{"meta":{"query_hash":"1d14961659f5","filters":{"venue":"Journal of Cognitive Engineering and Decision Making"},"cohort_total":32,"direct_labels_cover":0,"predictions_cover":32,"exported":32,"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/1d14961659f5","api":"https://metacan.xera.ac/api/v1/cohort?venue=Journal+of+Cognitive+Engineering+and+Decision+Making"},"results":[{"id":"W2002894033","doi":"10.1518/155534308x284417","title":"Situation Awareness, Mental Workload, and Trust in Automation: Viable, Empirically Supported Cognitive Engineering Constructs","year":2008,"lang":"en","type":"article","venue":"Journal of Cognitive Engineering and Decision Making","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":672,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Transport Canada","funders":"","keywords":"Operationalization; Workload; Computer science; Cognitive ergonomics; Situation awareness; Automation; Cognition; Empirical research; Knowledge management; Human–computer interaction; Cognitive science; Psychology; Data science; Human factors and ergonomics; Poison control; Engineering; Epistemology","score_opus":0.026262311589130425,"score_gpt":0.34432124287148386,"score_spread":0.3180589312823534,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2002894033","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89219314,0.0077843023,0.054795194,0.014606179,0.00012687585,0.00022848308,0.00026424494,0.000056565066,0.029944876],"genre_scores_gemma":[0.99390775,0.0006542836,0.005017,0.0001611137,0.000027145863,0.00008717482,0.000036301077,0.0000045118577,0.000104773324],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9956986,0.00203926,0.00035247588,0.00047147958,0.0011454097,0.00029279297],"domain_scores_gemma":[0.9439108,0.039777335,0.0088391,0.0020079266,0.0034215078,0.0020432984],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008321534,0.0008710394,0.0006429238,0.0034023102,0.0013543946,0.006014222,0.0011604268,0.0017896302,0.0020529013],"category_scores_gemma":[0.038574096,0.0005358543,0.0007705479,0.0023028573,0.008616977,0.008910899,0.004548186,0.0031728817,0.0001385838],"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":[0.00047270817,0.0015457472,0.31489298,0.0012228054,0.00041565945,0.00036790266,0.037418045,0.007927871,0.0014187259,0.4796425,0.0014002469,0.1532748],"study_design_scores_gemma":[0.00008577359,0.0006574501,0.3299613,0.001549888,0.00029370436,0.00040862043,0.025362507,0.035323244,0.0010655461,0.60025245,0.0047604246,0.0002790537],"about_ca_topic_score_codex":0.004937252,"about_ca_topic_score_gemma":0.004064546,"teacher_disagreement_score":0.008321534,"about_ca_system_score_codex":0.0024255028,"about_ca_system_score_gemma":0.0024866443,"threshold_uncertainty_score":0.04400903},"labels":[],"label_agreement":null},{"id":"W2009277668","doi":"10.1518/155534307x264898","title":"Development and Evaluation of an Intuitive Operational Planning Process","year":2007,"lang":"en","type":"article","venue":"Journal of Cognitive Engineering and Decision Making","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":6,"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":"Process (computing); Operational planning; Process management; Computer science; Military doctrine; Operations research; Key (lock); Set (abstract data type); Action (physics); Comprehensive planning; Land-use planning; Doctrine; Operations management; Management science; Engineering; Computer security; Land use; Business; Political science","score_opus":0.059846007774369735,"score_gpt":0.44815801145592216,"score_spread":0.38831200368155244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2009277668","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6108813,0.00012724647,0.35789892,0.00064150494,0.0000940447,0.008459847,0.00020226047,0.0010958473,0.020598982],"genre_scores_gemma":[0.50264305,0.00010689264,0.49266657,0.00010397031,0.000009119921,0.002856547,0.00022900863,0.00006817916,0.0013166954],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.97967726,0.012813909,0.00103631,0.0008373131,0.0051775095,0.00045760453],"domain_scores_gemma":[0.9302307,0.049240034,0.0030401517,0.004593378,0.011684497,0.0012113764],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.024691744,0.00074615836,0.00036895878,0.0013817726,0.00089304696,0.0027175571,0.0016441185,0.0008609031,0.0021875561],"category_scores_gemma":[0.10217409,0.00038687617,0.0003899803,0.0008069147,0.0021947098,0.0024141956,0.00271987,0.00125557,0.00022370243],"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":[0.0017103875,0.005245301,0.018949488,0.0014446006,0.00008418641,0.0005595393,0.034358326,0.05190763,0.025030669,0.05091709,0.0038168058,0.8059761],"study_design_scores_gemma":[0.00471099,0.028776223,0.080186285,0.002210899,0.0005939383,0.0015926188,0.047834102,0.5254212,0.113125995,0.07150182,0.122879855,0.0011661624],"about_ca_topic_score_codex":0.0032131027,"about_ca_topic_score_gemma":0.0035463364,"teacher_disagreement_score":0.024691744,"about_ca_system_score_codex":0.0024927324,"about_ca_system_score_gemma":0.006487535,"threshold_uncertainty_score":0.130584},"labels":[],"label_agreement":null},{"id":"W2046742742","doi":"10.1518/155534307x232848","title":"Using GOMS for Modeling Routine Tasks Within Complex Sociotechnical Systems: Connecting Macrocognitive Models to Microcognition","year":2007,"lang":"en","type":"article","venue":"Journal of Cognitive Engineering and Decision Making","topic":"Cognitive Science and Mapping","field":"Computer Science","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":"Carleton University","funders":"","keywords":"Sociotechnical system; Computer science; Task (project management); Cognitive ergonomics; Cognition; Cognitive model; Socio-cognitive; Work (physics); Systems modeling; Human–computer interaction; Complex system; Management science; Systems engineering; Artificial intelligence; Engineering; Software engineering; Poison control; Psychology; Human factors and ergonomics","score_opus":0.10379096358067728,"score_gpt":0.35358182245898306,"score_spread":0.24979085887830577,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2046742742","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.26602152,0.00017244784,0.71675026,0.00094399264,0.000033746855,0.00017593242,0.00021298832,0.00034165208,0.01534742],"genre_scores_gemma":[0.85287744,0.00012902931,0.144612,0.00006673301,0.000012482316,0.00042356297,0.00010044272,0.000053640502,0.0017246143],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993291,0.00037849686,0.00003540873,0.00010850799,0.00009251294,0.00005602232],"domain_scores_gemma":[0.99362814,0.004491194,0.0005213614,0.00079484814,0.00035904528,0.0002053893],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001682329,0.0007996103,0.00051566685,0.0013953808,0.0006495503,0.0020391014,0.0016823402,0.0010730237,0.0033766557],"category_scores_gemma":[0.009314689,0.00047782378,0.00089121424,0.0009894143,0.0020610872,0.0040881415,0.0015933871,0.0015293617,0.00032401455],"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":[0.000092618,0.00015382057,0.012519099,0.00014056504,0.00008329935,0.00016845524,0.002856101,0.6837462,0.00088161515,0.27487886,0.00046458008,0.024014832],"study_design_scores_gemma":[0.000020132438,0.000043397613,0.001464296,0.00002531201,0.000019682224,0.00003448338,0.00037160786,0.8435046,0.0002953293,0.15232755,0.0018743363,0.00001920589],"about_ca_topic_score_codex":0.01096726,"about_ca_topic_score_gemma":0.01632483,"teacher_disagreement_score":0.01096726,"about_ca_system_score_codex":0.0022971204,"about_ca_system_score_gemma":0.0013494317,"threshold_uncertainty_score":0.021806836},"labels":[],"label_agreement":null},{"id":"W2075418616","doi":"10.1518/155534309x441853","title":"Modeling SGOMS in ACT-R: Linking Macro- and Microcognition","year":2009,"lang":"en","type":"article","venue":"Journal of Cognitive Engineering and Decision Making","topic":"Cognitive Science and Mapping","field":"Computer Science","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":"Carleton University","funders":"","keywords":"Cognitive architecture; Sociotechnical system; Computer science; Cognitive science; Cognition; Architecture; Cognitive model; Macro; Selection (genetic algorithm); Software engineering; Human–computer interaction; Artificial intelligence; Psychology; Programming language","score_opus":0.014898807227578767,"score_gpt":0.2751815534824121,"score_spread":0.26028274625483333,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2075418616","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.053384185,0.00008751941,0.9258469,0.00066171,0.000031039086,0.00014679138,0.00013434759,0.0008619579,0.01884565],"genre_scores_gemma":[0.48442316,0.00010254157,0.51164776,0.0001244182,0.000013223217,0.00033552464,0.00017346047,0.00011787232,0.0030620252],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99779046,0.001458584,0.00010808498,0.00029150207,0.0002597239,0.00009155007],"domain_scores_gemma":[0.99525756,0.002742199,0.00040334475,0.0010146839,0.0003781711,0.00020406207],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029953995,0.0007082158,0.00042581823,0.0010042565,0.00069460634,0.0030266447,0.0013256334,0.001216669,0.004891534],"category_scores_gemma":[0.008338688,0.00064735505,0.0012299458,0.0006731373,0.0027740584,0.0048847008,0.002532944,0.0020051063,0.0008905003],"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":[0.00015838175,0.00015089332,0.007222714,0.00018765226,0.000111454516,0.0003510053,0.0055529457,0.20719914,0.0021591457,0.721422,0.0013262995,0.054158323],"study_design_scores_gemma":[0.00005591193,0.00007370605,0.0011647142,0.00005642321,0.00006639902,0.00014438927,0.00039584967,0.6521942,0.0020898741,0.33265597,0.0110541945,0.000048388894],"about_ca_topic_score_codex":0.0072013554,"about_ca_topic_score_gemma":0.010338183,"teacher_disagreement_score":0.0072013554,"about_ca_system_score_codex":0.0016013331,"about_ca_system_score_gemma":0.0020096458,"threshold_uncertainty_score":0.01636386},"labels":[],"label_agreement":null},{"id":"W2099372490","doi":"10.1177/1555343412446193","title":"Support Requirements for Cognitive Readiness in Complex Operations","year":2012,"lang":"en","type":"article","venue":"Journal of Cognitive Engineering and Decision Making","topic":"Complex Systems and Decision Making","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":"Université Laval; Defence Research and Development Canada","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Anticipation (artificial intelligence); Cognition; Computer science; Task (project management); Term (time); Risk analysis (engineering); Focus (optics); Knowledge management; Cognitive psychology; Process management; Management science; Psychology; Artificial intelligence; Engineering; Systems engineering","score_opus":0.19153899633747282,"score_gpt":0.44391318231428634,"score_spread":0.2523741859768135,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2099372490","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9602837,0.00021506386,0.025845762,0.00087936677,0.000019537083,0.00028035042,0.00003307895,0.00011886428,0.012324259],"genre_scores_gemma":[0.98889065,0.00006967634,0.010433221,0.00007797487,0.000005958002,0.00017874008,0.000032553282,0.000007539626,0.00030353054],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9977428,0.0010340817,0.00020980154,0.00020964112,0.0006234286,0.00018027166],"domain_scores_gemma":[0.98112625,0.013441198,0.0024040432,0.0011624439,0.0010587969,0.0008071077],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003210561,0.00036463403,0.0003246766,0.00035375243,0.00039215878,0.0017494679,0.00063458824,0.0010048968,0.0034674578],"category_scores_gemma":[0.03262559,0.00029022532,0.00030607817,0.0002489015,0.0008502095,0.0018001085,0.0013757404,0.0010483394,0.00025589904],"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":[0.0039586625,0.0056447373,0.09930589,0.0039376244,0.000340617,0.0023007826,0.018754218,0.039616503,0.20240042,0.12614638,0.00294634,0.49464795],"study_design_scores_gemma":[0.0016220034,0.017290391,0.35803506,0.0010132997,0.0009253026,0.0040791123,0.016186636,0.18795493,0.13208109,0.24333283,0.03686296,0.00061636907],"about_ca_topic_score_codex":0.00033930485,"about_ca_topic_score_gemma":0.00038766582,"teacher_disagreement_score":0.0034674578,"about_ca_system_score_codex":0.000493075,"about_ca_system_score_gemma":0.0008621234,"threshold_uncertainty_score":0.016979277},"labels":[],"label_agreement":null},{"id":"W2100987193","doi":"10.1518/155534307x255654","title":"Intelligent Adaptive Interfaces for the Control of Multiple UAVs","year":2007,"lang":"en","type":"article","venue":"Journal of Cognitive Engineering and Decision Making","topic":"Human-Automation Interaction and Safety","field":"Psychology","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":"Defence Research and Development Canada","funders":"","keywords":"Workload; Situation awareness; Workstation; Task (project management); Computer science; Control (management); Human–computer interaction; Interface (matter); Simulation; Engineering; Systems engineering; Artificial intelligence; Operating system","score_opus":0.03860555287976615,"score_gpt":0.3730407804181074,"score_spread":0.33443522753834126,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2100987193","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12954153,0.00067213515,0.85464513,0.00028346485,0.00017774152,0.00012831368,0.0000389658,0.0014133478,0.013099389],"genre_scores_gemma":[0.91861767,0.00022431015,0.07820275,0.00007586755,0.000031766198,0.00011833251,0.00004536004,0.000023570412,0.0026603357],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9998223,0.00006106384,0.000010500047,0.00002822326,0.00006338889,0.000014550482],"domain_scores_gemma":[0.9996308,0.00019868315,0.0000507175,0.00003861369,0.00006002358,0.000021088956],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033254374,0.0003468326,0.00017119455,0.00015531492,0.00020506457,0.00047255092,0.00045013017,0.00033228006,0.00239643],"category_scores_gemma":[0.0015421574,0.00011831522,0.00015819981,0.00010919201,0.00026311036,0.000540984,0.00039904568,0.00042930726,0.00025089597],"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":[0.0009994453,0.0004356433,0.0047603855,0.00045096007,0.000119191995,0.0006725148,0.0018986571,0.23886576,0.1691104,0.08408935,0.0065966346,0.49200106],"study_design_scores_gemma":[0.000092510694,0.00055214437,0.0022818786,0.00004779249,0.000058217094,0.00023623365,0.00018741253,0.95439315,0.010321684,0.015267951,0.016532626,0.000028310122],"about_ca_topic_score_codex":0.00096593215,"about_ca_topic_score_gemma":0.0010342776,"teacher_disagreement_score":0.00239643,"about_ca_system_score_codex":0.00022786594,"about_ca_system_score_gemma":0.00018601619,"threshold_uncertainty_score":0.008016884},"labels":[],"label_agreement":null},{"id":"W2103865800","doi":"10.1177/1555343414540172","title":"Comparing Cognitive Efficiency of Experienced and Inexperienced Designers in Conceptual Design Processes","year":2014,"lang":"en","type":"article","venue":"Journal of Cognitive Engineering and Decision Making","topic":"Design Education and Practice","field":"Engineering","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":"McMaster University; University of New Brunswick","funders":"","keywords":"Creativity; Cognition; Conceptual design; Quality (philosophy); Computer science; Engineering design process; Design process; Design education; Process (computing); Psychology; Human–computer interaction; Engineering; Social psychology; Work in process; Operations management","score_opus":0.03648772234528918,"score_gpt":0.306836422491104,"score_spread":0.2703487001458148,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2103865800","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9929345,0.00016922306,0.005011079,0.000016340591,0.000002656077,0.000026801288,0.00001654354,0.000015392536,0.0018074247],"genre_scores_gemma":[0.99535227,0.00012975797,0.0038690858,0.000015610709,0.0000036244667,0.000034453737,0.000059325434,0.00000780949,0.00052803115],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9928565,0.0031517434,0.0009139074,0.00081155525,0.0018225018,0.00044376843],"domain_scores_gemma":[0.95090824,0.035517577,0.0046950476,0.00392827,0.0035562064,0.0013946493],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009228442,0.00056077144,0.00052092277,0.0026977705,0.00032017098,0.0027656395,0.00054221856,0.00065269304,0.0011417217],"category_scores_gemma":[0.04731235,0.0003315513,0.00068391254,0.0008982705,0.00083322194,0.0014352787,0.0014288124,0.00043441966,0.0002400514],"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":[0.0020618006,0.0015949106,0.620039,0.00091321085,0.0011214424,0.0004626674,0.048814055,0.010365063,0.031788144,0.0020023645,0.00038288423,0.28045443],"study_design_scores_gemma":[0.00021409213,0.0025570025,0.9438522,0.00016306479,0.00038286825,0.0011248928,0.014658663,0.01648701,0.012043826,0.0049899854,0.0033172984,0.00020902144],"about_ca_topic_score_codex":0.00046195908,"about_ca_topic_score_gemma":0.00054660486,"teacher_disagreement_score":0.009228442,"about_ca_system_score_codex":0.0005363313,"about_ca_system_score_gemma":0.00047489844,"threshold_uncertainty_score":0.048805237},"labels":[],"label_agreement":null},{"id":"W2123927446","doi":"10.1177/1555343412440697","title":"Designing for Social Engagement in Online Social Networks Using Communities-of-Practice Theory and Cognitive Work Analysis","year":2012,"lang":"en","type":"article","venue":"Journal of Cognitive Engineering and Decision Making","topic":"Knowledge Management and Sharing","field":"Social 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":"Knowledge management; Usability; Online participation; Social computing; Process (computing); Social engagement; Domain (mathematical analysis); Online community; Computer science; Sociology; Public relations; World Wide Web; Social media; The Internet; Human–computer interaction; Political science; Social science","score_opus":0.08574631084439252,"score_gpt":0.39841668536762925,"score_spread":0.31267037452323676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2123927446","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.057952367,0.00038394396,0.9117627,0.0037037132,0.000069863665,0.0012307673,0.00003399478,0.0002443829,0.02461829],"genre_scores_gemma":[0.51152277,0.00030244133,0.48355234,0.0002465149,0.000022246619,0.0017553896,0.00006111269,0.00006723165,0.0024699261],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9843232,0.01208352,0.00046743278,0.0010279345,0.0015525345,0.0005453246],"domain_scores_gemma":[0.97568613,0.019619761,0.0010718395,0.0015773467,0.0010989272,0.00094602944],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.015354935,0.0010287542,0.00076185126,0.0045701275,0.005093208,0.0091377655,0.0025859813,0.002639651,0.0036487787],"category_scores_gemma":[0.01998008,0.000848869,0.00195223,0.0021149777,0.013123501,0.01185345,0.007946778,0.002569972,0.0004213196],"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":[0.00007676249,0.0009117749,0.00914059,0.0010448643,0.00020225187,0.00075625174,0.1073468,0.022306675,0.0026389072,0.7141371,0.0035279777,0.1379102],"study_design_scores_gemma":[0.00020966442,0.00026930636,0.0025148108,0.00072735955,0.00009744891,0.0005691671,0.07535028,0.09758483,0.0027368392,0.7571365,0.06268009,0.00012365352],"about_ca_topic_score_codex":0.0027081217,"about_ca_topic_score_gemma":0.003530457,"teacher_disagreement_score":0.015354935,"about_ca_system_score_codex":0.0047617983,"about_ca_system_score_gemma":0.0049183522,"threshold_uncertainty_score":0.08120561},"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":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99926573,0.000025169626,0.0002676546,0.000027193943,0.0000014596897,0.000003958108,0.00003095193,0.0000033128877,0.00037449898],"genre_scores_gemma":[0.99948573,0.000023877936,0.00029529087,0.0000085466845,0.0000026375358,0.0000036401536,0.00007245861,0.0000010895795,0.00010678248],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99964416,0.00016115238,0.000029822759,0.000045737976,0.00007363823,0.00004552795],"domain_scores_gemma":[0.985727,0.0079557095,0.0036920577,0.0011494892,0.00066044775,0.0008153147],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022541615,0.00019598819,0.0001275767,0.0007210112,0.00018450498,0.0008704379,0.00016373675,0.00030017388,0.0013967901],"category_scores_gemma":[0.015386002,0.00012265786,0.00031980002,0.0005494417,0.00034409144,0.0005580641,0.00041031544,0.0004954018,0.0002661559],"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":[0.000033349785,0.000063917105,0.993956,0.0000032216055,0.000031513395,0.000008902691,0.00018330284,0.00026770754,0.00022018712,0.00008372454,0.000037282094,0.005110843],"study_design_scores_gemma":[0.0000019999836,0.00007814687,0.9968352,0.0000030361807,0.000009067672,0.000020458436,0.0001684793,0.0022466914,0.00012694074,0.00041491122,0.00009194105,0.0000031614609],"about_ca_topic_score_codex":0.0020210096,"about_ca_topic_score_gemma":0.0030143375,"teacher_disagreement_score":0.0022541615,"about_ca_system_score_codex":0.0001996522,"about_ca_system_score_gemma":0.0002927107,"threshold_uncertainty_score":0.011921287},"labels":[],"label_agreement":null},{"id":"W2158737396","doi":"10.1177/1555343415591395","title":"Cultural Practices and Cognition in Debriefing","year":2015,"lang":"en","type":"article","venue":"Journal of Cognitive Engineering and Decision Making","topic":"Occupational Health and Safety Research","field":"Health Professions","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 Victoria","funders":"Griffith University","keywords":"Debriefing; Recall; Cognition; Psychology; Think aloud protocol; Applied psychology; Protocol analysis; Social psychology; Cognitive psychology; Computer science; Cognitive science; Human–computer interaction","score_opus":0.16996561604802332,"score_gpt":0.5254188067284895,"score_spread":0.3554531906804662,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2158737396","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8566023,0.0025065858,0.10946959,0.0029513482,0.00031183765,0.000442747,0.000047734913,0.00014479963,0.027522912],"genre_scores_gemma":[0.97768563,0.00041080997,0.020552872,0.00035159686,0.000042901007,0.00027632152,0.000023012382,0.000032733402,0.0006242658],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.9011174,0.085908286,0.0033122948,0.002320661,0.0057088444,0.0016325383],"domain_scores_gemma":[0.8652341,0.097800255,0.015631052,0.008153516,0.010398781,0.002782305],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.05107448,0.00077213155,0.0003269385,0.0018437841,0.004186929,0.0049200845,0.0012103791,0.00090669526,0.0011149729],"category_scores_gemma":[0.14966354,0.0005050814,0.0005168395,0.0010724263,0.0091325985,0.0032970416,0.0047339126,0.0026154534,0.00014299578],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000386146,0.00025356552,0.032177947,0.0006203082,0.00015787274,0.00026642537,0.8332038,0.0007415361,0.0071616047,0.020488786,0.0007706524,0.10377141],"study_design_scores_gemma":[0.00008593084,0.00060497044,0.10146316,0.0021680275,0.00014758226,0.001212037,0.7827639,0.0028822068,0.008574698,0.05187594,0.04780801,0.00041351115],"about_ca_topic_score_codex":0.0051880195,"about_ca_topic_score_gemma":0.008299102,"teacher_disagreement_score":0.05107448,"about_ca_system_score_codex":0.0048465226,"about_ca_system_score_gemma":0.0038454344,"threshold_uncertainty_score":0.27011085},"labels":[],"label_agreement":null},{"id":"W2163019878","doi":"10.1177/1555343414532813","title":"Exploring the Use of Categories in the Assessment of Airline Pilots’ Performance as a Potential Source of Examiners’ Disagreement","year":2014,"lang":"en","type":"article","venue":"Journal of Cognitive Engineering and Decision Making","topic":"Human-Automation Interaction and Safety","field":"Psychology","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 Victoria","funders":"Griffith University","keywords":"Aviation; Aviation accident; Psychology; Applied psychology; Aviation safety; Computer science; Engineering","score_opus":0.09387926552206022,"score_gpt":0.35872147579915614,"score_spread":0.2648422102770959,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2163019878","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98713857,0.0007547882,0.008643554,0.0006510157,0.00007622472,0.00013569671,0.000041745086,0.00003070836,0.0025276865],"genre_scores_gemma":[0.99578106,0.00015289454,0.0035230767,0.00015545756,0.000029853716,0.000112588335,0.00004687413,0.0000143633515,0.00018391105],"study_design_codex":"qualitative","study_design_gemma":"observational","domain_scores_codex":[0.79491204,0.14863633,0.01985055,0.0068369154,0.026957836,0.0028063557],"domain_scores_gemma":[0.45579976,0.4359058,0.036572956,0.018810425,0.049863547,0.0030475173],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.15194717,0.00056675303,0.00091922656,0.0067113508,0.0024216082,0.0046590464,0.0015865965,0.0013384025,0.00053223973],"category_scores_gemma":[0.39079177,0.0006683335,0.0009434395,0.0024140507,0.004675856,0.0025316218,0.006550982,0.0014951569,0.00017386016],"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":[0.00073542347,0.00015555846,0.43732357,0.0007272317,0.0005423381,0.0009549289,0.4864083,0.00080961565,0.0071493182,0.0027328818,0.0008480291,0.061612744],"study_design_scores_gemma":[0.00012593188,0.0010993463,0.51670176,0.0018743112,0.00038871737,0.003044285,0.43334496,0.010050268,0.009218919,0.011427627,0.0122753745,0.00044846995],"about_ca_topic_score_codex":0.0046595796,"about_ca_topic_score_gemma":0.005050386,"teacher_disagreement_score":0.15194717,"about_ca_system_score_codex":0.0022601644,"about_ca_system_score_gemma":0.00199024,"threshold_uncertainty_score":0.803583},"labels":[],"label_agreement":null},{"id":"W2163994264","doi":"10.1177/1555343412445577","title":"Team Cognitive Work Analysis","year":2012,"lang":"en","type":"article","venue":"Journal of Cognitive Engineering and Decision Making","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":53,"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 Toronto","keywords":"Sociotechnical system; Teamwork; Computer science; Task analysis; Work (physics); Domain (mathematical analysis); Task (project management); Decision support system; Knowledge management; Process management; Human–computer interaction; Management science; Engineering; Systems engineering; Artificial intelligence","score_opus":0.024705107314950948,"score_gpt":0.3721395102661025,"score_spread":0.3474344029511515,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2163994264","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13155441,0.00046556056,0.7799391,0.000858079,0.0001573499,0.0014668644,0.0024331894,0.0016000904,0.08152532],"genre_scores_gemma":[0.66961825,0.00031071418,0.31538013,0.00009679124,0.000048247206,0.0012550935,0.0022521436,0.00025447548,0.010784141],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9958424,0.0011012792,0.00027925518,0.0008419645,0.0016039143,0.0003311819],"domain_scores_gemma":[0.99026173,0.0043663983,0.0007181433,0.0013182091,0.0029482844,0.00038732204],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0039791204,0.0009973214,0.00051811995,0.009399159,0.0022391854,0.0047214716,0.0015007248,0.00061102136,0.010570239],"category_scores_gemma":[0.012730029,0.00025730507,0.0013359033,0.0049632434,0.0013079267,0.0024341226,0.0030109705,0.00086623564,0.0014125232],"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":[0.00036914198,0.00050859316,0.03444107,0.0010132424,0.00033204805,0.00040682603,0.03269162,0.023798244,0.004664292,0.21308585,0.020065598,0.66862345],"study_design_scores_gemma":[0.00017092022,0.00035795697,0.056177184,0.00064057537,0.00027572302,0.00070924644,0.048489593,0.3744243,0.011827319,0.3002937,0.20638369,0.0002497477],"about_ca_topic_score_codex":0.009643829,"about_ca_topic_score_gemma":0.005250743,"teacher_disagreement_score":0.010570239,"about_ca_system_score_codex":0.0027237944,"about_ca_system_score_gemma":0.0035482212,"threshold_uncertainty_score":0.035360932},"labels":[],"label_agreement":null},{"id":"W2314523922","doi":"10.1177/1555343416636515","title":"The ShadowBox Approach to Cognitive Skills Training","year":2016,"lang":"en","type":"article","venue":"Journal of Cognitive Engineering and Decision Making","topic":"Team Dynamics and Performance","field":"Psychology","cited_by":52,"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 British Columbia","keywords":"Cognition; Cognitive training; Cognitive skill; Psychology; Applied psychology; Computer science","score_opus":0.020586676072976876,"score_gpt":0.3131264873993531,"score_spread":0.29253981132637624,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2314523922","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.33720723,0.0011896287,0.549077,0.0016155521,0.0011256188,0.0052397978,0.0008224995,0.009226161,0.09449653],"genre_scores_gemma":[0.45302582,0.0015530312,0.46178952,0.0014527171,0.00027330572,0.007373992,0.00082469574,0.0007438709,0.07296299],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9993476,0.00019411785,0.000026726468,0.00015649466,0.00019299812,0.00008211413],"domain_scores_gemma":[0.99854004,0.0006530115,0.00008205434,0.00025548702,0.00016420223,0.00030524444],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009481826,0.00070700294,0.0003914467,0.0008626653,0.0004083231,0.0008008181,0.001334751,0.0007308139,0.032128774],"category_scores_gemma":[0.0023349603,0.0003117438,0.0005811689,0.0004263505,0.0005029843,0.0008866721,0.002334022,0.0011501039,0.0050376523],"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":[0.0015019682,0.0103048915,0.0022111428,0.00076672767,0.000052300344,0.00016930564,0.0018652292,0.0036173274,0.05242802,0.005072596,0.01788276,0.9041277],"study_design_scores_gemma":[0.0055269185,0.040192187,0.11994926,0.0021058517,0.00041492688,0.0029538726,0.00463779,0.08078552,0.114675805,0.047591366,0.58056116,0.00060539506],"about_ca_topic_score_codex":0.0013747024,"about_ca_topic_score_gemma":0.0035179781,"teacher_disagreement_score":0.032128774,"about_ca_system_score_codex":0.0005164692,"about_ca_system_score_gemma":0.0011246861,"threshold_uncertainty_score":0.10748148},"labels":[],"label_agreement":null},{"id":"W2315359425","doi":"10.1177/1555343413488391","title":"Twenty Years of Cognitive Work Analysis in Health Care","year":2013,"lang":"en","type":"article","venue":"Journal of Cognitive Engineering and Decision Making","topic":"Patient Safety and Medication Errors","field":"Health Professions","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 Toronto","funders":"Alzheimer Society","keywords":"Health care; Work (physics); Health informatics; Cognition; Context (archaeology); Informatics; Computer science; Knowledge management; Management science; Data science; Psychology; Risk analysis (engineering); Medicine; Engineering; Political science","score_opus":0.032591601099705415,"score_gpt":0.3956430049256184,"score_spread":0.36305140382591294,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2315359425","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014392442,0.7519019,0.022678336,0.16379334,0.008669032,0.00015535804,0.00016753734,0.00011896059,0.038123086],"genre_scores_gemma":[0.23986538,0.62897855,0.05017889,0.05194981,0.016699387,0.0004814983,0.00027467043,0.00019296011,0.011378868],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9846906,0.008968488,0.001112262,0.0013568973,0.0032343615,0.00063735596],"domain_scores_gemma":[0.95185286,0.03399501,0.0017485049,0.0030061346,0.0067908717,0.002606701],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.031724725,0.0015390136,0.0013585744,0.007866868,0.0037161256,0.011737214,0.0019849525,0.00402806,0.004867272],"category_scores_gemma":[0.034737047,0.00078195747,0.0011871131,0.007299605,0.020036362,0.012476444,0.009738067,0.007404801,0.00084042875],"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":[0.00020202412,0.00023621198,0.008287785,0.0037133924,0.00023608922,0.00021135935,0.02041493,0.0011775162,0.00045891505,0.2133057,0.038363922,0.7133921],"study_design_scores_gemma":[0.00004109848,0.0003623573,0.014382515,0.012497101,0.000115192655,0.00060206593,0.017495696,0.0012857002,0.0005155571,0.1969026,0.7556012,0.00019888177],"about_ca_topic_score_codex":0.010506324,"about_ca_topic_score_gemma":0.011640354,"teacher_disagreement_score":0.031724725,"about_ca_system_score_codex":0.012985761,"about_ca_system_score_gemma":0.012385447,"threshold_uncertainty_score":0.16777837},"labels":[],"label_agreement":null},{"id":"W2319833901","doi":"10.1177/1555343414555159","title":"Finding Common Ground","year":2014,"lang":"en","type":"article","venue":"Journal of Cognitive Engineering and Decision Making","topic":"Human-Automation Interaction and Safety","field":"Psychology","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 Waterloo","funders":"","keywords":"Common ground; Construct (python library); Computer science; Interpretation (philosophy); Process (computing); Cognition; Task (project management); Field (mathematics); Work (physics); Management science; Cognitive science; Engineering ethics; Psychology; Social psychology; Engineering","score_opus":0.028239342582518066,"score_gpt":0.3742108125234656,"score_spread":0.3459714699409475,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2319833901","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03436816,0.0055047707,0.1663472,0.030068317,0.0031767057,0.00072282006,0.004019249,0.0017937453,0.75399905],"genre_scores_gemma":[0.6289751,0.0054266043,0.16087206,0.008127604,0.0012385712,0.0012164131,0.01497352,0.0025124606,0.17665775],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.984726,0.0041985726,0.001329435,0.004697799,0.0033876952,0.0016604988],"domain_scores_gemma":[0.98668265,0.0039903843,0.0011508495,0.004079318,0.0030464695,0.0010503526],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00838408,0.0013325283,0.0012401526,0.009372429,0.010493566,0.016849432,0.0048368727,0.0046135844,0.10846891],"category_scores_gemma":[0.03533882,0.00094613584,0.0019547364,0.008882695,0.0106388,0.031574965,0.01916372,0.0037524637,0.02224706],"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":[0.000088380926,0.000055182085,0.0038025111,0.00045323567,0.00007401473,0.0009209249,0.019160017,0.000356283,0.00045058993,0.78189695,0.06992109,0.122820884],"study_design_scores_gemma":[0.000021556187,0.000032499152,0.0010370977,0.0007033376,0.000042319796,0.0007052061,0.020185871,0.0008844086,0.00035955873,0.39236155,0.58362687,0.000039704883],"about_ca_topic_score_codex":0.0059628747,"about_ca_topic_score_gemma":0.0066437274,"teacher_disagreement_score":0.10846891,"about_ca_system_score_codex":0.0044844532,"about_ca_system_score_gemma":0.006320187,"threshold_uncertainty_score":0.36286467},"labels":[],"label_agreement":null},{"id":"W2473322218","doi":"10.1177/1555343416657237","title":"Training Change Agents in CTA to Bring Health Care Transformation to Scale","year":2016,"lang":"en","type":"article","venue":"Journal of Cognitive Engineering and Decision Making","topic":"Health Policy Implementation Science","field":"Health Professions","cited_by":10,"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 Alberta","funders":"","keywords":"Task (project management); Transformational leadership; Scale (ratio); Health care; Medical education; Interview; Motivational interviewing; Computer science; Applied psychology; Psychology; Intervention (counseling); Nursing; Knowledge management; Process management; Medicine; Engineering; Social psychology","score_opus":0.5271666404804437,"score_gpt":0.6279348470391299,"score_spread":0.10076820655868624,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2473322218","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.49001902,0.0007116551,0.36145416,0.04220554,0.0013017766,0.017963687,0.0003806677,0.006454029,0.0795095],"genre_scores_gemma":[0.44303957,0.0006601148,0.5298639,0.003589268,0.0002835187,0.0062646554,0.0002801977,0.00024494508,0.01577381],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.98553944,0.009797769,0.00053877145,0.0010524124,0.001703352,0.0013682551],"domain_scores_gemma":[0.95178723,0.02325017,0.0031441972,0.0046280264,0.0067909285,0.010399492],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.024004914,0.0008492623,0.00046759404,0.001547981,0.003980714,0.00410403,0.002277,0.0019731272,0.0093163],"category_scores_gemma":[0.050178126,0.0010999327,0.0006226633,0.0010219943,0.0017024502,0.003183626,0.0068124207,0.004990408,0.0030379232],"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":[0.0005537034,0.015510414,0.034277968,0.0012975092,0.00009064865,0.000878754,0.13048588,0.005983568,0.014615411,0.009313804,0.0626144,0.72437793],"study_design_scores_gemma":[0.0018665071,0.009966764,0.089784466,0.002527585,0.0002519066,0.0016590871,0.10216996,0.03907264,0.024045646,0.03159701,0.6964602,0.0005981672],"about_ca_topic_score_codex":0.003930444,"about_ca_topic_score_gemma":0.014758343,"teacher_disagreement_score":0.024004914,"about_ca_system_score_codex":0.003466155,"about_ca_system_score_gemma":0.015894976,"threshold_uncertainty_score":0.1269517},"labels":[],"label_agreement":null},{"id":"W2507495592","doi":"10.1177/1555343416661889","title":"Judgment Analysis in a Dynamic Multitask Environment: Capturing Nonlinear Policies Using Decision Trees","year":2016,"lang":"en","type":"article","venue":"Journal of Cognitive Engineering and Decision Making","topic":"Multi-Criteria Decision Making","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":"Université Laval; Thales (Canada)","funders":"","keywords":"Decision tree; Computer science; Machine learning; Heuristics; Artificial intelligence; Bootstrapping (finance); Data mining; Decision tree learning; Decision support system; Incremental decision tree; Decision rule; Task (project management); Econometrics; Mathematics","score_opus":0.04999714675743787,"score_gpt":0.36857287522802185,"score_spread":0.31857572847058396,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2507495592","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20606191,0.00011136812,0.7914699,0.0002419607,0.000025414216,0.00012390656,0.0001463983,0.00047690826,0.0013421837],"genre_scores_gemma":[0.7930167,0.00007935703,0.20605052,0.000084952095,0.000015165384,0.00012298842,0.00021249136,0.000045010664,0.00037293043],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974439,0.0014387243,0.00015766844,0.0004702424,0.00035770863,0.00013181586],"domain_scores_gemma":[0.9733695,0.020877028,0.0019846822,0.001856245,0.0014054157,0.00050719676],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0059273113,0.0007152137,0.0010281189,0.0012279933,0.0006114143,0.0016130204,0.0011484846,0.0008700561,0.0010922499],"category_scores_gemma":[0.034406647,0.00036869984,0.0007626728,0.0011672137,0.0007369565,0.002966468,0.00084789656,0.0019121479,0.00037039138],"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":[0.00043988728,0.0005485614,0.02287209,0.00020773908,0.00016740146,0.00015671895,0.0012502442,0.74164265,0.004349094,0.013467054,0.0015097068,0.21338889],"study_design_scores_gemma":[0.000007885211,0.000037339338,0.0014979808,0.000010713808,0.0000073088786,0.000012351206,0.00005300976,0.9859577,0.0007225778,0.0114383,0.00024014,0.0000146496395],"about_ca_topic_score_codex":0.006685871,"about_ca_topic_score_gemma":0.0058745653,"teacher_disagreement_score":0.006685871,"about_ca_system_score_codex":0.0012678071,"about_ca_system_score_gemma":0.0015904028,"threshold_uncertainty_score":0.031346977},"labels":[],"label_agreement":null},{"id":"W2617922124","doi":"10.1177/1555343417709669","title":"Modeling Automation With Cognitive Work Analysis to Support Human-Automation Coordination","year":2017,"lang":"en","type":"article","venue":"Journal of Cognitive Engineering and Decision Making","topic":"Human-Automation Interaction and Safety","field":"Psychology","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 Waterloo","funders":"Centre for Bioengineering and Biotechnology, University of Waterloo; Natural Sciences and Engineering Research Council of Canada","keywords":"Automation; Computer science; Hierarchy; Domain (mathematical analysis); Abstraction; Human–computer interaction; Layering; Software engineering; Artificial intelligence; Engineering","score_opus":0.035439131249662845,"score_gpt":0.391931794404927,"score_spread":0.3564926631552641,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2617922124","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.052922033,0.000116498886,0.9314572,0.00053642615,0.000023055243,0.00013551043,0.00012439227,0.0004830492,0.014201839],"genre_scores_gemma":[0.564989,0.0001643883,0.43289325,0.00004749949,0.00002046902,0.00027906577,0.00015578196,0.000058011843,0.001392585],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987583,0.0006374942,0.0000860948,0.00019583174,0.00021774787,0.00010455272],"domain_scores_gemma":[0.9951297,0.0031951647,0.0005286915,0.0006264318,0.00031150944,0.00020851361],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00209707,0.0009779931,0.00038861527,0.002108876,0.001002777,0.00379606,0.0011093895,0.00080849876,0.0040596016],"category_scores_gemma":[0.007724964,0.00048058206,0.0013720373,0.0013859477,0.0021713462,0.0038255954,0.0025905839,0.0013277885,0.00047442148],"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":[0.00016923875,0.00033285652,0.013299033,0.00026393833,0.00014167208,0.00023193582,0.007229866,0.399683,0.002964293,0.48909372,0.0017744689,0.08481601],"study_design_scores_gemma":[0.000044435335,0.000073562805,0.0024387273,0.000084087675,0.000047013255,0.000060044677,0.001050423,0.73635256,0.001075571,0.24964927,0.009081456,0.000042719472],"about_ca_topic_score_codex":0.008916413,"about_ca_topic_score_gemma":0.00722187,"teacher_disagreement_score":0.008916413,"about_ca_system_score_codex":0.0018423585,"about_ca_system_score_gemma":0.0023075796,"threshold_uncertainty_score":0.017729044},"labels":[],"label_agreement":null},{"id":"W2762075223","doi":"10.1177/1555343417735398","title":"The Benefits and the Costs of Using Auditory Warning Messages in Dynamic Decision-Making Settings","year":2017,"lang":"en","type":"article","venue":"Journal of Cognitive Engineering and Decision Making","topic":"Human-Automation Interaction and Safety","field":"Psychology","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 Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Task (project management); Computer science; Notice; Cued speech; Computer security; Warning system; Work (physics); Applied psychology; Situation awareness; Cognitive psychology; Psychology; Human–computer interaction; Engineering","score_opus":0.015670505558733994,"score_gpt":0.36204533460858856,"score_spread":0.34637482904985456,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2762075223","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99350476,0.00036700736,0.0014300743,0.00055757724,0.00002366162,0.000039156334,0.00002339867,0.000022005388,0.0040323795],"genre_scores_gemma":[0.99749655,0.00015518692,0.002042177,0.00006833733,0.000019999836,0.000021449654,0.000012428796,0.0000052507216,0.00017858125],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9971746,0.0015074536,0.00025166405,0.0001523174,0.00067616714,0.00023774053],"domain_scores_gemma":[0.95926625,0.033461343,0.003560442,0.0011708497,0.0012631725,0.0012779679],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030684348,0.00053386047,0.00022105293,0.0008010738,0.00044555258,0.0014265282,0.0004390458,0.00087216974,0.0025199973],"category_scores_gemma":[0.03951025,0.0003635057,0.0003088229,0.00038152843,0.0007175985,0.0016850774,0.0010498681,0.0007159567,0.00019213387],"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":[0.011636369,0.0054765963,0.24233367,0.0013681401,0.00050225673,0.0016868388,0.0062477062,0.014424861,0.07558345,0.0052744336,0.0015298342,0.63393587],"study_design_scores_gemma":[0.00070514187,0.008527581,0.9163805,0.00037084043,0.0008857185,0.001581053,0.009701283,0.02883558,0.015366187,0.013723164,0.0036888542,0.00023412555],"about_ca_topic_score_codex":0.001446912,"about_ca_topic_score_gemma":0.0027528808,"teacher_disagreement_score":0.0030684348,"about_ca_system_score_codex":0.00062178145,"about_ca_system_score_gemma":0.00064391847,"threshold_uncertainty_score":0.016227603},"labels":[],"label_agreement":null},{"id":"W2765913378","doi":"10.1177/1555343417724975","title":"Automation and the Human Factors Race to Catch Up","year":2017,"lang":"en","type":"article","venue":"Journal of Cognitive Engineering and Decision Making","topic":"Human-Automation Interaction and Safety","field":"Psychology","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 Waterloo","funders":"","keywords":"Automation; Pace; Field (mathematics); Computer science; Race (biology); Data science; Sociology; Engineering","score_opus":0.03573835585750612,"score_gpt":0.3980936480376214,"score_spread":0.36235529218011525,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2765913378","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.020040385,0.14560404,0.0140269445,0.7335086,0.0054600174,0.000039813658,0.00011120682,0.00018589638,0.08102312],"genre_scores_gemma":[0.73239297,0.08392208,0.011117734,0.13768014,0.011503206,0.00017235156,0.00009889449,0.00025318653,0.022859434],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9905873,0.004732452,0.00027627693,0.0015193261,0.001995921,0.00088873086],"domain_scores_gemma":[0.9717557,0.021224314,0.0009991819,0.0017219144,0.0026181247,0.001680851],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.013246454,0.0008859463,0.0013323183,0.0033358876,0.0042601055,0.012261304,0.0012825088,0.007673071,0.012249487],"category_scores_gemma":[0.015591336,0.0004361321,0.0010057214,0.0022098445,0.037968155,0.020455986,0.0061685005,0.011613701,0.0017108056],"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":[0.00014024675,0.00014846414,0.0038329521,0.000429578,0.00011109052,0.00019859555,0.01409179,0.0008501152,0.0003458752,0.8151715,0.042221855,0.12245785],"study_design_scores_gemma":[0.000032867483,0.00009427542,0.0058352347,0.0007421548,0.000023462488,0.00020504248,0.007971033,0.0006096555,0.00017624999,0.7118198,0.27241436,0.00007588077],"about_ca_topic_score_codex":0.007513141,"about_ca_topic_score_gemma":0.004870654,"teacher_disagreement_score":0.013246454,"about_ca_system_score_codex":0.0046260585,"about_ca_system_score_gemma":0.0043763197,"threshold_uncertainty_score":0.07005483},"labels":[],"label_agreement":null},{"id":"W2766932986","doi":"10.1177/1555343417732856","title":"Levels of Automation in Human Factors Models for Automation Design: Why We Might Consider Throwing the Baby Out With the Bathwater","year":2017,"lang":"en","type":"article","venue":"Journal of Cognitive Engineering and Decision Making","topic":"Human-Automation Interaction and Safety","field":"Psychology","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 Toronto","funders":"Federal Aviation Administration","keywords":"Automation; Computer science; Throwing; Value (mathematics); Space (punctuation); Human–computer interaction; Data science; Engineering; Machine learning","score_opus":0.11442358140553303,"score_gpt":0.39216840463518504,"score_spread":0.277744823229652,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2766932986","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017519118,0.017414734,0.5273648,0.40336958,0.001872144,0.00012803388,0.00008267529,0.00065126125,0.031597685],"genre_scores_gemma":[0.7646258,0.007514522,0.18735963,0.030568246,0.0010068885,0.0005996234,0.00006712874,0.0004681341,0.0077901273],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9767973,0.017449042,0.0007345763,0.0015894579,0.0027434393,0.0006863375],"domain_scores_gemma":[0.9418683,0.044714775,0.0022061956,0.005361907,0.0045900904,0.0012586837],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0357419,0.0014847104,0.0015160114,0.0022247583,0.003183971,0.009353138,0.0033497089,0.005886097,0.0039007843],"category_scores_gemma":[0.06149078,0.0015497959,0.0010901531,0.0015269207,0.03534968,0.02347934,0.007466411,0.014883848,0.0020224247],"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":[0.00007080674,0.000054380453,0.0009357527,0.00024810564,0.000043685337,0.000080004706,0.010771773,0.0052287844,0.00017469768,0.95109314,0.0070146057,0.024284272],"study_design_scores_gemma":[0.000039580875,0.000051469673,0.00023752537,0.00040397682,0.000019633646,0.000046705904,0.001880383,0.0054353843,0.00016426733,0.95200765,0.039661456,0.000051849813],"about_ca_topic_score_codex":0.006668227,"about_ca_topic_score_gemma":0.007029766,"teacher_disagreement_score":0.0357419,"about_ca_system_score_codex":0.0053275106,"about_ca_system_score_gemma":0.00460749,"threshold_uncertainty_score":0.1890235},"labels":[],"label_agreement":null},{"id":"W2885852522","doi":"10.1177/1555343418789831","title":"Evidence-Based Medicine, Best Practices, Transductive Models, and Naturalistic Decision Making: Commentary on Paul R. Falzer, Naturalistic Decision Making and the Practice of Health Care","year":2018,"lang":"en","type":"article","venue":"Journal of Cognitive Engineering and Decision Making","topic":"Healthcare cost, quality, practices","field":"Health Professions","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":"McMaster University","funders":"","keywords":"Process (computing); Health care; Evidence-based medicine; Psychology; Naturalism; Quality (philosophy); Best practice; Evidence-based practice; Task (project management); MEDLINE; Management science; Computer science; Medicine; Alternative medicine; Epistemology; Political science; Management","score_opus":0.40879437433535054,"score_gpt":0.5413866205489544,"score_spread":0.13259224621360383,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2885852522","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":"methods","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":"methods","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000038934515,0.044641063,0.00019790369,0.9368275,0.017753169,0.000009099732,0.00002426896,0.0000062910876,0.0005017724],"genre_scores_gemma":[0.0023343277,0.025542822,0.0004995931,0.94094276,0.029701337,0.000090459886,0.000022094951,0.000023394856,0.0008431439],"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9761436,0.014106341,0.0019564002,0.002031477,0.0049356623,0.0008265368],"domain_scores_gemma":[0.79025763,0.18997964,0.0031240731,0.0014609124,0.012953278,0.0022244516],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.035724785,0.001716819,0.003946394,0.002879346,0.0056492193,0.0071202354,0.01151706,0.0419315,0.0041909553],"category_scores_gemma":[0.1457034,0.0010214326,0.0030079756,0.0036786085,0.028143985,0.016530069,0.0046366295,0.068309866,0.0026376545],"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":[0.000071156144,0.000015556412,0.000047438156,0.001083303,0.000040408722,0.00017113269,0.0011625986,0.0001392232,0.00002341614,0.03332871,0.9530968,0.0108201755],"study_design_scores_gemma":[0.00017207715,0.00006171079,0.00033523736,0.013360865,0.00007685703,0.0006543357,0.0024631796,0.0003664592,0.000139036,0.121270336,0.8609322,0.0001678307],"about_ca_topic_score_codex":0.032909732,"about_ca_topic_score_gemma":0.04230805,"teacher_disagreement_score":0.96427524,"about_ca_system_score_codex":0.0140089085,"about_ca_system_score_gemma":0.018550904,"threshold_uncertainty_score":0.18893301},"labels":[],"label_agreement":null},{"id":"W3178658338","doi":"10.1177/15553434211029530","title":"Ecological Design of an Augmentative and Alternative Communication Device Interface","year":2021,"lang":"en","type":"article","venue":"Journal of Cognitive Engineering and Decision Making","topic":"Assistive Technology in Communication and Mobility","field":"Health Professions","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 Toronto","funders":"Fondation Brain Canada","keywords":"Augmentative and alternative communication; Computer science; Human–computer interaction; Interface (matter); Augmentative; Process (computing); Domain (mathematical analysis); User interface; Workload; Workspace; Psychology; Artificial intelligence","score_opus":0.11108784454219943,"score_gpt":0.4709468004480844,"score_spread":0.35985895590588496,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3178658338","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4051399,0.00009964133,0.56052375,0.00047924265,0.00007029985,0.0011488686,0.00017515806,0.0017047386,0.030658364],"genre_scores_gemma":[0.72588754,0.00006371935,0.26692444,0.00008636435,0.000010870988,0.000637696,0.00008987908,0.000115489165,0.0061840634],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988912,0.00058184756,0.00005851515,0.00017137162,0.00020901034,0.00008813778],"domain_scores_gemma":[0.99895155,0.00046710818,0.000070684895,0.00012615001,0.00023240273,0.00015197946],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017182267,0.00076270883,0.00024931596,0.00092891447,0.0010984883,0.0018545425,0.001240471,0.00080706045,0.0048948447],"category_scores_gemma":[0.0038913684,0.0005067726,0.00056092057,0.00026090586,0.0013318817,0.0011810951,0.0024810042,0.00044150243,0.0009392474],"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":[0.0015542617,0.0032647878,0.044411764,0.0017646718,0.00022334214,0.0033368613,0.05484141,0.14485157,0.33265892,0.12629844,0.00457165,0.28222227],"study_design_scores_gemma":[0.0006203369,0.0050139613,0.04060721,0.0003613214,0.00041575145,0.0023909747,0.017615903,0.709641,0.060372245,0.060651004,0.10199551,0.00031475458],"about_ca_topic_score_codex":0.0027754926,"about_ca_topic_score_gemma":0.0037861124,"teacher_disagreement_score":0.0048948447,"about_ca_system_score_codex":0.00082002464,"about_ca_system_score_gemma":0.0014683309,"threshold_uncertainty_score":0.016374886},"labels":[],"label_agreement":null},{"id":"W4214934859","doi":"10.1177/15553434221078215","title":"Evaluation of an Ecological Interface Design–Driven Augmentative and Alternative Communication Interface","year":2022,"lang":"en","type":"article","venue":"Journal of Cognitive Engineering and Decision Making","topic":"Assistive Technology in Communication and Mobility","field":"Health Professions","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":"Holland Bloorview Kids Rehabilitation Hospital; University of Toronto","funders":"Fondation Brain Canada","keywords":"Augmentative and alternative communication; Interface (matter); Workload; Computer science; Human–computer interaction; Information transfer; Usability; Brain–computer interface; Multimedia; Psychology; Telecommunications","score_opus":0.15436163305566702,"score_gpt":0.4962199834657256,"score_spread":0.3418583504100586,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4214934859","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9755381,0.000164444,0.020887274,0.00005420415,0.00003524935,0.0019294764,0.00008252795,0.00014581303,0.0011630689],"genre_scores_gemma":[0.8749536,0.00028967336,0.1189047,0.00011513007,0.000034759225,0.0035472992,0.00025883227,0.00004776897,0.0018482878],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99697065,0.0016306642,0.00032341114,0.00019057907,0.00076889107,0.00011579936],"domain_scores_gemma":[0.9941374,0.0033566777,0.00033295155,0.00039355917,0.0015201265,0.0002593608],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005257295,0.0007897335,0.00040735907,0.0006483081,0.00027463396,0.00062112906,0.0007517819,0.00042911217,0.0013694154],"category_scores_gemma":[0.017369397,0.00030299075,0.00040373666,0.00026443895,0.00040969066,0.0005257274,0.0009183559,0.0003235537,0.00022752488],"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":[0.012927776,0.019806825,0.033641495,0.003609356,0.00024245094,0.0006304282,0.01194575,0.008652905,0.33290023,0.0016484385,0.0012687164,0.57272565],"study_design_scores_gemma":[0.0074214716,0.26212144,0.31767377,0.00053019036,0.0010450368,0.0036639208,0.006221644,0.097493626,0.26768962,0.0028673564,0.032754485,0.0005174341],"about_ca_topic_score_codex":0.00071249047,"about_ca_topic_score_gemma":0.0007259999,"teacher_disagreement_score":0.005257295,"about_ca_system_score_codex":0.00040814042,"about_ca_system_score_gemma":0.00087127514,"threshold_uncertainty_score":0.02780354},"labels":[],"label_agreement":null},{"id":"W4318833987","doi":"10.1177/15553434231153311","title":"Cognitive and Behavioral Impacts of Two Decision-Support Modes for Judgmental Bootstrapping","year":2023,"lang":"en","type":"article","venue":"Journal of Cognitive Engineering and Decision Making","topic":"Human-Automation Interaction and Safety","field":"Psychology","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":"Université Laval; Dalhousie University; McGill University; Thales (Canada)","funders":"Ministère de la Défense Nationale","keywords":"Mode (computer interface); Decision support system; Computer science; Workload; Shadow (psychology); Cognition; Human–computer interaction; Dwell time; Automation; Artificial intelligence; Psychology; Engineering","score_opus":0.060563090501740906,"score_gpt":0.43710689513630757,"score_spread":0.37654380463456666,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4318833987","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99645305,0.00001746678,0.0026186875,0.000042817683,0.0000094890465,0.000049356884,0.000013300223,0.00007562085,0.00072023104],"genre_scores_gemma":[0.9933234,0.000014092161,0.0062708636,0.00002906431,0.0000057478524,0.00006322804,0.00002164691,0.000016258324,0.00025560317],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9979547,0.001029501,0.00015499354,0.00026975572,0.000425665,0.00016534781],"domain_scores_gemma":[0.95442843,0.036082286,0.0023529883,0.0039221095,0.0010855466,0.0021285634],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0038045612,0.0006417968,0.0003380516,0.00047097297,0.0003168541,0.0015788662,0.0005542268,0.0007113066,0.0027741916],"category_scores_gemma":[0.045627497,0.00048458777,0.0003285943,0.00020353815,0.0008293146,0.0016193704,0.001137683,0.0009112283,0.00027380887],"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":[0.030659962,0.0137483375,0.256053,0.0009383325,0.0004269828,0.0010808822,0.046141177,0.017117951,0.21862343,0.0045182467,0.0021256711,0.40856606],"study_design_scores_gemma":[0.0028754896,0.039927874,0.6129852,0.00035463678,0.0007177099,0.0012264777,0.020707238,0.2280071,0.06995955,0.014427416,0.008099514,0.0007118191],"about_ca_topic_score_codex":0.0010587233,"about_ca_topic_score_gemma":0.0011513304,"teacher_disagreement_score":0.0038045612,"about_ca_system_score_codex":0.00047027334,"about_ca_system_score_gemma":0.0005479408,"threshold_uncertainty_score":0.02012068},"labels":[],"label_agreement":null},{"id":"W4380271342","doi":"10.1177/15553434231171484","title":"Does It MultiMatch? What Scanpath Comparison Tells us About Task Performance in Teams","year":2023,"lang":"en","type":"article","venue":"Journal of Cognitive Engineering and Decision Making","topic":"Human-Automation Interaction and Safety","field":"Psychology","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":"Carleton University","funders":"","keywords":"Teamwork; Workload; Task (project management); Computer science; Context (archaeology); Similarity (geometry); Artificial intelligence; Machine learning; Engineering","score_opus":0.020304950612855005,"score_gpt":0.3666193155963371,"score_spread":0.3463143649834821,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4380271342","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9721562,0.0010478529,0.019985225,0.0007340987,0.00008609162,0.000030793704,0.0003077387,0.0001613927,0.005490474],"genre_scores_gemma":[0.9940975,0.00025642494,0.004805342,0.00011719653,0.00005333568,0.00003127517,0.00020371462,0.000047080426,0.00038825226],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99774545,0.0008828223,0.00014523283,0.0006539546,0.00043352728,0.0001389621],"domain_scores_gemma":[0.9767209,0.013561699,0.005024219,0.002175818,0.0015676686,0.0009495587],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0037823606,0.00043455945,0.000576362,0.002960213,0.0006627366,0.0019930664,0.0005687697,0.0008242206,0.002890977],"category_scores_gemma":[0.037743017,0.0002647283,0.0005112355,0.0022173622,0.0013779143,0.004660274,0.0012656124,0.0006539807,0.0004451507],"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":[0.002311343,0.0002595039,0.6447547,0.00045605697,0.0005814856,0.0002837012,0.010436626,0.0037965209,0.008615995,0.0047581634,0.0024410775,0.32130483],"study_design_scores_gemma":[0.000041735006,0.0010490193,0.94806683,0.00017757002,0.00015031632,0.00061431795,0.0068697077,0.012050747,0.0024384523,0.02458364,0.0038299586,0.00012769389],"about_ca_topic_score_codex":0.0021361948,"about_ca_topic_score_gemma":0.0026243075,"teacher_disagreement_score":0.0037823606,"about_ca_system_score_codex":0.0005258329,"about_ca_system_score_gemma":0.0003713389,"threshold_uncertainty_score":0.02000326},"labels":[],"label_agreement":null},{"id":"W4385145728","doi":"10.1177/15553434231189375","title":"The Failure to Grasp Automation Failure","year":2023,"lang":"en","type":"article","venue":"Journal of Cognitive Engineering and Decision Making","topic":"Human-Automation Interaction and Safety","field":"Psychology","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":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Automation; GRASP; Computer science; Construct (python library); Aviation; Confusion; Risk analysis (engineering); Engineering; Software engineering; Psychology; Medicine","score_opus":0.018366482496103273,"score_gpt":0.3559266117424469,"score_spread":0.3375601292463436,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385145728","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.25519773,0.01772775,0.5005464,0.07185171,0.0011262723,0.00025587468,0.0005892977,0.00063594524,0.15206906],"genre_scores_gemma":[0.9693002,0.0037403058,0.019407857,0.0033023776,0.00029413681,0.00017664803,0.00015298754,0.000073800395,0.003551676],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99557745,0.0016123169,0.00032988505,0.0007307977,0.0012709163,0.00047857256],"domain_scores_gemma":[0.9819515,0.010472774,0.0022886891,0.002436462,0.0021111756,0.000739439],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006214595,0.0010685374,0.0008702998,0.0027882871,0.002267128,0.005344607,0.0015730492,0.004174952,0.003811759],"category_scores_gemma":[0.021356797,0.00039269074,0.0008043982,0.0017122175,0.024656402,0.014091648,0.0068141506,0.006738297,0.0008736577],"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":[0.00007121783,0.000051732834,0.012002399,0.0004053644,0.000038410566,0.0003435503,0.013560655,0.005168347,0.0009929347,0.9071486,0.0054726866,0.054744173],"study_design_scores_gemma":[0.000008684064,0.00010975682,0.008812991,0.00038299942,0.000018543733,0.00048740138,0.0053374437,0.005076677,0.00038259456,0.95184857,0.027479012,0.000055395896],"about_ca_topic_score_codex":0.0027470107,"about_ca_topic_score_gemma":0.0014291023,"teacher_disagreement_score":0.006214595,"about_ca_system_score_codex":0.0018153846,"about_ca_system_score_gemma":0.0018621384,"threshold_uncertainty_score":0.0328663},"labels":[],"label_agreement":null},{"id":"W4391484721","doi":"10.1177/15553434241230604","title":"How Are Automation Failures Characterized in the Driving Domain? Insights From a Scoping Review","year":2024,"lang":"en","type":"review","venue":"Journal of Cognitive Engineering and Decision Making","topic":"Human-Automation Interaction and Safety","field":"Psychology","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","funders":"","keywords":"Automation; Domain (mathematical analysis); Computer science; Human factors and ergonomics; Engineering; Poison control; Human–computer interaction; Systems engineering; Psychology; Medicine; Medical emergency","score_opus":0.04748859424286141,"score_gpt":0.40743432934940677,"score_spread":0.3599457351065454,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391484721","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0018862439,0.99140066,0.0012742891,0.0025906747,0.00023871103,0.00012934764,0.00021839773,0.000012483967,0.0022492723],"genre_scores_gemma":[0.020007655,0.97645265,0.0016084646,0.0010554743,0.00009514208,0.00023766352,0.00025076378,0.000010414637,0.00028175773],"study_design_codex":"design_other","study_design_gemma":"systematic_review","domain_scores_codex":[0.99281013,0.0021916009,0.0023277039,0.0006057687,0.0018067434,0.00025805074],"domain_scores_gemma":[0.922907,0.058931153,0.0061990055,0.0012218183,0.01024609,0.0004949832],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.016825782,0.00088678114,0.0019883446,0.026177077,0.0009884476,0.0045468756,0.0015317898,0.0019594466,0.0014083574],"category_scores_gemma":[0.061960932,0.00072560296,0.0023817883,0.020545188,0.0017835603,0.0060897907,0.0020322227,0.0018967973,0.00047362735],"study_design_candidate":"systematic_review","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010350242,0.00005402668,0.004717948,0.29903734,0.0011863312,0.00057925616,0.0075711966,0.0008745947,0.00084143376,0.014199353,0.012792928,0.6580421],"study_design_scores_gemma":[0.000017053406,0.00012293321,0.011656512,0.6553263,0.0038192153,0.001352095,0.008492777,0.0003941418,0.00067039893,0.0097296275,0.30832824,0.00009063109],"about_ca_topic_score_codex":0.0091862995,"about_ca_topic_score_gemma":0.019439902,"teacher_disagreement_score":0.026177077,"about_ca_system_score_codex":0.003949545,"about_ca_system_score_gemma":0.012109777,"threshold_uncertainty_score":0.08898431},"labels":[],"label_agreement":null},{"id":"W4393010663","doi":"10.1177/15553434241240553","title":"The Influence of Agent Transparency and Complexity on Situation Awareness, Mental Workload, and Task Performance","year":2024,"lang":"en","type":"article","venue":"Journal of Cognitive Engineering and Decision Making","topic":"Human-Automation Interaction and Safety","field":"Psychology","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":"Memorial University of Newfoundland","funders":"Norges Forskningsråd","keywords":"Transparency (behavior); Workload; Computer science; Task (project management); Comprehension; Human–computer interaction; Computer security; Engineering; Systems engineering","score_opus":0.03941185628199759,"score_gpt":0.36215447646162596,"score_spread":0.3227426201796284,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393010663","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99542916,0.000030098865,0.0035512804,0.00003464916,0.0000059975223,0.00003076243,0.0000128033425,0.000029207757,0.0008759332],"genre_scores_gemma":[0.9977731,0.000015229396,0.0020305465,0.000010511104,0.000003452622,0.000021766184,0.000019086174,0.0000063682523,0.00011992164],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9981369,0.0008001517,0.00013839742,0.00020605898,0.0005628353,0.00015571274],"domain_scores_gemma":[0.9681216,0.024558501,0.00349327,0.0014181068,0.0011109536,0.0012975631],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019032765,0.00043712833,0.0002327556,0.00035082985,0.00029448312,0.001306854,0.00030330778,0.00040025474,0.0011040322],"category_scores_gemma":[0.030452838,0.00032500268,0.00025975096,0.0001279462,0.0007706459,0.00090397376,0.0010409416,0.00068401714,0.000081779064],"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":[0.011452325,0.0046787667,0.3468835,0.0009405699,0.00074352784,0.0008493156,0.024235,0.032978605,0.43924496,0.002780086,0.0010385717,0.13417475],"study_design_scores_gemma":[0.00027294352,0.0059022517,0.90512687,0.00008217993,0.0003011469,0.00036402483,0.002988055,0.044547215,0.035524655,0.0034953048,0.0012053197,0.00018996629],"about_ca_topic_score_codex":0.0013880943,"about_ca_topic_score_gemma":0.001185018,"teacher_disagreement_score":0.0019032765,"about_ca_system_score_codex":0.00035827796,"about_ca_system_score_gemma":0.00043671913,"threshold_uncertainty_score":0.010065615},"labels":[],"label_agreement":null},{"id":"W4403378968","doi":"10.1177/15553434241292400","title":"Stumbling Towards a Shared Apprehension of Automation Failure","year":2024,"lang":"en","type":"article","venue":"Journal of Cognitive Engineering and Decision Making","topic":"Human-Automation Interaction and Safety","field":"Psychology","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 Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Apprehension; Automation; Computer science; Computer security; Psychology; Engineering; Human–computer interaction; Cognitive psychology","score_opus":0.02777989866861204,"score_gpt":0.3719330363808515,"score_spread":0.3441531377122395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403378968","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.088268526,0.0020799914,0.02676856,0.85020334,0.013271617,0.00010486438,0.00019425446,0.00035756966,0.018751265],"genre_scores_gemma":[0.6763943,0.0012470721,0.0066924337,0.2966341,0.010092112,0.0003090608,0.0001145279,0.00044108945,0.0080752615],"study_design_codex":"qualitative","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9499266,0.02759322,0.0038023647,0.0059592547,0.009256994,0.003461574],"domain_scores_gemma":[0.71505445,0.21909098,0.015826374,0.010009141,0.034655645,0.0053633987],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04243106,0.0012390027,0.00095530896,0.002286279,0.01250417,0.011966436,0.005118049,0.020334927,0.0037929167],"category_scores_gemma":[0.15829694,0.00074747036,0.0012955231,0.0016320639,0.025428655,0.012257516,0.0132355895,0.034937058,0.001125492],"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":[0.0003041922,0.00010054179,0.0066462876,0.0005402737,0.00013421016,0.00398119,0.50057083,0.0011560662,0.0042776153,0.26856878,0.18967204,0.024048034],"study_design_scores_gemma":[0.00004660758,0.00023330141,0.006003436,0.0014273241,0.000081090955,0.0022121812,0.38943192,0.003658899,0.0040690973,0.11135661,0.48092762,0.0005518777],"about_ca_topic_score_codex":0.004261232,"about_ca_topic_score_gemma":0.0033122166,"teacher_disagreement_score":0.04243106,"about_ca_system_score_codex":0.0061064838,"about_ca_system_score_gemma":0.00342146,"threshold_uncertainty_score":0.22439957},"labels":[],"label_agreement":null},{"id":"W4408546962","doi":"10.1177/15553434251327697","title":"Designing High-Impact Experiments for Human–Autonomy / AI Teaming","year":2025,"lang":"en","type":"article","venue":"Journal of Cognitive Engineering and Decision Making","topic":"Human-Automation Interaction and Safety","field":"Psychology","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 Calgary","funders":"Division of Information and Intelligent Systems","keywords":"Autonomy; Computer science; Psychology; Human–computer interaction; Engineering; Political science","score_opus":0.028009116458370776,"score_gpt":0.430526081579753,"score_spread":0.4025169651213822,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408546962","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.579737,0.0006179256,0.2776049,0.0030451177,0.0011167807,0.092379674,0.0007820286,0.00073929847,0.04397737],"genre_scores_gemma":[0.54068124,0.00050312723,0.34111744,0.0015574885,0.00023855595,0.112086855,0.00042094997,0.00015566798,0.003238611],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.95732003,0.032746382,0.0025890777,0.0020354253,0.0037669705,0.0015421198],"domain_scores_gemma":[0.82349753,0.13793316,0.010940544,0.013217572,0.010413299,0.0039978125],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.056277506,0.0011709443,0.0008826013,0.0010444855,0.0033080538,0.0033260535,0.0024254923,0.0023269884,0.009184942],"category_scores_gemma":[0.14055318,0.0010955272,0.0010989651,0.0009030828,0.0040416517,0.004245327,0.0037644785,0.0031477383,0.0013462937],"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":[0.034221355,0.103360586,0.07471352,0.0135310665,0.0021465651,0.0010960216,0.04044326,0.05722174,0.09527619,0.17430502,0.016205553,0.3874792],"study_design_scores_gemma":[0.022068897,0.1662101,0.10177193,0.003750765,0.0020685897,0.00056218595,0.020560171,0.069650784,0.119327255,0.35318044,0.13991098,0.0009379873],"about_ca_topic_score_codex":0.0007413324,"about_ca_topic_score_gemma":0.0010884181,"teacher_disagreement_score":0.056277506,"about_ca_system_score_codex":0.0029252684,"about_ca_system_score_gemma":0.0038199062,"threshold_uncertainty_score":0.2976274},"labels":[],"label_agreement":null},{"id":"W4415395963","doi":"10.1177/15553434251390009","title":"Situation Awareness in Fast Rescue Crafts Operators—A Simulator Study","year":2025,"lang":"en","type":"article","venue":"Journal of Cognitive Engineering and Decision Making","topic":"Human-Automation Interaction and Safety","field":"Psychology","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":"National Research Council Canada","funders":"","keywords":"Situation awareness; Task (project management); Underpinning; Human factors and ergonomics; Psychological intervention; Poison control; Guard (computer science); Confidence interval; Situational ethics","score_opus":0.022458435758367763,"score_gpt":0.39788918584090915,"score_spread":0.3754307500825414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415395963","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9998171,0.00000537517,0.00007620458,0.0000051116,7.9463763e-7,0.000005386696,0.0000066014786,8.546921e-7,0.00008258285],"genre_scores_gemma":[0.99953854,0.00001809534,0.0002127593,0.000018961131,0.000002379151,0.000012489971,0.00003038951,9.108688e-7,0.0001654672],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996182,0.00013588076,0.000021691321,0.000060544724,0.000084316875,0.00007936308],"domain_scores_gemma":[0.9970251,0.0010849771,0.00044927304,0.00020162479,0.00045645187,0.0007826212],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00092695386,0.00032921202,0.00020160993,0.00038825558,0.00039420868,0.00065244397,0.00026560837,0.00041540648,0.0011510706],"category_scores_gemma":[0.0051576165,0.00020258498,0.00022758779,0.000105751365,0.0005320561,0.00042472302,0.00048090695,0.0005954607,0.00016437938],"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":[0.0011881937,0.0062863114,0.8709355,0.00012952517,0.0001157293,0.00071750244,0.061801575,0.0022409405,0.025362141,0.000207409,0.00056065386,0.030454503],"study_design_scores_gemma":[0.00011264302,0.013105682,0.9427399,0.000042220912,0.000051830884,0.0011486203,0.030482601,0.005107479,0.0038966048,0.0004352556,0.0027579376,0.000119223936],"about_ca_topic_score_codex":0.0050768806,"about_ca_topic_score_gemma":0.007845972,"teacher_disagreement_score":0.0050768806,"about_ca_system_score_codex":0.00034800556,"about_ca_system_score_gemma":0.0005232802,"threshold_uncertainty_score":0.010094643},"labels":[],"label_agreement":null}]}