0.0016712054,0.0011546811,0.0010650344],"category_scores_gemma":[0.008300502,0.00084982725,0.00057625124,0.001554899,0.00015498826,0.0010915074,0.00041679273,0.0014254675,0.00044030833],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036357332,0.0004962146,0.012467328,0.000038604445,0.000049698785,0.00016448695,0.0000404831,0.00017210792,0.0013017257,0.0003251265,0.000034631994,0.984546],"study_design_scores_gemma":[0.0067309774,0.0006469639,0.7673539,0.0046001603,0.00073122536,0.000070040805,0.019267011,0.0020073012,0.004265705,0.18758674,0.003636547,0.0031034574],"about_ca_topic_score_codex":0.00046368942,"about_ca_topic_score_gemma":0.022937054,"teacher_disagreement_score":0.9814426,"about_ca_system_score_codex":0.00086115184,"about_ca_system_score_gemma":0.00015212261,"threshold_uncertainty_score":0.9998481},"labels":[],"label_agreement":null},{"id":"W6982102273","doi":"","title":"At Guelph Volume 30 Number 28, September 4, 1986","year":2017,"lang":"en","type":"other","venue":"The Atrium (University of Guelph)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Division of Environmental Biology; Ministry of Colleges and Universities; Murdoch University; McMaster University; Iowa State University","keywords":"","score_opus":0.06611961782234957,"score_gpt":0.3169930769166739,"score_spread":0.25087345909432435,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6982102273","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.045233093,0.00029022145,0.00024638642,0.0008567355,0.0016495049,0.00032117224,0.00037708718,0.00012945247,0.9508963],"genre_scores_gemma":[0.19010729,0.00011539558,0.00048033142,0.00006097575,0.00025449938,2.3767758e-7,0.00001887091,0.000118642136,0.8088438],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9968916,0.00021803011,0.0003862793,0.00088187814,0.0011821908,0.00043998242],"domain_scores_gemma":[0.99419916,0.00043953824,0.0016858862,0.0032215924,0.0002491319,0.00020469433],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0016422508,0.00040794234,0.0009515526,0.00035017444,0.0007130858,0.00017667572,0.004786237,0.00057257706,0.09965166],"category_scores_gemma":[0.0002821596,0.00033112368,0.0007197448,0.0002795354,0.00087054516,0.00026920563,0.0018248132,0.00039899026,0.058261584],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000047342386,0.000041112704,0.0015662509,0.0000072328603,0.000060807473,0.000057242803,0.0001961201,0.000006691192,0.00014492338,0.000045016925,0.9656178,0.032209486],"study_design_scores_gemma":[0.00046917834,0.000033708373,0.010623425,0.00009242967,0.00016826703,0.00002671664,0.0005097541,0.000116144,0.0000037944458,0.002670638,0.9848841,0.00040185032],"about_ca_topic_score_codex":0.0017830265,"about_ca_topic_score_gemma":0.0021052833,"teacher_disagreement_score":0.14487419,"about_ca_system_score_codex":0.00016014033,"about_ca_system_score_gemma":0.0001454659,"threshold_uncertainty_score":0.9999141},"labels":[],"label_agreement":null},{"id":"W6982104773","doi":"","title":"Guy Pierre. 2015. La crise de 1929 et le développement du capitalisme en Haïti. Une perspective de longue durée et une conjoncture perdue. Montreal: CIDIHCA. 548 pp. ISBN: 9782894543283.","year":2017,"lang":"fr","type":"other","venue":"Redalyc (Universidad Autónoma del Estado de México)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Nucleofection; Gestational period; TSG101; Dysgeusia; Diafiltration; Liquation; Emperipolesis; Demotion; Triacetin","score_opus":0.03191612626980148,"score_gpt":0.32809126627114893,"score_spread":0.2961751400013474,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6982104773","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.33014303,0.018011127,0.037631623,0.19719464,0.0041690343,0.0029329113,0.002450131,0.0008554273,0.4066121],"genre_scores_gemma":[0.7265743,0.010012816,0.01437992,0.0021410603,0.00087331445,0.00007041553,0.000220154,0.0008035005,0.24492453],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.98920715,0.0021718605,0.0014186207,0.0031833919,0.0016919012,0.0023271032],"domain_scores_gemma":[0.98931694,0.0021924353,0.0023573022,0.0034802642,0.0010829839,0.0015700605],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"category_scores_codex":[0.0046016825,0.002038459,0.002549841,0.0016328109,0.0014932735,0.0021820616,0.004829707,0.0028076922,0.0043545193],"category_scores_gemma":[0.0018709038,0.002101094,0.0014734111,0.0013008018,0.0016809268,0.0016176774,0.0015976173,0.002567423,0.0014534857],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":true,"study_design_scores_codex":[0.0010392461,0.0024557337,0.007505475,0.00015220746,0.0013190374,0.01569817,0.05986518,0.006313805,0.0007204301,0.07154949,0.60264194,0.2307393],"study_design_scores_gemma":[0.0068215705,0.0007748295,0.098625764,0.0015702188,0.0013273589,0.0022670683,0.07426953,0.013048815,0.00013140228,0.06034257,0.73688143,0.00393944],"about_ca_topic_score_codex":0.071443364,"about_ca_topic_score_gemma":0.0341332,"teacher_disagreement_score":0.39643127,"about_ca_system_score_codex":0.005024078,"about_ca_system_score_gemma":0.0073797256,"threshold_uncertainty_score":0.99980664},"labels":[],"label_agreement":null},{"id":"W6989461760","doi":"","title":"Behavioural and theoretical support for ranking theory as an alternative model of human uncertainty representation","year":2024,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Ranking (information retrieval); Probability distribution; Representation (politics); Probability theory; Task (project management); Imprecise probability; Decision theory; Logarithm","score_opus":0.10456295861023522,"score_gpt":0.3771395452114549,"score_spread":0.27257658660121964,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6989461760","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9874893,0.00004087188,0.0046419622,0.00019118424,0.00017807237,0.00032438018,0.0028104356,0.00013152756,0.004192279],"genre_scores_gemma":[0.99759775,0.0000035991782,0.0010966259,0.00015481561,0.00007621514,0.000024349898,0.0003452949,0.000053622472,0.000647718],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99711585,0.0001642285,0.0009246914,0.0008268484,0.000663462,0.00030493966],"domain_scores_gemma":[0.9972443,0.0016725018,0.0001992558,0.00051300996,0.00012355753,0.00024735334],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0017778445,0.00024647615,0.00039456264,0.0003584353,0.00015066178,0.0031521386,0.000720434,0.00014523164,0.00064060895],"category_scores_gemma":[0.0012192192,0.0001857906,0.00025743307,0.0003201275,0.00044671216,0.0049079154,0.00028540698,0.00027739556,0.0001750514],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00057187007,0.0002173029,0.030495709,0.000019895582,0.000038352624,0.000034897188,0.00058731344,0.0005046539,0.000533573,0.71251273,0.00043626397,0.25404745],"study_design_scores_gemma":[0.000341419,0.00028313397,0.0004108051,0.000056080466,0.0000355144,0.000015173299,0.00027577498,0.030298961,0.0020781513,0.9653382,0.0006330399,0.00023379704],"about_ca_topic_score_codex":0.000004289493,"about_ca_topic_score_gemma":0.0000013980166,"teacher_disagreement_score":0.25381365,"about_ca_system_score_codex":0.000028485103,"about_ca_system_score_gemma":0.00012580703,"threshold_uncertainty_score":0.99788266},"labels":[],"label_agreement":null},{"id":"W7006336425","doi":"","title":"Three Essays on Online Economic Experiments and Experimental Data Analysis","year":2020,"lang":"en","type":"dissertation","venue":"Spectrum Research Repository (Concordia University)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Valuation (finance); Public health; Value (mathematics); Task (project management); Health insurance; Everyday life","score_opus":0.20616628050709457,"score_gpt":0.4313908345931424,"score_spread":0.22522455408604786,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7006336425","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95473355,0.00025284025,0.000033520206,0.00024787697,0.0011886577,0.0003833626,0.00033907185,0.000064872496,0.04275625],"genre_scores_gemma":[0.98933125,0.00006985828,0.00010194759,0.000016653423,0.00036883308,0.0000024739686,0.0007528179,0.00004966004,0.009306538],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99377346,0.00048713188,0.000798952,0.002675461,0.0016283026,0.0006366708],"domain_scores_gemma":[0.99474007,0.0010841305,0.0005351313,0.0028503793,0.00017466099,0.00061560737],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001403167,0.00046567962,0.0010426028,0.0031096442,0.00086250773,0.0010581576,0.004174106,0.0004008861,0.00047072637],"category_scores_gemma":[0.0003152873,0.00046306147,0.00036880226,0.0017314784,0.00032142483,0.00075579353,0.0014114804,0.0010909144,0.00037029505],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.030907733,0.0077058272,0.43489125,0.00018406364,0.0139369415,0.020442456,0.011161964,0.0022763312,0.026653586,0.023553222,0.1439518,0.2843348],"study_design_scores_gemma":[0.00939193,0.007705968,0.30057085,0.000555595,0.00364075,0.00009668305,0.12828776,0.07558602,0.07551774,0.032820683,0.3582508,0.0075752125],"about_ca_topic_score_codex":0.0063321306,"about_ca_topic_score_gemma":0.030617481,"teacher_disagreement_score":0.2767596,"about_ca_system_score_codex":0.0008798314,"about_ca_system_score_gemma":0.0008235945,"threshold_uncertainty_score":0.99997884},"labels":[],"label_agreement":null},{"id":"W7009478780","doi":"","title":"Do children predict the sunk cost bias if prompted to consider effort and emotion?","year":2024,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Sunk costs; Character (mathematics); Control (management); Sadness; Dynamic inconsistency","score_opus":0.07298248528803979,"score_gpt":0.3258285006611064,"score_spread":0.2528460153730666,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7009478780","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9841326,0.00034812308,0.00018760617,0.0038188072,0.00053301285,0.00088679884,0.0034260093,0.00041062044,0.006256432],"genre_scores_gemma":[0.9965767,0.000012577873,0.00032754993,0.001132521,0.00022432691,0.000038583556,0.00015242392,0.00007197262,0.0014633304],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9962595,0.0001344312,0.0009939781,0.0011028405,0.0010044174,0.0005048387],"domain_scores_gemma":[0.9967292,0.001584924,0.00014274215,0.0009362648,0.00009159481,0.0005152831],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0015395439,0.00037674117,0.00041661243,0.0004531893,0.00033417947,0.015206733,0.0011266749,0.00017980355,0.0012114665],"category_scores_gemma":[0.0020610166,0.00022570073,0.00023922446,0.0012759196,0.00024676224,0.004058507,0.0007778062,0.00056501955,0.009630227],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007713067,0.00010640645,0.44612816,0.000007576678,0.000051675695,0.00008283485,0.00011883237,0.000043002277,0.000011921706,0.001236646,0.06825826,0.48387754],"study_design_scores_gemma":[0.00044341912,0.0002043262,0.24009433,0.00026425972,0.000049899536,0.00033482575,0.00016728729,0.00062990165,0.00019590653,0.15532395,0.60162795,0.00066392357],"about_ca_topic_score_codex":0.0000036471783,"about_ca_topic_score_gemma":0.0000016744492,"teacher_disagreement_score":0.5333697,"about_ca_system_score_codex":0.00003903462,"about_ca_system_score_gemma":0.00018879832,"threshold_uncertainty_score":0.99970156},"labels":[],"label_agreement":null},{"id":"W7009700429","doi":"","title":"Exelon and Pepco Holdings Inc. Reach Settlement Agreement with Montgomery and Prince George’s Counties in Maryland - Commodities (COMMODIT) News","year":2015,"lang":"en","type":"other","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Settlement (finance); Trade agreement; Human settlement; Agreement","score_opus":0.08196073329870758,"score_gpt":0.3361934895226765,"score_spread":0.25423275622396896,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7009700429","genre_codex":"empirical","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6097648,0.0049802065,0.00009188017,0.001563062,0.00072590896,0.0013368522,0.0011437902,0.00016312167,0.38023037],"genre_scores_gemma":[0.04173725,0.002623145,0.0040590474,0.00087367365,0.00030399117,0.00010117495,0.0002767487,0.00035049973,0.9496745],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9963453,0.00013056461,0.0008819976,0.0010247199,0.0012036776,0.0004137803],"domain_scores_gemma":[0.9974394,0.0003522698,0.0009335832,0.00090936257,0.00014390002,0.00022147645],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0022012822,0.00052341295,0.000983503,0.00086113566,0.00010676053,0.000744745,0.00064267975,0.00028378362,0.0012361606],"category_scores_gemma":[0.00015369557,0.00035004967,0.000040235183,0.00025696875,0.00038015321,0.00031025053,0.00067739777,0.00032367534,0.000102640835],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008573954,0.0000871211,0.060421858,0.000022914219,0.000022095104,0.000027727467,0.00042145053,0.000006291897,0.000002268432,0.00012753755,0.8901887,0.048586328],"study_design_scores_gemma":[0.0010470882,0.00021845323,0.0058978,0.00026342453,0.00003448452,0.000028945979,0.0032224474,0.00011440698,0.000003193238,0.0054213894,0.98316306,0.0005853356],"about_ca_topic_score_codex":0.0073766983,"about_ca_topic_score_gemma":0.0550467,"teacher_disagreement_score":0.5694441,"about_ca_system_score_codex":0.00014446463,"about_ca_system_score_gemma":0.00015325252,"threshold_uncertainty_score":0.99989516},"labels":[],"label_agreement":null},{"id":"W7020706266","doi":"","title":"Meta-reasoning: Deciding which game to play, which problem to solve, and when to quit","year":2025,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Princeton University; York University; Yale University","keywords":"Cognition; Flexibility (engineering); Bounded function; Feature (linguistics); Range (aeronautics); Decision problem","score_opus":0.08280820396397659,"score_gpt":0.3258223067878651,"score_spread":0.24301410282388852,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7020706266","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94802743,0.00017293218,0.0077675493,0.012496516,0.00040392735,0.0010168349,0.0013713929,0.00033185084,0.028411582],"genre_scores_gemma":[0.94966847,0.000003869796,0.038540594,0.005804218,0.000109494715,0.00014221779,0.00004875243,0.00008989037,0.0055924705],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9942037,0.00013085669,0.0015822959,0.0018764347,0.0012438175,0.0009629213],"domain_scores_gemma":[0.9948998,0.0016745192,0.00023829074,0.0013603844,0.00042630557,0.0014006833],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0022077502,0.0006280161,0.0011388354,0.0013997565,0.00035596965,0.011471174,0.0023154127,0.0002718574,0.0008912275],"category_scores_gemma":[0.007894221,0.0004926431,0.00031077495,0.003959499,0.000047730307,0.0045911833,0.0025270495,0.0005386894,0.008371121],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009258265,0.00054944365,0.20446855,0.000039007315,0.00059633947,0.00007418876,0.0010518739,0.0015036738,0.0007153678,0.009626655,0.17490555,0.6055435],"study_design_scores_gemma":[0.00047499794,0.00028569382,0.007366581,0.0002708856,0.00020215167,0.00001871316,0.0002391482,0.0001133778,0.0015628542,0.20117511,0.7873552,0.0009353258],"about_ca_topic_score_codex":0.00001481555,"about_ca_topic_score_gemma":0.00010984017,"teacher_disagreement_score":0.6124496,"about_ca_system_score_codex":0.000097354336,"about_ca_system_score_gemma":0.0003409478,"threshold_uncertainty_score":0.9997525},"labels":[],"label_agreement":null},{"id":"W7045686250","doi":"","title":"Balance of Choices Involving Chance: Psychometric Evaluation","year":2020,"lang":"en","type":"article","venue":"Scholarship at UWindsor (University of Windsor)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of Windsor","keywords":"Nucleofection; Gestational period; TSG101; Dysgeusia; Liquation; Diafiltration; Emperipolesis; Triacetin; Durvalumab","score_opus":0.2341097266003796,"score_gpt":0.36761206641946514,"score_spread":0.13350233981908555,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7045686250","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9945354,0.00059910165,0.00030673156,0.000980449,0.00036305992,0.00027251994,0.0000650341,0.00003870898,0.002839038],"genre_scores_gemma":[0.99758947,0.0000610222,0.0016424222,0.00017642794,0.0000776835,4.38018e-7,0.000011077089,0.000015416874,0.00042606256],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99575007,0.00036591326,0.00063928444,0.00081604294,0.0021139167,0.00031477085],"domain_scores_gemma":[0.99623793,0.0006625234,0.0010657792,0.00076664105,0.0009805647,0.00028656583],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0042597395,0.00021697357,0.00063794747,0.00080823805,0.00031904332,0.000094546034,0.0019096488,0.00022812374,0.0023288012],"category_scores_gemma":[0.0033206595,0.00022997308,0.00032487008,0.0031187197,0.00024207536,0.0015007339,0.00046028497,0.0003518546,0.00053459324],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048799082,0.00020382606,0.7540631,0.000037510592,0.00005636501,0.000007817465,0.0031865514,0.0006202143,0.018286353,0.00016934612,0.0017139415,0.22116695],"study_design_scores_gemma":[0.0029247827,0.00045099156,0.9572288,0.00015022868,0.00016497733,0.000006687129,0.0041997433,0.007340788,0.0035795271,0.011035443,0.012337738,0.0005803026],"about_ca_topic_score_codex":0.000043957945,"about_ca_topic_score_gemma":0.000081221086,"teacher_disagreement_score":0.22058664,"about_ca_system_score_codex":0.00012330447,"about_ca_system_score_gemma":0.00015745178,"threshold_uncertainty_score":0.9985832},"labels":[],"label_agreement":null},{"id":"W7066072462","doi":"","title":"Generating Distributed Randomness using Artificial Neural Networks","year":2024,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Randomness; Artificial neural network; Representation (politics); Binary number; Cognition","score_opus":0.08655545151657267,"score_gpt":0.32658671676413425,"score_spread":0.24003126524756158,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7066072462","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94376534,0.00052886194,0.049254846,0.00042670325,0.001815402,0.00022403606,0.0027251632,0.0005206911,0.00073897553],"genre_scores_gemma":[0.9969535,0.0000032282828,0.0010868838,0.00030734073,0.0009039052,0.000009372048,0.00046841093,0.00008899154,0.00017840731],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9956747,0.00021292864,0.0014719814,0.0010631706,0.0009122328,0.00066496234],"domain_scores_gemma":[0.9970572,0.001540679,0.00022426074,0.0006895872,0.00009595929,0.00039231894],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0013012924,0.00041302398,0.0005584821,0.00039632438,0.0004148028,0.019403191,0.0010958138,0.0002492616,0.0009289961],"category_scores_gemma":[0.0015357754,0.00031560063,0.00047840358,0.0016761454,0.00015132612,0.006571241,0.000526909,0.00070629886,0.0020395142],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027740034,0.00014696867,0.014089237,0.0000114928625,0.000039550156,0.00042123246,0.000025518106,0.057774194,0.00028768036,0.0015602362,0.0048414706,0.920525],"study_design_scores_gemma":[0.00033846335,0.000045283374,0.00017478202,0.00009078518,0.00003225298,0.00007997446,0.00006916147,0.8557657,0.00027923923,0.08860571,0.053955857,0.000562795],"about_ca_topic_score_codex":0.000002706543,"about_ca_topic_score_gemma":0.0000017024742,"teacher_disagreement_score":0.9199622,"about_ca_system_score_codex":0.000065649634,"about_ca_system_score_gemma":0.0001436732,"threshold_uncertainty_score":0.99998426},"labels":[],"label_agreement":null},{"id":"W7085148421","doi":"10.5281/zenodo.17286644","title":"Prevalence of depression among elderly patients in India: A systematic review and meta-analysis","year":2025,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Office of the Chief Medical Examiner","funders":"","keywords":"Depression (economics); Geriatric Depression Scale; Psychological intervention; Mental health; Prevalence; Population; Meta-analysis; Epidemiology","score_opus":0.09170105938148994,"score_gpt":0.3486791579248762,"score_spread":0.25697809854338627,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7085148421","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95065427,0.011443592,0.0021417213,0.00046427184,0.00008876904,0.003441912,0.0005504751,0.00020886469,0.031006154],"genre_scores_gemma":[0.9985774,0.00035379833,0.00008388543,0.00010414981,0.0000018217739,2.0646262e-7,0.00003478427,0.000083759514,0.0007601518],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99710494,0.00077585847,0.0009215524,0.00048580987,0.0005514547,0.00016039611],"domain_scores_gemma":[0.9978161,0.00023057962,0.0004266869,0.00074731733,0.0007047702,0.00007454066],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0033105563,0.000115970266,0.0008170374,0.0008134931,0.00036260212,0.0004211778,0.0011822219,0.000053442087,0.0035396514],"category_scores_gemma":[0.005311291,0.00008439488,0.00020678781,0.002004764,0.0001115485,0.00030628755,0.00093055714,0.00014068431,0.00033307465],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004404736,0.005356639,0.0890736,0.24218649,0.046803568,0.00009598553,0.008734273,0.0011106924,0.00029331818,0.006400676,0.17999163,0.41951266],"study_design_scores_gemma":[0.002781044,0.0010643792,0.6715449,0.010961195,0.27214107,0.00003216239,0.0014059547,0.002081554,0.0002853747,0.01311256,0.023011284,0.0015785124],"about_ca_topic_score_codex":0.00001640724,"about_ca_topic_score_gemma":0.0000011665038,"teacher_disagreement_score":0.5824713,"about_ca_system_score_codex":0.000047689475,"about_ca_system_score_gemma":0.0000033734877,"threshold_uncertainty_score":0.99737126},"labels":[],"label_agreement":null},{"id":"W7092588826","doi":"10.57902/d7t01p","title":"Arctic Geospatial Data for Cold Region Transportation Infrastructure Analysis: High Resolution LiDAR Point Clouds along the Steese Highway, Alaska, 2023 - Site_9","year":2023,"lang":"en","type":"dataset","venue":"California Digital Library","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Geospatial analysis; Lidar; Terrain; Arctic; Point cloud; High resolution; Permafrost; The arctic","score_opus":0.05633738611340885,"score_gpt":0.30686148726080076,"score_spread":0.25052410114739193,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7092588826","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02928575,0.00012902473,0.0010004499,0.0012117627,0.00150548,0.000896444,0.96576774,0.0001901603,0.000013214005],"genre_scores_gemma":[0.030919338,0.000100883546,0.00024905725,0.00041058825,0.0008832116,0.00008158105,0.9665593,0.00008979132,0.00070627313],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99357593,0.00017122489,0.002182528,0.0019463737,0.001464443,0.00065947726],"domain_scores_gemma":[0.99112606,0.0027345135,0.0014314683,0.0041682576,0.00022371624,0.00031600794],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0011317711,0.00069293065,0.0011640795,0.0009397214,0.00047294542,0.003466135,0.004490995,0.0007286866,0.00028857077],"category_scores_gemma":[0.001500851,0.00047517006,0.0007557554,0.0026842733,0.0002783613,0.0029753693,0.0008077406,0.0007206833,0.0032471998],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002720879,0.00007253974,0.0014932556,0.000040897605,0.00023837494,0.00009055611,0.000014462944,0.0013862636,4.1178345e-7,0.000022105412,0.9883911,0.007977927],"study_design_scores_gemma":[0.0005007031,0.00013035786,0.0055606174,0.00012763219,0.00094887,0.00000973379,0.00016592775,0.001457658,0.0000030277688,0.013820362,0.976667,0.0006081028],"about_ca_topic_score_codex":0.00028068127,"about_ca_topic_score_gemma":0.00068424636,"teacher_disagreement_score":0.013798256,"about_ca_system_score_codex":0.000113173424,"about_ca_system_score_gemma":0.00047867227,"threshold_uncertainty_score":0.99977},"labels":[],"label_agreement":null},{"id":"W7095338951","doi":"","title":"Older and Younger Adults &amp;apos; Strategy Use and Execution in Currency Conversion Tasks: Insights From French Franc to Euro and Euro","year":2014,"lang":"en","type":"article","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Euros; Currency; Calculator; Older people","score_opus":0.16373481950879606,"score_gpt":0.3768363988746975,"score_spread":0.21310157936590143,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7095338951","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9969562,0.00030669093,0.0014019541,0.0001739353,0.00044015574,0.0002208835,0.0000329422,0.00002906268,0.00043812406],"genre_scores_gemma":[0.9978629,0.000089461086,0.0011905562,0.0004071943,0.00004710282,0.000003991293,0.000012751645,0.000011757523,0.00037433772],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9976805,0.00017567024,0.00060611183,0.00090615766,0.00040893693,0.00022266338],"domain_scores_gemma":[0.9978493,0.0011214702,0.00014316976,0.0004496805,0.00017187792,0.00026454375],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055124145,0.00022555453,0.00036422542,0.00037182364,0.00012535464,0.0006981291,0.00022820363,0.00014498047,0.00022599736],"category_scores_gemma":[0.0008435943,0.00016674053,0.00003275342,0.0003340873,0.00011431379,0.0011239666,0.00023262967,0.00017441792,0.00017570022],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018682977,0.00022217091,0.18175557,0.000009985607,0.000008355727,0.000018529727,0.0054093758,0.000038623704,0.0020046313,0.000432166,0.01397174,0.795942],"study_design_scores_gemma":[0.0015358542,0.00023182912,0.95454913,0.00012628314,0.000016379277,0.000010618973,0.0006020507,0.0035191139,0.00014290438,0.015687702,0.023155669,0.0004224368],"about_ca_topic_score_codex":0.002448877,"about_ca_topic_score_gemma":0.0019336407,"teacher_disagreement_score":0.7955196,"about_ca_system_score_codex":0.00002070896,"about_ca_system_score_gemma":0.000021781994,"threshold_uncertainty_score":0.67994815},"labels":[],"label_agreement":null},{"id":"W7096207395","doi":"","title":"Bristol-West Insurance Group","year":2015,"lang":"en","type":"article","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Autobiographical memory; Quarter (Canadian coin); Replicate; Affect (linguistics); Order (exchange); Event (particle physics)","score_opus":0.31110862206404466,"score_gpt":0.4300136630334191,"score_spread":0.11890504096937443,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7096207395","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92227024,0.00006903958,0.0026619874,0.00044988227,0.0011193939,0.000058132387,0.000009392642,0.00007487796,0.07328703],"genre_scores_gemma":[0.99106,0.000002516197,0.0031535605,0.0004982876,0.00008941145,0.0000031527895,0.0000015330664,0.0000088852485,0.005182627],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980149,0.00006436625,0.00053176674,0.00042767762,0.0007602551,0.00020102023],"domain_scores_gemma":[0.99827325,0.00039172368,0.00014470088,0.00069000426,0.0002535336,0.0002467796],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0022246542,0.00010999657,0.00023709203,0.00014767925,0.00007217666,0.0003975715,0.00083346304,0.00006921893,0.0007424832],"category_scores_gemma":[0.0014936151,0.00007528847,0.000088079636,0.0004389959,0.00008162559,0.00045815666,0.00015869363,0.0000979782,0.010885571],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023688632,0.000078146186,0.09162238,2.0216604e-7,0.0000015776143,0.000017907087,0.00013143427,0.000060308255,0.000032607248,0.0014758857,0.08081199,0.82574385],"study_design_scores_gemma":[0.0006965823,0.000160972,0.11584079,0.000008726448,0.0000043939367,0.000051215524,0.0009936551,0.00079120096,0.00009043699,0.27272874,0.6082813,0.00035199628],"about_ca_topic_score_codex":0.00014750876,"about_ca_topic_score_gemma":0.00025585506,"teacher_disagreement_score":0.8253919,"about_ca_system_score_codex":0.000050437196,"about_ca_system_score_gemma":0.000059394726,"threshold_uncertainty_score":0.98988456},"labels":[],"label_agreement":null},{"id":"W7096652463","doi":"","title":"Saskatoon by","year":2008,"lang":"en","type":"article","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Interpretation (philosophy); Inference; Advice (programming); Probabilistic logic; Psychological research","score_opus":0.2675328607806963,"score_gpt":0.41625043682881846,"score_spread":0.14871757604812214,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7096652463","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9111942,0.000037602083,0.0013019096,0.0004776274,0.0003004025,0.000033534412,0.000006511565,0.000050300037,0.08659789],"genre_scores_gemma":[0.9530483,0.000006756356,0.0012488861,0.0006053494,0.000029474819,0.0000015233692,0.0000012563765,0.000005553163,0.045052927],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99861026,0.000030835494,0.00037902722,0.00031924507,0.0005085077,0.0001521147],"domain_scores_gemma":[0.9988857,0.00038391372,0.00007741284,0.00047176593,0.00008302399,0.00009821078],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0006459379,0.0000756678,0.00015830425,0.00009252299,0.00014410028,0.00011347938,0.0005103251,0.000051852818,0.0037220942],"category_scores_gemma":[0.00032529767,0.000049559785,0.000083649524,0.00025512432,0.00008315513,0.00026267732,0.00007920691,0.00006385254,0.0081046615],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000381997,0.00003788273,0.0051690335,4.097681e-8,7.6469246e-7,0.000011496884,0.000057263325,0.0000049996324,0.00019719661,0.00011396994,0.71166974,0.28273377],"study_design_scores_gemma":[0.00020488276,0.00006748309,0.0039999792,0.0000016531312,0.0000019459242,0.000089620036,0.00019995365,0.00033491378,0.0011112171,0.039836697,0.95398194,0.00016973338],"about_ca_topic_score_codex":0.000030854466,"about_ca_topic_score_gemma":0.00002176747,"teacher_disagreement_score":0.282564,"about_ca_system_score_codex":0.000017587981,"about_ca_system_score_gemma":0.000032323907,"threshold_uncertainty_score":0.9971886},"labels":[],"label_agreement":null},{"id":"W7099027828","doi":"","title":"1What Works in Youth Literacy and Why? A Literature Review and Discussion","year":2001,"lang":"en","type":"article","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Literacy; Process (computing); Apprenticeship; Adult literacy; Information literacy","score_opus":0.07325185133720459,"score_gpt":0.39269316766594603,"score_spread":0.31944131632874145,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7099027828","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92232686,0.06611468,0.0002475413,0.008876235,0.00018295845,0.000249123,0.000013157495,0.000029020499,0.001960414],"genre_scores_gemma":[0.9211098,0.06883431,0.0014161769,0.004906671,0.000047792593,0.000006145012,0.000009459762,0.000012559402,0.0036570672],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99833316,0.00010255696,0.00056622823,0.0005329296,0.0002746283,0.00019052578],"domain_scores_gemma":[0.99897605,0.00027420977,0.00011425044,0.00042253258,0.000073381736,0.00013955413],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0013897434,0.00015272037,0.0003788466,0.00023782978,0.00007368767,0.0012891284,0.00025184578,0.00010186018,0.00027947314],"category_scores_gemma":[0.0005056231,0.000072180614,0.00005313508,0.00077302253,0.000051412924,0.0012359421,0.00020005617,0.0002019224,0.00004498535],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016450218,0.000030282677,0.010869502,0.000010022172,8.6239686e-7,0.000035967252,0.001053906,7.202349e-7,0.0000029264002,0.000046613473,0.0021850148,0.98574775],"study_design_scores_gemma":[0.0039042733,0.00049401604,0.09279762,0.043881577,0.00021787838,0.0013401118,0.0069997637,0.0027315961,0.000021264796,0.28774145,0.5574834,0.0023870945],"about_ca_topic_score_codex":0.000011701075,"about_ca_topic_score_gemma":0.000053388576,"teacher_disagreement_score":0.98336065,"about_ca_system_score_codex":0.000014917659,"about_ca_system_score_gemma":0.0000115951125,"threshold_uncertainty_score":0.99974763},"labels":[],"label_agreement":null},{"id":"W7099757122","doi":"","title":"and","year":2001,"lang":"en","type":"article","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Order (exchange); Value (mathematics); Constant (computer programming); Risk aversion (psychology); Marginal utility; Social risk","score_opus":0.2769398743294252,"score_gpt":0.4611550126299083,"score_spread":0.18421513830048314,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7099757122","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90783286,0.000023019014,0.0010972238,0.00068606704,0.00013739234,0.00001749007,4.9668915e-7,0.00001967338,0.09018576],"genre_scores_gemma":[0.98821294,0.000013198328,0.0012824623,0.00036191975,0.000024281284,5.234316e-7,9.601004e-8,0.000002079167,0.010102468],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99934214,0.000013422459,0.0001855494,0.0001858349,0.00019469738,0.000078367964],"domain_scores_gemma":[0.99934,0.00030562014,0.00003157803,0.000222065,0.000041520794,0.000059215134],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0006516704,0.000037519974,0.000081554885,0.000075849406,0.00005028818,0.00020183895,0.0001756899,0.000023787179,0.002014942],"category_scores_gemma":[0.00034731178,0.000023137802,0.000023243012,0.0001494704,0.000031344953,0.00014598951,0.00006625714,0.000028358936,0.0013640514],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000307903,0.0000075641874,0.025742523,2.2228171e-8,3.1489697e-7,0.0000056973677,0.000020064648,0.0000023129178,0.000025796478,0.0009225933,0.008021277,0.96524876],"study_design_scores_gemma":[0.00013479326,0.000030522267,0.034398027,0.0000015001712,0.0000018457301,0.00006587857,0.00029997918,0.00084246194,0.00004251811,0.39416698,0.5699275,0.0000879589],"about_ca_topic_score_codex":0.000013800545,"about_ca_topic_score_gemma":0.000028336939,"teacher_disagreement_score":0.9651608,"about_ca_system_score_codex":0.0000044312665,"about_ca_system_score_gemma":0.000006819121,"threshold_uncertainty_score":0.9994135},"labels":[],"label_agreement":null},{"id":"W7101023960","doi":"","title":"（Universite de Montreal）","year":2007,"lang":"en","type":"article","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Rationalizability; Axiom; Social choice theory; Axiomatic system; Consistency (knowledge bases)","score_opus":0.12750768242649715,"score_gpt":0.42608275963802605,"score_spread":0.29857507721152887,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7101023960","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7608102,0.000009112274,0.024216292,0.00017996292,0.00016608862,0.000024466666,0.0000016268715,0.00003757728,0.2145547],"genre_scores_gemma":[0.9773117,0.0000023929088,0.0051020593,0.0003869529,0.00004086224,1.2712786e-7,3.7625318e-7,0.0000040193745,0.017151544],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99891067,0.000020122096,0.00027765625,0.00023604733,0.0003314038,0.00022408621],"domain_scores_gemma":[0.99860084,0.0007321731,0.000072947056,0.00035871362,0.000093638664,0.00014168904],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0026857182,0.00006240596,0.00011752812,0.00021029552,0.000087937566,0.00013392656,0.0004802996,0.000056887944,0.0016728468],"category_scores_gemma":[0.00038023925,0.000045071614,0.000083078834,0.00029871464,0.000036081183,0.00020564256,0.000089084104,0.0000621313,0.002157369],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020814308,0.000023531813,0.013387627,6.3203e-8,0.0000014220791,0.000044086803,0.00014322801,0.000036175104,0.0001260103,0.0010326501,0.018893493,0.9662909],"study_design_scores_gemma":[0.000663005,0.00009485644,0.2668696,0.000006705723,0.000014381194,0.000057923586,0.0042789946,0.0018928398,0.0013314916,0.3908447,0.3335991,0.00034638273],"about_ca_topic_score_codex":0.00029993235,"about_ca_topic_score_gemma":0.0009147378,"teacher_disagreement_score":0.9659445,"about_ca_system_score_codex":0.00005911362,"about_ca_system_score_gemma":0.000031845713,"threshold_uncertainty_score":0.99923974},"labels":[],"label_agreement":null},{"id":"W7106607324","doi":"10.2139/ssrn.5793943","title":"The Two-System View of Cognition and Investor Choice","year":2025,"lang":"","type":"preprint","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Intuition; Cognition; Portfolio; Construct (python library); Mutual fund; Foundation (evidence); China","score_opus":0.055868020568518695,"score_gpt":0.3679582268284272,"score_spread":0.3120902062599085,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7106607324","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9281846,0.050598763,0.007007405,0.0018325944,0.0062150825,0.00092819554,0.00010219895,0.000036221267,0.0050948914],"genre_scores_gemma":[0.94970596,0.046915594,0.00017576144,0.00009857202,0.0004929077,0.000014273101,0.0000039348565,0.000028082333,0.002564918],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99032867,0.0011739564,0.0032920502,0.0010764409,0.0014488412,0.0026800577],"domain_scores_gemma":[0.98948306,0.004282527,0.0034906908,0.0011472256,0.0013149417,0.00028155843],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.025130961,0.0006269113,0.0013199147,0.0005965932,0.0015910098,0.0014037829,0.0023749485,0.00046041372,0.000049681046],"category_scores_gemma":[0.0024392284,0.00042011653,0.0006842038,0.000717993,0.00060141453,0.0004196772,0.0011377617,0.00619894,0.000091924885],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014814326,0.000080570346,0.00047433403,0.000046849465,0.00024649873,0.0000033176418,0.00019244422,0.00013005245,0.00005213607,0.03509348,0.00015174664,0.96338046],"study_design_scores_gemma":[0.001574813,0.000539119,0.00041673108,0.0019039155,0.000666187,0.0009777315,0.00967793,0.0021233938,0.000091260874,0.9459572,0.0354906,0.0005811196],"about_ca_topic_score_codex":0.00024245582,"about_ca_topic_score_gemma":0.0026406033,"teacher_disagreement_score":0.9627993,"about_ca_system_score_codex":0.0018960835,"about_ca_system_score_gemma":0.012523143,"threshold_uncertainty_score":0.99982506},"labels":[],"label_agreement":null},{"id":"W7111063317","doi":"10.2139/ssrn.5873302","title":"Salience and Generalized Empirical Likelihood: An Equivalence Result","year":2025,"lang":"","type":"preprint","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Equivalence (formal languages); Salience (neuroscience); Empirical research; Calculus (dental)","score_opus":0.10357480049007324,"score_gpt":0.43331488017316927,"score_spread":0.32974007968309604,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7111063317","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9564521,0.010394072,0.023100583,0.0031411233,0.0044003306,0.00057864096,0.0001331653,0.00008124863,0.0017187754],"genre_scores_gemma":[0.92250097,0.06595195,0.0036894928,0.000926845,0.0010684528,0.00002481697,0.000015951218,0.00006650512,0.0057550063],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98037785,0.0019101612,0.0042542233,0.003476847,0.0027398898,0.0072410135],"domain_scores_gemma":[0.9906418,0.0016614457,0.002553297,0.0025781498,0.0013393107,0.0012260398],"candidate_categories":["metaresearch","metaepi_narrow","sts","scholarly_communication","open_science","research_integrity"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.030524578,0.0013156701,0.0021079874,0.0014381738,0.0018150908,0.0038266235,0.005555935,0.0012942777,0.0003845118],"category_scores_gemma":[0.003379906,0.0011065911,0.00089867826,0.0013441991,0.00086878036,0.0015322692,0.0031442144,0.012283543,0.00025428509],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006722613,0.00042372127,0.0039627077,0.000014806419,0.00014493876,0.000058530008,0.0009598,0.00081185973,0.0001437215,0.007305717,0.00055857113,0.9849434],"study_design_scores_gemma":[0.0017253641,0.0013338339,0.0009309961,0.00046407527,0.00030218714,0.002228447,0.0039518275,0.008291773,0.000054003267,0.969322,0.010099399,0.0012960944],"about_ca_topic_score_codex":0.00037702103,"about_ca_topic_score_gemma":0.0015609984,"teacher_disagreement_score":0.9836473,"about_ca_system_score_codex":0.0029024924,"about_ca_system_score_gemma":0.024961106,"threshold_uncertainty_score":0.99995947},"labels":[],"label_agreement":null},{"id":"W7116077166","doi":"10.2139/ssrn.5935973","title":"Separating Preferences from Endogenous Effort and Cognitive Noise in Observed Decisions","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Center for Interuniversity Research and Analysis on Organizations","funders":"","keywords":"Preference; Noise (video); Task (project management); Cognition; Risk aversion (psychology); Preference elicitation; Decision theory; Loss aversion; Cognitive bias","score_opus":0.20523897607501995,"score_gpt":0.3901757407236675,"score_spread":0.18493676464864756,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7116077166","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9854287,0.007319601,0.003337828,0.00018399744,0.0010746296,0.0004117776,0.00023012354,0.000030477257,0.0019828633],"genre_scores_gemma":[0.9938662,0.004405292,0.0007557075,0.000110433975,0.0002109254,0.00002957449,0.000033471366,0.000021659609,0.0005667082],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9932865,0.0004403352,0.0019676012,0.0012801683,0.0010749862,0.0019503897],"domain_scores_gemma":[0.9924483,0.0050488166,0.0011326795,0.00065770664,0.0004992436,0.00021330662],"candidate_categories":["metaepi_narrow","scholarly_communication","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00785551,0.0005136891,0.0011235031,0.00088839425,0.00042088697,0.001207669,0.0017374589,0.0005177618,0.00011194227],"category_scores_gemma":[0.0045386506,0.0004063251,0.00036038924,0.00052285247,0.00013248452,0.00034968255,0.001357867,0.0054692174,0.00007010015],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020261564,0.00014654039,0.050153635,0.0000024068593,0.00014299013,0.000043394222,0.0008290382,0.000692639,0.000052634317,0.00059242116,0.000065076885,0.9470766],"study_design_scores_gemma":[0.0008511056,0.00016639392,0.010890863,0.00063496234,0.00013874246,0.000091783506,0.004797604,0.0011245852,0.000048010294,0.9806699,0.00015816539,0.00042787867],"about_ca_topic_score_codex":0.0010446771,"about_ca_topic_score_gemma":0.01440579,"teacher_disagreement_score":0.9800775,"about_ca_system_score_codex":0.0007764071,"about_ca_system_score_gemma":0.0064668413,"threshold_uncertainty_score":0.9998389},"labels":[],"label_agreement":null},{"id":"W7124203608","doi":"10.65109/vxdr3212","title":"Preference elicitation for risky prospects","year":2010,"lang":"","type":"article","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Preference elicitation; Cumulative prospect theory; Preference; Expected utility hypothesis; Utility theory; Prospect theory; Expert elicitation; Decision theory","score_opus":0.20600924919862232,"score_gpt":0.42222833304038043,"score_spread":0.21621908384175811,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7124203608","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9499103,0.000036898044,0.024005722,0.0008498793,0.0067918203,0.0012013534,0.00009437249,0.00007852492,0.017031161],"genre_scores_gemma":[0.9599885,0.00002210636,0.029425241,0.0002586953,0.00036866023,0.00008736686,0.0000069102875,0.000029590343,0.009812957],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9958216,0.000057992893,0.0014211035,0.0012655763,0.00084246055,0.00059124245],"domain_scores_gemma":[0.99381775,0.0028366381,0.00063515134,0.0012758229,0.0011072877,0.0003273373],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00329856,0.0003501051,0.00054958626,0.0003586084,0.0006165749,0.0016437933,0.0014154038,0.0004061991,0.0043457593],"category_scores_gemma":[0.0060501755,0.00026983395,0.00032231864,0.0006043275,0.0002509787,0.0009753059,0.0002108114,0.00048311643,0.0030828957],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011259377,0.00024012475,0.0031897377,0.0000057302186,0.0000073208844,0.0000013145165,0.000371757,0.000031049654,0.0033420133,0.014515659,0.007169351,0.97101337],"study_design_scores_gemma":[0.0014530111,0.00075518095,0.017435357,0.00004845859,0.00007958548,0.000015793434,0.00089427514,0.037349608,0.0066211754,0.7775954,0.15691641,0.0008357606],"about_ca_topic_score_codex":0.00006786659,"about_ca_topic_score_gemma":0.00057678623,"teacher_disagreement_score":0.9701776,"about_ca_system_score_codex":0.00004689162,"about_ca_system_score_gemma":0.00029626657,"threshold_uncertainty_score":0.9999754},"labels":[],"label_agreement":null},{"id":"W7132945037","doi":"","title":"Looking for bias in all the right places: Incentive-driven optimism and pessimism","year":2024,"lang":"","type":"dissertation","venue":"TSpace","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Pessimism; Preference; Incentive; Optimism; Moderation; Negative information; Independence (probability theory); Empirical evidence","score_opus":0.17175842694787613,"score_gpt":0.4638478915355451,"score_spread":0.292089464587669,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7132945037","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9822691,0.003531618,0.0006079655,0.002471486,0.0046330136,0.0015328905,0.00007781009,0.000054335902,0.0048217513],"genre_scores_gemma":[0.9631869,0.0012257764,0.00253101,0.0003473736,0.0002932257,0.00020003876,0.0001247912,0.00012732252,0.031963557],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99427676,0.00031361287,0.001660002,0.0019339144,0.0010224881,0.00079320685],"domain_scores_gemma":[0.99160904,0.0058013927,0.0010270387,0.0009733634,0.0003533888,0.0002357978],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0038472463,0.0007867119,0.0011353011,0.0008621742,0.00057997444,0.0025370396,0.0016343344,0.00074070174,0.0006432597],"category_scores_gemma":[0.0014952706,0.00052387954,0.00045614352,0.00083358947,0.00031010064,0.00047330227,0.00038466157,0.0010723356,0.00036016168],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001519485,0.0005281986,0.0014544844,0.00041738487,0.00030093675,0.00031709595,0.21935426,0.0071883597,0.00067857606,0.0034998765,0.023670552,0.7410708],"study_design_scores_gemma":[0.0033991276,0.0006673048,0.0024934781,0.0057141893,0.0011154235,0.00006910201,0.18218915,0.24787103,0.0011554798,0.11008737,0.44228053,0.002957796],"about_ca_topic_score_codex":0.0003153585,"about_ca_topic_score_gemma":0.001956412,"teacher_disagreement_score":0.738113,"about_ca_system_score_codex":0.00025551685,"about_ca_system_score_gemma":0.00045450387,"threshold_uncertainty_score":0.9997213},"labels":[],"label_agreement":null},{"id":"W7134111940","doi":"10.61190/fsr.v16i2.4883","title":"savings and investment decisions of planners","year":2007,"lang":"","type":"article","venue":"Financial Services Review","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Salary; Pension plan; Pension; Propensity score matching; Marital status; Investment decisions; Investment (military)","score_opus":0.06792927124473518,"score_gpt":0.38226944721733114,"score_spread":0.31434017597259595,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7134111940","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.68716174,0.30468947,0.00039251547,0.0006469135,0.0015132747,0.0008961292,0.00015614249,0.00002281827,0.004520967],"genre_scores_gemma":[0.5937219,0.3774871,0.0076792846,0.020032987,0.00039601407,0.000023262637,0.000032573324,0.000070323564,0.00055652164],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99344355,0.00016445367,0.003425377,0.0010921307,0.0011886761,0.0006857925],"domain_scores_gemma":[0.9938332,0.0020772754,0.0017807848,0.0012170277,0.00054731255,0.00054443395],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.007704149,0.00051103265,0.0017197451,0.00040935684,0.00032732595,0.00019318792,0.0015870153,0.00033306595,0.00075256085],"category_scores_gemma":[0.0021132324,0.00041033293,0.00043438005,0.0016691402,0.00030067025,0.000584303,0.0008207651,0.00035333243,0.0005601298],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006460515,0.00016817503,0.002557369,0.00092933746,0.00001120283,0.000039507864,0.00048201982,0.0000029958799,0.000030417274,0.0014665767,0.0034140928,0.9908337],"study_design_scores_gemma":[0.0005704944,0.0004403579,0.036277246,0.02993439,0.0003264242,0.000059521684,0.00032634585,0.000085327425,0.00008443043,0.042831216,0.8883625,0.00070171943],"about_ca_topic_score_codex":0.00028566254,"about_ca_topic_score_gemma":0.0007024258,"teacher_disagreement_score":0.990132,"about_ca_system_score_codex":0.00009891557,"about_ca_system_score_gemma":0.0003233676,"threshold_uncertainty_score":0.99983484},"labels":[],"label_agreement":null},{"id":"W7135882875","doi":"","title":"Deceit behaviour","year":2010,"lang":"en","type":"book-chapter","venue":"Bristol Research (University of Bristol)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute of Infection and Immunity","funders":"","keywords":"","score_opus":0.35549755117579823,"score_gpt":0.4377643900348535,"score_spread":0.08226683885905528,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7135882875","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15747894,0.00062384986,0.00082278077,0.0013497525,0.0010777479,0.0008109242,0.00080131815,0.00011583295,0.83691883],"genre_scores_gemma":[0.15067014,0.00027572864,0.0028864683,0.00003002457,0.00015887855,4.2803347e-7,0.000056240937,0.000088681445,0.8458334],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99201494,0.00023172282,0.0008954081,0.0016129969,0.004493276,0.00075167353],"domain_scores_gemma":[0.9908108,0.0018326767,0.0010129557,0.0026589711,0.0030166756,0.00066790124],"candidate_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0068365633,0.00045428882,0.0012803086,0.0023981,0.0009202451,0.00032289658,0.0051576565,0.001248234,0.010456374],"category_scores_gemma":[0.0015086991,0.0005212417,0.0008449058,0.00045262923,0.0023900017,0.00050536054,0.0018637701,0.002845807,0.009503885],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032312577,0.00023656119,0.00086639525,0.000023141522,0.000067704204,0.0013025886,0.0005486726,0.0000049097534,0.00029694312,0.010637621,0.26920635,0.716486],"study_design_scores_gemma":[0.00044134888,0.00022209986,0.0009069824,0.00012216879,0.000062289844,0.000055884302,0.0007965959,0.000044753262,0.000025548265,0.14420815,0.8526152,0.0004990279],"about_ca_topic_score_codex":0.0013268776,"about_ca_topic_score_gemma":0.0039698984,"teacher_disagreement_score":0.71598697,"about_ca_system_score_codex":0.00048242422,"about_ca_system_score_gemma":0.0010481215,"threshold_uncertainty_score":0.9997239},"labels":[],"label_agreement":null},{"id":"W7139219557","doi":"","title":"Integrate Risk in the Timing of Outcomes","year":2025,"lang":"","type":"dissertation","venue":"TSpace (University of Toronto)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"University of Toronto","keywords":"Stochastic dominance; Expected utility hypothesis; Axiom; Outcome (game theory); Subjective expected utility; Axiom independence; Predictive power; Rank (graph theory); Isoelastic utility","score_opus":0.07715566139754573,"score_gpt":0.3672824648566934,"score_spread":0.29012680345914765,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7139219557","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9324238,0.00058167934,0.00043696113,0.0003806455,0.0010042656,0.0003824368,0.0001302154,0.000010252855,0.06464978],"genre_scores_gemma":[0.98371714,0.0011675613,0.0014542118,0.000019677169,0.000010796882,3.6330735e-7,0.000027616625,0.000010003422,0.01359265],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9965946,0.0005592016,0.00079057954,0.00075441244,0.000969661,0.00033152994],"domain_scores_gemma":[0.9935058,0.0025466029,0.0021149286,0.0012205683,0.00053283427,0.00007928319],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002977721,0.00039607415,0.0013004803,0.00041558497,0.00036605552,0.00009195633,0.0030810612,0.00046706962,0.013307789],"category_scores_gemma":[0.0010563855,0.00033449664,0.0007521129,0.0004925605,0.00024326968,0.0007694863,0.00027433052,0.00053680385,0.00006005691],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003912479,0.00027976427,0.017150292,0.00004240027,0.000077441175,0.000020185711,0.06937127,0.00017878046,0.000040291743,0.00028517016,0.0006624718,0.9115007],"study_design_scores_gemma":[0.0007536716,0.00017416783,0.54861915,0.00046705396,0.0003301401,8.3533064e-7,0.4443647,0.0026130842,0.000026982967,0.0013744375,0.00096353627,0.00031225983],"about_ca_topic_score_codex":0.31761578,"about_ca_topic_score_gemma":0.45665103,"teacher_disagreement_score":0.9111884,"about_ca_system_score_codex":0.00034945147,"about_ca_system_score_gemma":0.00047107125,"threshold_uncertainty_score":0.9999107},"labels":[],"label_agreement":null},{"id":"W7154428261","doi":"","title":"Can an informative artefact induce sustainable behaviour in the French households? The answer of a cognitive transfer experience","year":2004,"lang":"fr","type":"dissertation","venue":"Open Repository and Bibliography (University of Liège)","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"GDG Environnement","funders":"Institut National de la Recherche Agronomique; Universitaire Stichting","keywords":"Cognition; Context (archaeology); Set (abstract data type); Perception; Affect (linguistics)","score_opus":0.05063747139328725,"score_gpt":0.3199279015391101,"score_spread":0.2692904301458229,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7154428261","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.994468,0.00031434727,0.00008482599,0.00021289839,0.00027162986,0.0011289291,0.00016825483,0.000007333154,0.0033437847],"genre_scores_gemma":[0.99859744,0.00049986405,0.000096852404,0.00005786313,0.00001600912,0.0000069144876,0.000046686626,0.000011475041,0.0006668882],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9967848,0.00060794875,0.00074562,0.00064529676,0.00082901854,0.0003873339],"domain_scores_gemma":[0.9968635,0.0008559634,0.0006841281,0.0006251537,0.00082051504,0.00015078008],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0018958938,0.00036207546,0.00068984914,0.005050469,0.001231104,0.0008184225,0.002654113,0.00039510397,0.000077810204],"category_scores_gemma":[0.000007206825,0.00026643288,0.0003539196,0.012667509,0.0011841882,0.0030817746,0.00023202912,0.00060536695,0.000002049573],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00062222447,0.0010823761,0.6448995,0.00006492637,0.00009742212,0.0002921645,0.34576565,0.00006202074,0.0001955539,0.0006704821,0.0002636115,0.0059840763],"study_design_scores_gemma":[0.00063033315,0.00052177475,0.5123343,0.00036922158,0.000155892,0.000027033922,0.4841339,0.000014292553,0.00040260024,0.0011296618,0.000049847637,0.00023118056],"about_ca_topic_score_codex":0.0976038,"about_ca_topic_score_gemma":0.005633429,"teacher_disagreement_score":0.13836825,"about_ca_system_score_codex":0.000034803466,"about_ca_system_score_gemma":0.00046730862,"threshold_uncertainty_score":0.9999788},"labels":[],"label_agreement":null},{"id":"W74042481","doi":"10.2139/ssrn.2490695","title":"Half-Full or Half-Empty? A Simple Model of Decision Making Under Risk","year":2014,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Trinity College","funders":"","keywords":"Simple (philosophy); Mathematics; Philosophy","score_opus":0.07232507915644121,"score_gpt":0.3770293633081054,"score_spread":0.3047042841516642,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W74042481","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.58611035,0.00017301332,0.41273978,0.00016130762,0.0002447121,0.00007433195,0.0000064633896,0.000021072286,0.00046895127],"genre_scores_gemma":[0.9922623,0.00037214137,0.0064136493,0.00012586039,0.0001991939,0.0000028732898,0.0000011017329,0.00004440185,0.00057844864],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99384475,0.0003335278,0.0016597055,0.00065879145,0.0014954391,0.002007765],"domain_scores_gemma":[0.99457574,0.0024386186,0.0013605178,0.000936055,0.000495619,0.00019342979],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.014037651,0.0003191608,0.0007016991,0.00062962604,0.0004969366,0.00041295326,0.0016805135,0.00021658705,0.0003326659],"category_scores_gemma":[0.0038870135,0.00021170231,0.00044893654,0.00064482866,0.00012315418,0.00061257894,0.00026074576,0.0017495231,0.00027233225],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00053224113,0.00012641826,0.0010875871,0.0000011166431,0.000041079897,0.000004189914,0.0001162898,0.050379537,0.00020893704,0.017436055,0.0005719486,0.9294946],"study_design_scores_gemma":[0.0007361412,0.0005113529,0.00016688369,0.00004233889,0.0000532173,0.000411107,0.0009071759,0.12762754,0.000043185802,0.8677263,0.0015260739,0.00024867756],"about_ca_topic_score_codex":0.00007319632,"about_ca_topic_score_gemma":0.0030786467,"teacher_disagreement_score":0.92924595,"about_ca_system_score_codex":0.000636145,"about_ca_system_score_gemma":0.0019007054,"threshold_uncertainty_score":0.863297},"labels":[],"label_agreement":null},{"id":"W75541930","doi":"","title":"Minimally Restrictive Decision Support Systems","year":2014,"lang":"en","type":"article","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Normative; Decision support system; Component (thermodynamics); Risk analysis (engineering); Decision aids; Artificial intelligence; Business","score_opus":0.10593555851139856,"score_gpt":0.39234231939882025,"score_spread":0.2864067608874217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W75541930","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8479506,0.000016947273,0.034509987,0.00017617816,0.0018788168,0.0001505389,0.000009782437,0.00009121064,0.11521597],"genre_scores_gemma":[0.9858656,0.000004724886,0.0064657154,0.00025678758,0.00016662815,0.000008645101,0.0000024219587,0.000016499396,0.0072130123],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99639136,0.00016643954,0.0010967943,0.00075780874,0.0012598063,0.00032780808],"domain_scores_gemma":[0.99391174,0.0039787423,0.0003180866,0.0011125269,0.0004402115,0.00023871555],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.004476274,0.00018825688,0.00043971217,0.00042343698,0.0001743521,0.00079991,0.0011577329,0.00014810117,0.0011550087],"category_scores_gemma":[0.0047066174,0.00012410851,0.00017318477,0.0005895149,0.000074106014,0.0004308222,0.00024442124,0.00014015577,0.009240532],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006142306,0.000064594184,0.0051910994,5.666494e-7,0.0000038876965,0.000011129087,0.000069554735,0.0003924196,0.000121434765,0.0034293379,0.08911196,0.9015426],"study_design_scores_gemma":[0.00090278115,0.0007003418,0.023996562,0.00003614178,0.000023048184,0.00007313427,0.0011465921,0.024404624,0.00020744353,0.16462545,0.7833134,0.0005704553],"about_ca_topic_score_codex":0.000064084226,"about_ca_topic_score_gemma":0.000035002424,"teacher_disagreement_score":0.9009721,"about_ca_system_score_codex":0.000065719934,"about_ca_system_score_gemma":0.00008791755,"threshold_uncertainty_score":0.99975806},"labels":[],"label_agreement":null},{"id":"W803079709","doi":"10.1093/oxfordhb/9780199336746.013.7","title":"Looking Backward and Forward on Hindsight Bias","year":2015,"lang":"en","type":"book","venue":"Oxford University Press eBooks","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria; Kwantlen Polytechnic University","funders":"Canada Research Chairs","keywords":"Hindsight bias; Overconfidence effect; Debiasing; Psychology; Cognitive bias; Cognitive psychology; Futures studies; Social psychology; Cognition; Computer science; Artificial intelligence; Neuroscience","score_opus":0.1838910036281605,"score_gpt":0.3246528075504059,"score_spread":0.14076180392224538,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W803079709","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012524459,0.00006643791,0.00016284733,0.000040627692,0.00076034426,0.0003169533,0.00022669874,0.00009819331,0.9858034],"genre_scores_gemma":[0.0030354168,0.00006270056,0.0003625755,0.00013363126,0.00017481626,6.3368805e-7,0.000022096763,0.000047830094,0.9961603],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9964293,0.00016476926,0.0005499817,0.0011596718,0.0012905732,0.0004056997],"domain_scores_gemma":[0.9961957,0.0010651257,0.0006892244,0.0012098046,0.0004141187,0.0004260492],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0014220449,0.00049324235,0.0008609385,0.00070299034,0.00031370454,0.0005304391,0.0016104834,0.0006404284,0.00008255336],"category_scores_gemma":[0.00029948467,0.0004391976,0.00031671062,0.000045270142,0.00030120855,0.00027380098,0.0010605674,0.0006674415,0.000045512552],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037131942,0.000039759816,0.00007021549,0.000014216055,0.00007336329,0.00036886355,0.0005245702,0.000059322956,0.0000018163654,0.04074061,0.36626047,0.5914755],"study_design_scores_gemma":[0.0006256584,0.00018148375,0.00001649843,0.00014561134,0.00010677801,0.000015632151,0.00014252792,0.0001241492,0.000014998815,0.032322932,0.96581644,0.00048731745],"about_ca_topic_score_codex":0.000024299148,"about_ca_topic_score_gemma":0.000039605577,"teacher_disagreement_score":0.59955597,"about_ca_system_score_codex":0.00046601464,"about_ca_system_score_gemma":0.0004678351,"threshold_uncertainty_score":0.999806},"labels":[],"label_agreement":null},{"id":"W803144238","doi":"10.1111/1756-2171.12326","title":"Contracting with private rewards","year":2020,"lang":"en","type":"article","venue":"The RAND Journal of Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"Social Sciences and Humanities Research Council of Canada; Canada Research Chairs","keywords":"Moral hazard; Incentive; Microeconomics; Reservation; Principal (computer security); Private information retrieval; Balance (ability); Benchmark (surveying); Work (physics); Economics; Constraint (computer-aided design); Function (biology); Principal–agent problem; Participation constraint; Business; Computer science; Mathematics; Finance; Computer security; Engineering","score_opus":0.1875806383379456,"score_gpt":0.3555044006104599,"score_spread":0.1679237622725143,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W803144238","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9883506,0.00010617461,0.0017109119,0.007875752,0.00037379193,0.000065815926,0.000005386557,0.000005429932,0.0015061874],"genre_scores_gemma":[0.99697834,0.00008261457,0.0013365329,0.0011402561,0.0004023662,3.5822146e-7,1.3853888e-7,0.000012250245,0.0000471653],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983731,0.00008911359,0.0010220096,0.00017088931,0.00018279126,0.0001621276],"domain_scores_gemma":[0.996752,0.0013083012,0.001297154,0.00027927588,0.00019240238,0.00017084202],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032834508,0.00011536957,0.00045229084,0.00007495422,0.00014210654,0.00040770284,0.000922895,0.000044500222,0.0001535381],"category_scores_gemma":[0.0010780202,0.000057760364,0.00017880423,0.00013908715,0.0000900485,0.0004778501,0.00007205484,0.00030068305,0.000103808896],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0033076594,0.00007989551,0.009592467,0.0000033301594,0.00015879904,0.00009238964,0.0029132895,0.03754654,0.00027593697,0.0021394424,0.0055196043,0.93837065],"study_design_scores_gemma":[0.013073734,0.002715841,0.008067871,0.0001659515,0.00039074436,0.0022690762,0.0077018677,0.024570737,0.0031428244,0.3196107,0.6172136,0.001077094],"about_ca_topic_score_codex":0.0000022985453,"about_ca_topic_score_gemma":0.000007028332,"teacher_disagreement_score":0.9372935,"about_ca_system_score_codex":0.000035071746,"about_ca_system_score_gemma":0.00012323518,"threshold_uncertainty_score":0.3931488},"labels":[],"label_agreement":null},{"id":"W877610250","doi":"","title":"The Effect of Age and a Pop Out Distracter on the Attended Field of View (AFOV) With Divided Attention","year":2009,"lang":"en","type":"article","venue":"Investigative Ophthalmology & Visual Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Field (mathematics); Psychology; Gerontology; Optometry; Medicine; Mathematics","score_opus":0.09797660349281546,"score_gpt":0.4268323304460995,"score_spread":0.328855726953284,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W877610250","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99604815,0.000026340042,0.000008819199,0.002340637,0.00015518846,0.0002912485,0.000005308971,0.000006645484,0.0011176651],"genre_scores_gemma":[0.9995303,0.0000023208847,0.000106751475,0.00020948543,0.000014171432,0.000009511541,5.295932e-7,0.0000038143712,0.00012307493],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99736965,0.00046881044,0.0005493197,0.0005270128,0.0008048821,0.00028033365],"domain_scores_gemma":[0.99320906,0.005421742,0.0005454698,0.00050487474,0.0002029336,0.00011589942],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0048452746,0.00017765319,0.00037927777,0.00012295478,0.0004445966,0.00016842093,0.0010221013,0.00007040125,0.000034616605],"category_scores_gemma":[0.004670636,0.00007388052,0.0000817604,0.0006886059,0.00448413,0.00027837206,0.00015235986,0.00021704208,0.000020531763],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00078105385,0.00027279236,0.26529083,0.000011629266,0.000037322618,0.00022154782,0.0016862659,0.000029045475,0.48032615,0.0038549802,0.00040248418,0.24708591],"study_design_scores_gemma":[0.00037605493,0.0076998654,0.7694342,0.0001572194,0.000030834493,0.00010496902,0.000308858,0.00014866581,0.13194735,0.08954917,0.00005754175,0.00018523946],"about_ca_topic_score_codex":0.000026943357,"about_ca_topic_score_gemma":0.0000093704175,"teacher_disagreement_score":0.5041434,"about_ca_system_score_codex":0.000024218323,"about_ca_system_score_gemma":0.000080999205,"threshold_uncertainty_score":0.9982251},"labels":[],"label_agreement":null},{"id":"W88940488","doi":"10.1016/b978-0-12-800090-8.00002-0","title":"What Intuitions Are… and Are Not","year":2013,"lang":"en","type":"book-chapter","venue":"˜The œPsychology of learning and motivation/˜The œpsychology of learning and motivation","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":62,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Psychology; Epistemology; Cognitive science; Philosophy","score_opus":0.11877221066892774,"score_gpt":0.37859345632917035,"score_spread":0.2598212456602426,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W88940488","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.969525,0.0018845305,0.0022392683,0.0087918155,0.0012147572,0.00069924665,0.000022867376,0.00010526971,0.015517256],"genre_scores_gemma":[0.92728454,0.0030260242,0.00033327244,0.0009260226,0.00018077013,0.00003503582,0.00004857206,0.000085109124,0.06808067],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99472725,0.0008143894,0.0018529649,0.0014492653,0.00069695193,0.00045918254],"domain_scores_gemma":[0.98908675,0.00519784,0.0038511546,0.0008531054,0.00084582396,0.00016531828],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003980009,0.0006412429,0.0012482245,0.00094879227,0.0010872497,0.00032294373,0.00067598454,0.0010602216,0.000404052],"category_scores_gemma":[0.0021692554,0.00045658418,0.00024261397,0.00029375395,0.0024999592,0.000517097,0.00030686051,0.0022313222,0.00008865392],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00052850874,0.00030064225,0.22471237,0.00007965534,0.00044421788,0.000013691778,0.004141354,0.0006930425,0.001772919,0.0048602624,0.011383713,0.7510696],"study_design_scores_gemma":[0.0022479468,0.0010452896,0.6081372,0.0010243839,0.0002843197,0.00029838903,0.005658005,0.00031773103,0.000025340898,0.08293272,0.2970995,0.00092920876],"about_ca_topic_score_codex":0.000026393922,"about_ca_topic_score_gemma":0.000032702945,"teacher_disagreement_score":0.7501404,"about_ca_system_score_codex":0.000025318952,"about_ca_system_score_gemma":0.000047996702,"threshold_uncertainty_score":0.9997886},"labels":[],"label_agreement":null},{"id":"W899746788","doi":"10.3758/s13421-015-0535-1","title":"Additional evidence for a dual-strategy model of reasoning: Probabilistic reasoning is more invariant than reasoning about logical validity","year":2015,"lang":"en","type":"article","venue":"Memory & Cognition","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Counterexample; Probabilistic logic; Psychology; Deductive reasoning; Probabilistic argumentation; Reasoning system; Logical reasoning; Artificial intelligence; Cognitive psychology; Logical consequence; Computer science; Mathematics","score_opus":0.4938834877903444,"score_gpt":0.43840408084048743,"score_spread":0.05547940694985698,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W899746788","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9704787,0.00008343001,0.018079784,0.00029280098,0.0003010441,0.00081045716,0.0058942884,0.000107303356,0.0039521744],"genre_scores_gemma":[0.97824436,0.000007339912,0.019894004,0.00030306392,0.00022687121,0.00024715866,0.00054396864,0.00003097927,0.0005022706],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99551773,0.00029436377,0.0012267361,0.0010549155,0.0014541945,0.00045208103],"domain_scores_gemma":[0.99210316,0.004009543,0.00092415453,0.0006732778,0.0019406187,0.0003492372],"candidate_categories":["metaresearch","metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004863813,0.00032444342,0.00062601676,0.0002583463,0.00029793117,0.0003800758,0.00055623293,0.0002610795,0.002398909],"category_scores_gemma":[0.03565806,0.0002709817,0.0003142586,0.0004886326,0.00031068345,0.0010159537,0.00019351221,0.00028972363,0.00016803292],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004814737,0.002576393,0.0030717994,0.00021332398,0.00017987972,0.00021754326,0.0064792377,0.09023056,0.004315894,0.010311786,0.5391947,0.33839414],"study_design_scores_gemma":[0.0016795576,0.0008888495,0.0042546503,0.0022789987,0.000264898,0.00019086657,0.0026144427,0.58611673,0.0013162484,0.39823002,0.0012969356,0.0008678073],"about_ca_topic_score_codex":0.000036058078,"about_ca_topic_score_gemma":0.000034781064,"teacher_disagreement_score":0.53789777,"about_ca_system_score_codex":0.0001749003,"about_ca_system_score_gemma":0.0007607635,"threshold_uncertainty_score":0.99997425},"labels":[],"label_agreement":null},{"id":"W90283668","doi":"10.1017/s1930297500005933","title":"Decisional enhancement and autonomy: public attitudes towards overt and covert nudges","year":2013,"lang":"en","type":"article","venue":"Judgment and Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":170,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"NeuroDevNet; University of British Columbia","funders":"Canadian Institutes of Health Research; Boettcher Foundation","keywords":"Subconscious; Covert; Nudge theory; Vignette; Psychology; Social psychology; Autonomy; Context (archaeology); Cognition; Affect (linguistics); Psychological intervention; Cognitive psychology; Applied psychology","score_opus":0.11235741014067416,"score_gpt":0.3859037021502991,"score_spread":0.273546292009625,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W90283668","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97864443,0.0014513631,0.014939205,0.0015321503,0.000637672,0.00041053642,0.000013251552,0.000050104092,0.0023212899],"genre_scores_gemma":[0.96858776,0.00035545861,0.029112779,0.0013104925,0.000119355806,0.000043463315,0.0000024705519,0.000024220522,0.00044399852],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99543387,0.00008295923,0.0012285315,0.00125017,0.001483392,0.00052110973],"domain_scores_gemma":[0.9952286,0.0029864127,0.00037934387,0.00067583926,0.00033513785,0.00039469972],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0023779997,0.00040251334,0.0006672056,0.00058332435,0.0005548291,0.0031894727,0.000550809,0.00019395114,0.0019727536],"category_scores_gemma":[0.0014971669,0.0002885198,0.0001221021,0.0003738875,0.00024491365,0.0014479852,0.0012430048,0.00022574625,0.00038763855],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006342602,0.00007312254,0.027122468,0.0000034830857,0.000015667603,0.000007381139,0.00015034244,0.000007910356,0.0001563864,0.0010569126,0.006985731,0.9643572],"study_design_scores_gemma":[0.0016703637,0.00044384136,0.30726352,0.000285813,0.000038844453,0.000105183215,0.0006356158,0.011358295,0.00011984399,0.57318836,0.10398652,0.0009037973],"about_ca_topic_score_codex":0.000035843677,"about_ca_topic_score_gemma":0.0000305549,"teacher_disagreement_score":0.96345335,"about_ca_system_score_codex":0.00013577584,"about_ca_system_score_gemma":0.0001595108,"threshold_uncertainty_score":0.99995667},"labels":[],"label_agreement":null},{"id":"W996677107","doi":"10.1007/s00213-015-4029-4","title":"Genetic influences on delay discounting in smokers: examination of a priori candidates and exploration of dopamine-related haplotypes","year":2015,"lang":"en","type":"article","venue":"Psychopharmacology","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":22,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; St. Joseph’s Healthcare Hamilton","funders":"National Institute on Drug Abuse; National Institute on Alcohol Abuse and Alcoholism","keywords":"rs4680; Discounting; Impulsivity; Haplotype; Delay discounting; Addiction; Psychology; Association (psychology); Genetic association; Medicine; Allele; Single-nucleotide polymorphism; Genetics; Developmental psychology; Biology; Genotype; Neuroscience; Gene","score_opus":0.12593544063690687,"score_gpt":0.42272670838131193,"score_spread":0.29679126774440506,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W996677107","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99822783,0.0002514793,0.00013724407,0.00016023518,0.0005774641,0.00021361299,0.0000057729867,0.000010114518,0.00041623894],"genre_scores_gemma":[0.9993887,0.000060855473,0.0004085093,0.000046698693,0.000023710047,0.000018316558,0.0000017218885,0.000007588371,0.000043923326],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9981329,0.00021492106,0.00085394,0.00032760573,0.00033314855,0.000137514],"domain_scores_gemma":[0.99836916,0.0006769011,0.000506931,0.00017242598,0.00021179212,0.000062819934],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016663349,0.00010908884,0.00029678666,0.0005261371,0.000026654385,0.000035703848,0.00025140357,0.00009101933,0.000046605055],"category_scores_gemma":[0.0006162124,0.000086843225,0.000030662773,0.0004995032,0.00016528473,0.00043992302,0.00005145644,0.000101703736,0.000024650564],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004258127,0.0002619209,0.18619975,0.000008493322,0.000018261146,0.000010190114,0.004130782,0.0058865193,0.0106395185,0.00011924229,0.00027584084,0.79202366],"study_design_scores_gemma":[0.009208229,0.0024502382,0.8410816,0.00019460382,0.00012475176,0.000034833243,0.006544805,0.044270404,0.008855533,0.0832908,0.0032599058,0.00068426435],"about_ca_topic_score_codex":0.00010086049,"about_ca_topic_score_gemma":0.00010697266,"teacher_disagreement_score":0.7913394,"about_ca_system_score_codex":0.0000350197,"about_ca_system_score_gemma":0.0000476066,"threshold_uncertainty_score":0.3541364},"labels":[],"label_agreement":null}]}