{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":2808,"total_is_capped":false,"direct_labels_cover":2,"predictions_cover":2808,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"query_hash":"5bb8aab396d8","filters":{"venue":"Journal of Vision"}},"results":[{"id":"W2103666701","doi":"10.1167/9.3.5","title":"Saliency, attention, and visual search: An information theoretic approach","year":2009,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Visual Attention and Saliency Detection","field":"Computer Science","cited_by":855,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"","keywords":"Computer science; Fixation (population genetics); Computation; Premise; Visual cortex; Coding (social sciences); Artificial intelligence; Variety (cybernetics); Computational model; Theoretical computer science; Pattern recognition (psychology); Machine learning; Neuroscience; Psychology; Algorithm; Mathematics; Biology","retraction":null,"screen_n_in":null,"score":{"opus":0.01546226723078853,"gpt":0.3087286646497342,"spread":0.2932663974189457,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009495098,0.00007767492,0.0001137239,0.0002913511,0.0001314781,0.0002807952,0.0002279032,0.00004983079,0.000005571566],"category_scores_gemma":[0.00003106688,0.00005829363,0.0000584632,0.0002904775,0.00003090209,0.003545803,0.00003704609,0.0001550928,0.000009509534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001930151,"about_ca_system_score_gemma":0.0000286309,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001330797,"about_ca_topic_score_gemma":1.147624e-7,"domain_scores_codex":[0.9988082,0.0001233336,0.0003812104,0.00009837688,0.0004639988,0.0001248754],"domain_scores_gemma":[0.9992967,0.00001313705,0.0002102158,0.0001057018,0.0002495745,0.0001247079],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00009135559,0.0006065461,0.0007008077,0.00002975754,0.00001132212,0.000007093437,0.002330884,0.0002191883,0.01635062,0.07189962,0.0003201752,0.9074326],"study_design_scores_gemma":[0.001563769,0.007647055,0.5592433,0.00009501691,0.00001989974,0.000916332,0.0008107053,0.4156634,0.001081257,0.01175467,0.0009090523,0.0002955457],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4877191,0.00002817202,0.510968,0.0004016958,0.0001546765,0.00004923148,1.399225e-7,0.00002309841,0.0006558507],"genre_scores_gemma":[0.9912237,0.00004647739,0.008405324,0.0002447435,0.00006083255,2.501792e-7,0.000001470929,0.000001981203,0.00001521946],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9071371,"threshold_uncertainty_score":0.2707714,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2135682029","doi":"10.1167/9.3.6","title":"Viewing task influences eye movement control during active scene perception","year":2009,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Gaze Tracking and Assistive Technology","field":"Computer Science","cited_by":383,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Queen's University","funders":"Army Research Office; Economic and Social Research Council; Natural Sciences and Engineering Research Council of Canada; Queen's University; National Science Foundation","keywords":"Eye movement; Fixation (population genetics); Gaze; Saccade; Memorization; Perception; Psychology; Task (project management); Cognitive psychology; Visual search; Computer science; Artificial intelligence; Computer vision","retraction":null,"screen_n_in":null,"score":{"opus":0.008832606242384205,"gpt":0.2824567411403732,"spread":0.273624134897989,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000327286,0.00008978208,0.0001852406,0.0001978555,0.000120454,0.00007213264,0.0004004219,0.00005373248,0.000005857758],"category_scores_gemma":[0.00004972141,0.00006783615,0.00008592645,0.0001725217,0.00002339122,0.000624794,0.0000348199,0.0002321733,0.000008911526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000100822,"about_ca_system_score_gemma":0.00002537869,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001903739,"about_ca_topic_score_gemma":1.8374e-7,"domain_scores_codex":[0.9990379,0.0000542547,0.0003088723,0.0001366169,0.000300281,0.0001621425],"domain_scores_gemma":[0.9992753,0.00002568041,0.0003370036,0.0001458334,0.0001616626,0.00005455244],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0000454573,0.0001320379,0.002599129,0.000004819949,0.00001854783,0.00004696828,0.0005407816,0.0003715651,0.6675196,0.0002389328,0.00005368141,0.3284285],"study_design_scores_gemma":[0.000761025,0.0006872831,0.9880974,0.0001814863,0.00000986581,0.00002871869,0.0000593918,0.002432373,0.005765656,0.001740519,0.0001525632,0.00008369362],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9218889,0.0001197186,0.07485944,0.002819099,0.0001679791,0.00004323273,3.266156e-7,0.00003889256,0.00006234066],"genre_scores_gemma":[0.9919773,0.00005390923,0.007500933,0.0003681752,0.00008472922,3.757576e-7,7.968557e-8,0.000002407132,0.0000120476],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9854983,"threshold_uncertainty_score":0.2766278,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2097295641","doi":"10.1167/9.7.4","title":"Quantifying center bias of observers in free viewing of dynamic natural scenes","year":2009,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Visual Attention and Saliency Detection","field":"Computer Science","cited_by":371,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Queen's University","funders":"National Geospatial-Intelligence Agency; National Science Foundation","keywords":"Gaze; Eye movement; Eye tracking; Computer vision; Center (category theory); Attentional bias; Computer science; Psychology; Artificial intelligence; Cognitive psychology; Cognition; Neuroscience","retraction":null,"screen_n_in":null,"score":{"opus":0.06148352305998315,"gpt":0.3514077319045291,"spread":0.2899242088445459,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006098557,0.00006052667,0.0001867802,0.0002932602,0.00002511167,0.00002330761,0.000367949,0.00003526102,0.00000318041],"category_scores_gemma":[0.00009090463,0.00004739529,0.0001344212,0.0003694324,0.0000139085,0.0006729339,0.00004653263,0.000145663,7.689009e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003937617,"about_ca_system_score_gemma":0.00002088154,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009115122,"about_ca_topic_score_gemma":0.0000118935,"domain_scores_codex":[0.9988666,0.00008138311,0.0005413522,0.00008401214,0.0003281932,0.00009841526],"domain_scores_gemma":[0.9991925,0.0000302609,0.0004552601,0.0001470416,0.0001447307,0.00003016665],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001530819,0.0008252741,0.02078103,0.0001401433,0.00002565931,0.00005489033,0.001967257,0.0007564944,0.4606974,0.001311223,0.0002807048,0.5130069],"study_design_scores_gemma":[0.00158626,0.001098802,0.9025581,0.00142937,0.000007711716,0.0001036278,0.0001497189,0.08195574,0.009605278,0.001232479,0.0001514316,0.0001214563],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9864374,0.000713431,0.01124914,0.000707944,0.0008296928,0.00003101385,3.29118e-7,0.000005784332,0.00002526923],"genre_scores_gemma":[0.9939923,0.0001196798,0.005807009,0.00005189811,0.00001487126,4.421974e-8,1.70086e-7,0.000002051708,0.00001202539],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8817771,"threshold_uncertainty_score":0.1932724,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2081356243","doi":"10.1167/2.4.5","title":"Ecological statistics of Gestalt laws for the perceptual organization of contours","year":2002,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":342,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"IBM (Canada); York University","funders":"","keywords":"Gestalt psychology; Artificial intelligence; Psychophysics; Mathematics; Perception; Tangent; Statistical inference; Pattern recognition (psychology); Statistical model; Probabilistic logic; Computer science; Statistics; Psychology; Geometry","retraction":null,"screen_n_in":null,"score":{"opus":0.07519877128620395,"gpt":0.3455833302647638,"spread":0.2703845589785599,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002994467,0.00005381817,0.0001454122,0.00004802505,0.00008874862,0.00001867865,0.0001568183,0.00005039394,0.0008989487],"category_scores_gemma":[0.001399079,0.00003176024,0.00004386366,0.0001395068,0.00008647202,0.0001031189,0.00001841128,0.00009439497,0.00000567645],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001571405,"about_ca_system_score_gemma":0.00002016487,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":6.204806e-7,"about_ca_topic_score_gemma":6.868615e-7,"domain_scores_codex":[0.9991626,0.00007367049,0.0003530077,0.00006578503,0.000268981,0.00007598116],"domain_scores_gemma":[0.9986882,0.0004507766,0.0004379847,0.00006167534,0.0003244705,0.00003689311],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004341573,0.0002677391,0.00008700532,0.00002759808,0.000002786832,0.00000203675,0.0009013648,0.0001351816,0.9766718,0.001899982,0.00436966,0.01559147],"study_design_scores_gemma":[0.007628597,0.02069092,0.09922768,0.0005145916,0.0003349501,0.0005168441,0.005562503,0.1258055,0.719483,0.009029295,0.01057701,0.0006290746],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8675165,0.00003984242,0.1310628,0.0007076164,0.0003816731,0.0001387253,0.00003321449,0.000007206718,0.0001124319],"genre_scores_gemma":[0.9965426,0.0001944502,0.002796507,0.0002081366,0.00005914306,2.90778e-7,5.801394e-7,0.000007406021,0.0001909113],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2571887,"threshold_uncertainty_score":0.9842858,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2059552065","doi":"10.1167/9.8.784","title":"Material perception: What can you see in a brief glance?","year":2010,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":315,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Categorization; Artificial intelligence; Object (grammar); Natural (archaeology); Computer science; Computer vision; Contrast (vision); Perception; Psychology; Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.01040845525275164,"gpt":0.2786809141494596,"spread":0.2682724588967079,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004797032,0.00006224122,0.0001196549,0.0001253963,0.00003778259,0.000347871,0.0004348916,0.00006377212,0.00009286736],"category_scores_gemma":[0.00003064495,0.00004715136,0.0000511654,0.0001878304,0.0000268165,0.001216723,0.00006090306,0.0002404271,0.000009226624],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003673702,"about_ca_system_score_gemma":0.00006259073,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008623118,"about_ca_topic_score_gemma":0.000007705473,"domain_scores_codex":[0.9992042,0.00003693068,0.0002908689,0.0001025004,0.0002613575,0.0001041364],"domain_scores_gemma":[0.9993985,0.00001505263,0.0001917303,0.0001901564,0.0001458619,0.00005875617],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00002896515,0.00009182348,0.0006720629,0.000008221925,0.000002293983,0.00002494526,0.0007032988,2.788118e-7,0.745779,0.0009659287,0.0008161571,0.250907],"study_design_scores_gemma":[0.001692775,0.001289248,0.7519601,0.0005224681,0.00001042547,0.001337151,0.0004226594,0.005441471,0.1861129,0.009509501,0.04122219,0.0004790853],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9336348,0.00004750771,0.05868116,0.005449608,0.001886106,0.00007286941,8.935779e-7,0.00004128156,0.0001857718],"genre_scores_gemma":[0.9804822,0.0001949679,0.01877236,0.0001675627,0.0002860135,7.475497e-7,5.098358e-7,0.000003860132,0.00009177977],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.751288,"threshold_uncertainty_score":0.3354528,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2039700032","doi":"10.1167/14.7.9","title":"Quantifying the effect of intertrial dependence on perceptual decisions","year":2014,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":257,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"","keywords":"Perception; Stimulus (psychology); Neglect; Psychology; Cognitive psychology; Statistical inference; Inference; Computer science; Statistics; Artificial intelligence; Neuroscience; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.05156910440702418,"gpt":0.3409654257390757,"spread":0.2893963213320515,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001180615,0.00008117052,0.0001770831,0.0001083603,0.000123148,0.00004135763,0.0002862172,0.00003917979,0.00002671635],"category_scores_gemma":[0.004842842,0.00003882857,0.0001629231,0.0001396131,0.00005659821,0.0001468094,0.00005462444,0.0002860973,0.00001713857],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001898652,"about_ca_system_score_gemma":0.00001046465,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002045344,"about_ca_topic_score_gemma":0.00000227756,"domain_scores_codex":[0.9985158,0.0004332699,0.0003391391,0.0001149771,0.0004965643,0.0001002052],"domain_scores_gemma":[0.9958197,0.003597555,0.0003352008,0.0001550416,0.00004700826,0.00004546713],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009146993,0.00003435777,0.0003560671,0.000004343082,0.000002360979,0.000006796062,0.0000673116,0.0004879987,0.9207642,0.0004778962,0.0003868024,0.07649716],"study_design_scores_gemma":[0.006691138,0.05089204,0.07799335,0.001775895,0.0001270091,0.0008859273,0.0001540278,0.09937723,0.7544576,0.001890493,0.005333725,0.0004215702],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958025,0.000007264792,0.00203462,0.0003889196,0.001450614,0.00007555791,8.722409e-7,0.000004405839,0.0002352919],"genre_scores_gemma":[0.9995148,0.00003039269,0.00005020943,0.0001731229,0.0002020394,3.280296e-7,9.126583e-8,0.000006761989,0.00002225491],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1663066,"threshold_uncertainty_score":0.5797684,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2152174583","doi":"10.1167/10.11.23","title":"Bayesian integration of visual and vestibular signals for heading","year":2010,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":254,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto; Toronto Rehabilitation Institute; York University","funders":"","keywords":"Vestibular system; Sensory cue; Heading (navigation); Psychology; Audiology; Sensory system; Interval (graph theory); Cognitive psychology; Mathematics; Neuroscience; Medicine; Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.04190769164654563,"gpt":0.3854733671666445,"spread":0.3435656755200989,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005013499,0.00005606267,0.000126452,0.0001205919,0.0000777437,0.00004662996,0.00006922492,0.00005455862,0.00004605684],"category_scores_gemma":[0.0006264723,0.00004169297,0.00003514165,0.0000819596,0.0000381872,0.0002656597,0.00001126182,0.0001538615,0.000001115657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005737161,"about_ca_system_score_gemma":0.00002787399,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":6.490476e-7,"about_ca_topic_score_gemma":9.691404e-7,"domain_scores_codex":[0.99936,0.00003755039,0.0002685454,0.00008245889,0.0001799009,0.00007160413],"domain_scores_gemma":[0.9994141,0.0001091989,0.0002643504,0.00003888831,0.0001062757,0.00006721575],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006484053,0.00004720078,0.0000104573,0.0000167603,6.73274e-7,0.00000105064,0.0001913645,0.000009838294,0.9706169,0.000499643,0.00007040853,0.0284709],"study_design_scores_gemma":[0.0003916169,0.001770138,0.0004515038,0.000128596,0.000009746206,0.00007616207,0.00006909425,0.02462133,0.9679769,0.004027781,0.0004214197,0.00005572876],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8606444,0.00001220931,0.1387486,0.0002326038,0.0002606436,0.00005632608,0.000001212254,0.000004851554,0.00003912788],"genre_scores_gemma":[0.9928796,0.00001580507,0.006775601,0.0001683784,0.0001060558,4.381186e-7,2.662436e-7,0.0000069141,0.00004692345],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1322352,"threshold_uncertainty_score":0.170019,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2099905961","doi":"10.1167/9.12.19","title":"Face gender and emotion expression: Are angry women more like men?","year":2009,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Evolutionary Psychology and Human Behavior","field":"Psychology","cited_by":228,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Psychology; Anger; Happiness; Facial expression; Emotion perception; Perception; Emotional expression; Expression (computer science); Face perception; Developmental psychology; Face (sociological concept); Social psychology; Communication","retraction":null,"screen_n_in":null,"score":{"opus":0.03358695994621127,"gpt":0.36589155034897,"spread":0.3323045904027587,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003271762,0.0001101898,0.0001924163,0.0001579595,0.000127339,0.00001673332,0.0001225661,0.0001679395,0.001181262],"category_scores_gemma":[0.00001129014,0.0000870197,0.00006077206,0.00006604532,0.00005492382,0.0002304166,0.00001781047,0.0003186972,0.00003910848],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004791538,"about_ca_system_score_gemma":0.000009992349,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":3.373441e-7,"about_ca_topic_score_gemma":7.254721e-8,"domain_scores_codex":[0.9990252,0.0001152289,0.0003119348,0.000165095,0.0001931028,0.0001894764],"domain_scores_gemma":[0.9992555,0.00003340097,0.0003225801,0.0001767581,0.00008219332,0.0001295631],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.002765886,0.003541961,0.06865352,0.00003137733,0.0001427118,0.001133402,0.05563611,0.00005499823,0.06948572,0.001032885,0.7534305,0.04409098],"study_design_scores_gemma":[0.001096692,0.0007567749,0.9881828,0.00005886745,0.00001866155,0.0005193171,0.004620292,0.000005006576,0.0000252675,0.001079341,0.003544995,0.00009194951],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9931985,0.001752983,0.0003211037,0.0009247996,0.0006354489,0.00007202058,0.0000026374,0.00001595346,0.003076538],"genre_scores_gemma":[0.9968487,0.00005378392,0.0002834499,0.000779988,0.0002776276,0.000001462863,0.000001523619,0.000008273246,0.00174518],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9195293,"threshold_uncertainty_score":0.9997318,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2140721493","doi":"10.1167/11.5.2","title":"Classification images: A review","year":2011,"lang":"en","type":"review","venue":"Journal of Vision","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":200,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"","keywords":"Artificial intelligence; Computer science; Pattern recognition (psychology); Principal component analysis; Observer (physics); Curse of dimensionality; Image processing; Psychophysics; Machine learning; Perception; Image (mathematics)","retraction":null,"screen_n_in":null,"score":{"opus":0.2652969467840312,"gpt":0.4665862520625875,"spread":0.2012893052785564,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008954423,0.0002244919,0.001070873,0.0002436313,0.00007999856,0.0000615047,0.0004927592,0.0001651775,0.0008917052],"category_scores_gemma":[0.0007125709,0.0001417524,0.0005611468,0.0003783987,0.00003913385,0.0002964025,0.00004344987,0.0005620556,0.0005150712],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006826539,"about_ca_system_score_gemma":0.0002178035,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":2.304118e-7,"about_ca_topic_score_gemma":3.01621e-8,"domain_scores_codex":[0.9977527,0.0004554421,0.001057688,0.0002248262,0.0003735602,0.0001357474],"domain_scores_gemma":[0.9973833,0.0001089541,0.002011992,0.0002372962,0.0001387223,0.000119767],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000003265001,0.00005952117,6.671081e-9,0.01762217,0.000002821296,0.0000112749,0.00001280832,3.883186e-9,0.0005345378,0.0001568372,0.009229726,0.972367],"study_design_scores_gemma":[0.00005889397,0.0002089603,8.261217e-7,0.1187456,0.0002506864,0.0005946547,0.000002352041,0.0000016926,0.00002476932,0.0001907841,0.8797946,0.0001262005],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[2.895008e-7,0.9969006,0.0003836825,0.00007171431,0.0005703511,0.0002116663,0.000005328231,0.00001695287,0.001839455],"genre_scores_gemma":[0.00000510321,0.998175,0.0003617184,0.0006058022,0.000195761,0.000003946529,0.000002604558,0.00003162553,0.0006184267],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9722408,"threshold_uncertainty_score":0.9763547,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2104280957","doi":"10.1167/5.9.1","title":"Accurate statistical tests for smooth classification images","year":2005,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":197,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University; Université de Montréal","funders":"","keywords":"Toolbox; Artificial intelligence; Pattern recognition (psychology); Computer science; MATLAB; Statistical hypothesis testing; Field (mathematics); Statistical analysis; Computation; Variety (cybernetics); Machine learning; Mathematics; Statistics; Algorithm","retraction":null,"screen_n_in":null,"score":{"opus":0.03938048048456388,"gpt":0.3650808678566028,"spread":0.3257003873720389,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006006595,0.00007585077,0.0001312431,0.000116871,0.00007525517,0.0001573033,0.0004396599,0.00004652654,0.00001265929],"category_scores_gemma":[0.0002663225,0.00005582856,0.00006910091,0.0001606885,0.00003238415,0.0008902541,0.00003603968,0.0001153837,0.00001644749],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006370797,"about_ca_system_score_gemma":0.00007985917,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":3.916298e-7,"about_ca_topic_score_gemma":2.02728e-7,"domain_scores_codex":[0.9990108,0.00004337352,0.0004138415,0.000127046,0.0002792053,0.0001257613],"domain_scores_gemma":[0.9986719,0.0002287938,0.0003815917,0.0001931844,0.0004444604,0.0000800401],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000435121,0.0001770263,0.00004401386,0.00001505941,0.000007369193,0.000003485376,0.0000711898,0.00000588584,0.1177074,0.02817371,0.0238886,0.8298628],"study_design_scores_gemma":[0.002037328,0.002559824,0.2158267,0.0002197112,0.00005133667,0.0002053478,0.00007237541,0.2232486,0.1947032,0.03521077,0.3253063,0.0005585114],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0008747552,0.0001355674,0.9925824,0.005857829,0.0001200714,0.0001002577,0.000004442671,0.00004321951,0.0002814065],"genre_scores_gemma":[0.6157159,0.0001008499,0.383666,0.0001835585,0.000181568,0.000003034958,0.000001563943,0.000005661715,0.0001418526],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8293042,"threshold_uncertainty_score":0.2276623,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2055084839","doi":"10.1167/8.12.3","title":"Time course and robustness of ERP object and face differences","year":2008,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":175,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"","keywords":"Stimulus (psychology); Robustness (evolution); Computer science; Psychology; Amplitude; Artificial intelligence; Audiology; Speech recognition; Pattern recognition (psychology); Cognitive psychology; Optics; Physics; Medicine; Biology","retraction":null,"screen_n_in":null,"score":{"opus":0.04201751508916945,"gpt":0.3029095249365961,"spread":0.2608920098474266,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001250922,0.00005178705,0.0001354337,0.00006335742,0.00006706802,0.00001269454,0.00004514277,0.00003469451,0.000096523],"category_scores_gemma":[0.00008860977,0.00003640372,0.000027157,0.00006379249,0.0001376501,0.000192249,0.00001624515,0.00009079668,0.000005222796],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004762222,"about_ca_system_score_gemma":0.00001975722,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001227332,"about_ca_topic_score_gemma":5.673246e-7,"domain_scores_codex":[0.9994363,0.00006941574,0.0001709171,0.00007213732,0.0001921042,0.00005909166],"domain_scores_gemma":[0.99961,0.00008619097,0.0001621345,0.00003568654,0.00004805209,0.00005794808],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001574554,0.000199481,0.004290182,0.00003428975,0.000004821048,0.00002717251,0.00106726,0.000121688,0.9648604,0.000005653133,0.0009323088,0.02829926],"study_design_scores_gemma":[0.001706878,0.001705112,0.9375033,0.0004334048,0.00003791473,0.002486497,0.0005288337,0.01667739,0.03829511,0.0001049195,0.0003203691,0.0002002904],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991854,0.0001398478,0.0001707624,0.0002396106,0.00009064771,0.00003448415,0.000002911037,0.000003698489,0.0001326737],"genre_scores_gemma":[0.9981995,0.00145147,0.0001289141,0.0000346019,0.00003394676,1.148053e-7,1.236679e-7,0.000003054654,0.0001482995],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9332131,"threshold_uncertainty_score":0.1484501,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2326233976","doi":"10.1167/16.2.7","title":"Impairing the useful field of view in natural scenes: Tunnel vision versus general interference","year":2016,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":165,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"","keywords":"Foveal; Visual field; Visual angle; Peripheral vision; Contrast (vision); Eccentricity (behavior); Fixation (population genetics); Orientation (vector space); Task (project management); Psychology; Computer vision; Communication; Computer science; Mathematics; Neuroscience; Engineering; Retinal; Social psychology; Geometry","retraction":null,"screen_n_in":null,"score":{"opus":0.06337991318993186,"gpt":0.3810307636378468,"spread":0.3176508504479149,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005612201,0.00009366281,0.0001724374,0.0001336167,0.00006329999,0.00004151515,0.0003481649,0.000053221,0.0001349293],"category_scores_gemma":[0.0006449031,0.00004416336,0.00009392957,0.0001961124,0.00004864176,0.0004196379,0.00008314107,0.0002243147,0.00001466722],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004370643,"about_ca_system_score_gemma":0.00004254178,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004199436,"about_ca_topic_score_gemma":0.000008306339,"domain_scores_codex":[0.9988046,0.0001721767,0.0004240818,0.0001311614,0.0003246178,0.000143393],"domain_scores_gemma":[0.9990494,0.0003830667,0.0003040026,0.0001304614,0.00008305136,0.0000500696],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004774553,0.00004941724,0.0001243186,0.00001452293,0.000001253716,0.000007532174,0.0002501316,0.000009622009,0.9119172,0.00008769392,0.000188897,0.086872],"study_design_scores_gemma":[0.004431553,0.005123104,0.03191414,0.003934351,0.00002089197,0.0001722814,0.0003062537,0.003631859,0.9471,0.001803099,0.001269071,0.0002934233],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9953955,0.0001433623,0.001644316,0.001540183,0.001131914,0.00004832394,6.778444e-7,0.000006841727,0.00008890929],"genre_scores_gemma":[0.9988366,0.0003611729,0.0001978372,0.0003838703,0.0001040067,3.961017e-7,4.706436e-8,0.000007023327,0.0001090374],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08657858,"threshold_uncertainty_score":0.1800929,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2058994174","doi":"10.1167/9.5.19","title":"Free viewing of dynamic stimuli by humans and monkeys","year":2009,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":161,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Queen's University","funders":"","keywords":"Gaze; Fixation (population genetics); Saccadic masking; Eye movement; Luminance; Psychology; Computer vision; Artificial intelligence; Computer science; Communication; Biology","retraction":null,"screen_n_in":null,"score":{"opus":0.04275506177764923,"gpt":0.3649889775859679,"spread":0.3222339158083187,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002023887,0.0000641349,0.0001453677,0.00008657432,0.00007658859,0.00003462588,0.0001554783,0.00003892732,0.00005826185],"category_scores_gemma":[0.0001817154,0.00004916233,0.00004407764,0.00009764657,0.00002893273,0.0002436404,0.0000207101,0.0001372312,0.000002472246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001456641,"about_ca_system_score_gemma":0.00001309868,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":6.298284e-7,"about_ca_topic_score_gemma":1.860301e-7,"domain_scores_codex":[0.9992248,0.00005164503,0.0002774133,0.000091705,0.0002704207,0.00008395447],"domain_scores_gemma":[0.9995227,0.00004055225,0.0002429263,0.00008425477,0.00004639672,0.00006317632],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002504685,0.00006605525,0.000007499791,0.000009339457,5.614796e-7,0.000004331139,0.0002663757,0.000009036728,0.95441,0.0000448686,0.0007861108,0.04437084],"study_design_scores_gemma":[0.00628586,0.01399651,0.03421041,0.001963504,0.0001056114,0.0005145089,0.0006186477,0.03346228,0.8515179,0.04927934,0.007309453,0.0007359603],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9934067,0.000217875,0.005297798,0.0006756283,0.0001205042,0.00002999344,0.000003663059,0.000007988651,0.0002399089],"genre_scores_gemma":[0.9981906,0.000298839,0.0007894429,0.0005467607,0.00002127434,5.144391e-8,1.785308e-7,0.000004751463,0.0001480322],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.102892,"threshold_uncertainty_score":0.2004782,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2075229973","doi":"10.1167/9.1.19","title":"Acceleration carries the local inversion effect in biological motion perception","year":2009,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Animal Vocal Communication and Behavior","field":"Biochemistry, Genetics and Molecular Biology","cited_by":159,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Queen's University","funders":"","keywords":"Inversion (geology); Stimulus (psychology); Perception; Physics; Artificial intelligence; Geodesy; Computer science; Computer vision; Mathematics; Geology; Psychology; Neuroscience; Cognitive psychology","retraction":null,"screen_n_in":null,"score":{"opus":0.02363468097936681,"gpt":0.3241818502284202,"spread":0.3005471692490534,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004325501,0.00005980293,0.00008028702,0.00003780774,0.00006399845,0.00001867745,0.0001351568,0.0001031683,0.00001505163],"category_scores_gemma":[0.00006016762,0.00003374763,0.00007062154,0.00006256442,0.00004426275,0.00001171779,0.0000286508,0.0001452654,0.000003844852],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002738758,"about_ca_system_score_gemma":0.00001271488,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003160984,"about_ca_topic_score_gemma":0.000005304644,"domain_scores_codex":[0.9993752,0.0001916754,0.000194291,0.00006856798,0.0001055249,0.00006475676],"domain_scores_gemma":[0.9996788,0.00001310971,0.0001058943,0.0001054867,0.00006904639,0.0000276452],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0003057447,0.00006544634,0.005635572,0.000001204097,0.000001680596,0.000001307008,0.00004871199,0.00005886622,0.8662613,0.00001785033,0.0005217867,0.1270805],"study_design_scores_gemma":[0.0006534291,0.004507145,0.9550006,0.00003649027,0.00001072836,0.00002423082,0.0002606278,0.0004575333,0.03697115,0.0001112729,0.001889582,0.00007724728],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961372,0.0002059534,0.002719676,0.0007431867,0.00005076214,0.00006745619,3.125399e-7,0.000002132762,0.00007333399],"genre_scores_gemma":[0.9991206,0.000316317,0.0001321335,0.0003156026,0.00008789933,5.799398e-7,0.00001188544,0.000002254153,0.0000127319],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.949365,"threshold_uncertainty_score":0.1376188,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2127354632","doi":"10.1167/11.8.17","title":"Examining the influence of task set on eye movements and fixations","year":2011,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Visual Attention and Saliency Detection","field":"Computer Science","cited_by":154,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"National Eye Institute; Natural Sciences and Engineering Research Council of Canada; Killam Trusts","keywords":"Saccade; Eye movement; Fixation (population genetics); Perception; Task (project management); Set (abstract data type); Cognitive psychology; Psychology; Visual search; Computer science; Communication; Computer vision; Artificial intelligence; Neuroscience","retraction":null,"screen_n_in":null,"score":{"opus":0.04713570860952518,"gpt":0.3165040751310758,"spread":0.2693683665215506,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004015166,0.00003926013,0.00006341062,0.00008801088,0.00007379347,0.00002431659,0.0002058804,0.00001812491,0.000006166597],"category_scores_gemma":[0.00005304665,0.00002358584,0.00002478124,0.0001146319,0.00002286083,0.0003566946,0.00005108322,0.00008416847,0.000003318509],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008815697,"about_ca_system_score_gemma":0.00001164799,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005735403,"about_ca_topic_score_gemma":9.808208e-7,"domain_scores_codex":[0.9993865,0.00005151294,0.0002262114,0.00006206539,0.0002213959,0.00005234845],"domain_scores_gemma":[0.9994324,0.00003369145,0.0002821942,0.000112939,0.000108319,0.00003049526],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0002366467,0.001109393,0.1091026,0.00007314797,0.0001451725,0.00004257413,0.04037533,0.003535593,0.5506254,0.01542154,0.001450048,0.2778826],"study_design_scores_gemma":[0.0002089767,0.0009399725,0.9925951,0.00008260593,0.000003793772,0.00001116325,0.0001296147,0.002028975,0.002585924,0.001197901,0.0001821974,0.00003381813],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9867758,0.00001560755,0.01267252,0.0001005764,0.0001351525,0.0000302588,3.527205e-7,0.000004391758,0.0002653363],"genre_scores_gemma":[0.9986579,0.00002266556,0.001113029,0.0001492204,0.0000133378,3.329792e-7,5.333925e-8,0.000001508021,0.00004195595],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8834925,"threshold_uncertainty_score":0.09618028,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1978077482","doi":"10.1167/9.7.7","title":"Cue dynamics underlying rapid detection of animals in natural scenes","year":2009,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":147,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Luminance; Stimulus (psychology); Sensory cue; Artificial intelligence; Discriminative model; Computer science; Computer vision; Pattern recognition (psychology); Communication; Psychology; Cognitive psychology","retraction":null,"screen_n_in":null,"score":{"opus":0.02905094115060828,"gpt":0.3078915746447309,"spread":0.2788406334941226,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003048986,0.00007623319,0.000165632,0.0002712058,0.00005007666,0.00002874714,0.0001140434,0.00004830241,0.000004584176],"category_scores_gemma":[0.0002731215,0.00005930099,0.00008657757,0.0003255072,0.0000218931,0.0003157689,0.00001086944,0.0002447887,0.00000105724],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009324279,"about_ca_system_score_gemma":0.00001808054,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000400864,"about_ca_topic_score_gemma":0.00001521088,"domain_scores_codex":[0.999016,0.00008341647,0.0003980419,0.0001093713,0.0002765508,0.0001166029],"domain_scores_gemma":[0.9993445,0.0001100563,0.0003696811,0.00007185728,0.00006974497,0.00003422147],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001540724,0.00005149188,0.0001156098,0.000005915154,7.614428e-7,0.00001594221,0.00002360321,0.0002739932,0.8659224,0.0002162835,0.000004731191,0.1332152],"study_design_scores_gemma":[0.001490339,0.003999535,0.3222846,0.0003698232,0.00001649025,0.000512848,0.0001464289,0.2362878,0.4283502,0.006178309,0.0001424524,0.0002211982],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977439,0.0001558782,0.000847958,0.0004796274,0.000590199,0.00005734952,8.343688e-7,0.000006429327,0.0001177935],"genre_scores_gemma":[0.9995408,0.0001369985,0.0001387544,0.0001146433,0.00004625441,9.992791e-8,1.693884e-7,0.000005196134,0.00001705622],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4375722,"threshold_uncertainty_score":0.2418224,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2006040313","doi":"10.1167/8.16.13","title":"Visuospatial experience modulates attentional capture: Evidence from action video game players","year":2008,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Visual Attention and Saliency Detection","field":"Computer Science","cited_by":146,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Video game; Action (physics); Salient; Sensory system; Psychology; Task (project management); Sensory processing; Cognitive psychology; Visual processing; Cognition; Neuroscience; Computer science; Perception; Multimedia; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.05426943003164054,"gpt":0.3362703297571115,"spread":0.282000899725471,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003045086,0.0001454506,0.0002072405,0.0002077589,0.0002175009,0.0001144254,0.0005377531,0.0000941624,0.0001021548],"category_scores_gemma":[0.0001534149,0.0001193929,0.0002083001,0.0003475708,0.00006603567,0.002658266,0.00009895708,0.000272515,0.00005508586],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001165288,"about_ca_system_score_gemma":0.00008160381,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001019602,"about_ca_topic_score_gemma":0.000008128628,"domain_scores_codex":[0.99791,0.0001250659,0.0005624566,0.0002815678,0.0009355196,0.0001853828],"domain_scores_gemma":[0.9986426,0.0001227726,0.0005185675,0.0002356826,0.0003283204,0.0001520425],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0004540046,0.0005944159,0.01963434,0.00002018854,0.00008253998,0.0003174735,0.008687912,0.005812287,0.9014871,0.000419797,0.004197072,0.05829293],"study_design_scores_gemma":[0.001201209,0.001098696,0.781678,0.0004507092,0.00002243472,0.001085898,0.0002711574,0.1800988,0.03125975,0.001056381,0.001384367,0.000392612],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.636618,0.0001994651,0.3613838,0.0003805552,0.001330419,0.00004325496,6.245192e-7,0.00003020986,0.00001365454],"genre_scores_gemma":[0.992896,0.000259333,0.006261395,0.0001531993,0.0003058644,0.000002052056,0.000001074342,0.00000739954,0.0001136805],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8702273,"threshold_uncertainty_score":0.4868702,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2047262762","doi":"10.1167/9.5.8","title":"Characterizing global and local mechanisms in biological motion perception","year":2009,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":145,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Queen's University","funders":"","keywords":"Biological motion; Task (project management); Motion (physics); Perception; Computer science; Masking (illustration); Artificial intelligence; Contrast (vision); Process (computing); Motion perception; Psychophysics; Computer vision; Communication; Psychology; Neuroscience; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.051125185904195,"gpt":0.348226441005581,"spread":0.297101255101386,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004232145,0.00008544484,0.0001480336,0.00009591506,0.00006903752,0.00006287537,0.00008689826,0.00009742372,0.00006542649],"category_scores_gemma":[0.0001117278,0.00006313945,0.00004259323,0.000171395,0.00003180956,0.0003734739,0.00001776945,0.0001725358,0.00001379321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007903628,"about_ca_system_score_gemma":0.00001286286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":8.741909e-7,"about_ca_topic_score_gemma":4.000674e-7,"domain_scores_codex":[0.9990734,0.0001265202,0.0002958632,0.0001507045,0.0002232056,0.0001302873],"domain_scores_gemma":[0.9996566,0.00001878918,0.0001666883,0.00004477398,0.00003332289,0.00007984406],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0000815333,0.00007517369,0.00003798855,0.000002277845,1.728066e-7,0.0000154916,0.0001000685,0.000006723656,0.783893,0.0009442993,0.000006501519,0.2148368],"study_design_scores_gemma":[0.002788758,0.007568075,0.7611024,0.0006091892,0.00001451772,0.001982872,0.001065049,0.01673818,0.09211814,0.1152506,0.0003083216,0.0004537969],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9217392,0.00001550247,0.07714237,0.0007507459,0.0001820305,0.00004274889,9.34087e-7,0.00001414995,0.0001122831],"genre_scores_gemma":[0.9970051,0.000167068,0.001319154,0.001434962,0.00006275096,1.836759e-7,5.023194e-7,0.000002735315,0.000007530758],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7610645,"threshold_uncertainty_score":0.2574752,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2126226185","doi":"10.1167/8.12.8","title":"Maximum differentiation (MAD) competition: A methodology for comparing computational models of perceptual quantities","year":2008,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":144,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"Howard Hughes Medical Institute","keywords":"Stimulus (psychology); Perception; Computational model; Computer science; Strengths and weaknesses; Artificial intelligence; Set (abstract data type); Pattern recognition (psychology); Machine learning; Cognitive psychology; Psychology; Neuroscience; Social psychology","retraction":null,"screen_n_in":null,"score":{"opus":0.3043467223196251,"gpt":0.4031572376372731,"spread":0.098810515317648,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000406293,0.00009167167,0.000306087,0.0002027127,0.0002004237,0.00002167128,0.0001424016,0.00006024108,0.000104154],"category_scores_gemma":[0.0001718705,0.00007782094,0.0001374897,0.0001061672,0.0001130237,0.0003690847,0.00002725037,0.0001282422,0.000003939713],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002804142,"about_ca_system_score_gemma":0.00005839707,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001805425,"about_ca_topic_score_gemma":8.635453e-7,"domain_scores_codex":[0.9986448,0.0002276861,0.0005126157,0.0001249655,0.0003764053,0.000113471],"domain_scores_gemma":[0.99871,0.0004221702,0.0004805799,0.00005779615,0.0002757182,0.0000536957],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007537927,0.0004352086,0.0002132772,0.0001314957,0.00001418148,0.000007460045,0.004609356,0.04971834,0.8939427,0.0469559,0.0005115298,0.002706732],"study_design_scores_gemma":[0.00390665,0.002887583,0.01716269,0.0003512395,0.00006030943,0.001045431,0.001396026,0.6974193,0.06088175,0.2143363,0.0002294903,0.0003232888],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5350815,0.00001871661,0.4643945,0.0001153357,0.0002355733,0.00004966106,0.000004116171,0.000008160681,0.0000924532],"genre_scores_gemma":[0.9617785,0.00005329811,0.03782967,0.0001737807,0.00009375559,0.000001245617,0.00000500073,0.000009751942,0.00005497714],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.833061,"threshold_uncertainty_score":0.3173446,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2082917491","doi":"10.1167/7.9.950","title":"Attention based on information maximization","year":2010,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Visual Attention and Saliency Detection","field":"Computer Science","cited_by":141,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"","keywords":"Computer science; Maximization; Visual search; Heuristic; Variety (cybernetics); Generalization; Artificial intelligence; Focus (optics); Component (thermodynamics); Relation (database); Cognitive science; Machine learning; Psychology; Epistemology; Social psychology; Data mining","retraction":null,"screen_n_in":null,"score":{"opus":0.007926862384832199,"gpt":0.2732211379401892,"spread":0.265294275555357,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005439171,0.00005974838,0.00007443364,0.0003444505,0.00008581758,0.0001612901,0.0002245038,0.00005918522,0.0000315148],"category_scores_gemma":[0.000101142,0.00004663521,0.00008499433,0.0002730435,0.00000978898,0.001930772,0.00001861619,0.000216706,0.00006942818],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002332697,"about_ca_system_score_gemma":0.00003328767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":9.800153e-7,"about_ca_topic_score_gemma":8.517709e-7,"domain_scores_codex":[0.9990522,0.00004085294,0.0003407315,0.00006125761,0.0004289656,0.00007602329],"domain_scores_gemma":[0.9990916,0.00002326528,0.0003720829,0.0001550091,0.0002991144,0.00005891083],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001859738,0.0005861556,0.002693803,0.00003703944,0.00001307863,0.00001045453,0.0002960349,0.008047704,0.1569169,0.02179847,0.004343989,0.8050703],"study_design_scores_gemma":[0.00118437,0.001306007,0.2073217,0.00006891877,0.000007456034,0.0000650167,0.00001833245,0.7749089,0.00313237,0.001435297,0.01041751,0.0001341264],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1835931,0.000001451756,0.8122869,0.001190488,0.001927986,0.00005070196,2.596504e-7,0.00003134559,0.0009177583],"genre_scores_gemma":[0.9868248,0.000002816004,0.0126946,0.0003678738,0.00008154322,5.397181e-7,0.000001834137,0.000002412216,0.00002362596],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8049362,"threshold_uncertainty_score":0.1901729,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2083721127","doi":"10.1167/13.5.12","title":"Short-term monocular deprivation strengthens the patched eye's contribution to binocular combination","year":2013,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":139,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"Canadian Institutes of Health Research","keywords":"Ocular dominance; Monocular; Monocular deprivation; Binocular vision; Sensory system; Sensory deprivation; Dominance (genetics); Perception; Population; Monocular vision; Psychology; Optometry; Neuroscience; Visual cortex; Biology; Computer science; Artificial intelligence; Medicine","retraction":null,"screen_n_in":null,"score":{"opus":0.03180349968954732,"gpt":0.3318692270828555,"spread":0.3000657273933082,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000542409,0.0001111492,0.0001488208,0.0001439847,0.0002331074,0.0002164557,0.000252267,0.00007593223,0.0001307538],"category_scores_gemma":[0.0005720978,0.00007134894,0.0000947925,0.0002882456,0.00003883496,0.0005649974,0.0000446165,0.0002092268,0.0001297506],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007728326,"about_ca_system_score_gemma":0.00002303722,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003955252,"about_ca_topic_score_gemma":6.378162e-7,"domain_scores_codex":[0.9985262,0.0002090538,0.0004133955,0.000153448,0.00053456,0.0001633814],"domain_scores_gemma":[0.9990262,0.00008323205,0.0002428129,0.0001626873,0.0003708971,0.0001141603],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002937771,0.0001255143,0.0003465957,0.000004183138,0.00000275439,0.000003204231,0.0002658025,0.00008886285,0.9494132,0.0005840821,0.0002314765,0.04890491],"study_design_scores_gemma":[0.001914796,0.002233252,0.2157768,0.0002756788,0.00005714077,0.00008477754,0.0004383655,0.02886265,0.7368757,0.01049154,0.002604097,0.0003852969],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.964318,0.00001977888,0.03147126,0.003512069,0.0003500668,0.0002750323,0.000001280881,0.00002184449,0.0000306422],"genre_scores_gemma":[0.9986709,0.00004775136,0.0003684086,0.0007415397,0.00009631304,0.000006242487,0.000002543489,0.00001159988,0.00005472238],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2154302,"threshold_uncertainty_score":0.2909525,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2046612481","doi":"10.1167/7.6.1","title":"Priming of pop-out depends upon the current goals of observers","year":2007,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Neural and Behavioral Psychology Studies","field":"Neuroscience","cited_by":131,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Canadian Institutes of Health Research; Nederlandse Organisatie voor Wetenschappelijk Onderzoek","keywords":"Singleton; Visual search; Task (project management); Priming (agriculture); Psychology; Selection (genetic algorithm); Cognitive psychology; Current (fluid); Computer science; Artificial intelligence; Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.2156865639863731,"gpt":0.4565454107383726,"spread":0.2408588467519995,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00064437,0.00007587797,0.0002014475,0.00008674116,0.00006972702,0.000005976698,0.0002624493,0.00002726921,0.00001006447],"category_scores_gemma":[0.0001766976,0.00004000068,0.0001406872,0.0001424555,0.0001010379,0.0001319535,0.00006553027,0.0002460653,0.000002586472],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000150659,"about_ca_system_score_gemma":0.00001479804,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002549083,"about_ca_topic_score_gemma":0.000004451067,"domain_scores_codex":[0.9988253,0.00006890121,0.0005130128,0.00009447336,0.0003628822,0.0001353969],"domain_scores_gemma":[0.9989074,0.0002034627,0.0006375085,0.0001137155,0.00009840945,0.00003943256],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001426039,0.0001618644,0.005548872,0.00001148616,0.000002930359,0.00001797075,0.0002215118,0.000004611106,0.8917302,0.00002126551,0.0004210568,0.1017156],"study_design_scores_gemma":[0.0004268977,0.0007244512,0.188856,0.0001770422,0.00003824299,0.00004328707,0.0001193315,0.000003174882,0.807295,0.000187206,0.002073338,0.00005603569],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976417,0.0004695085,0.00005003373,0.0005495591,0.001019982,0.00005415794,0.00000176106,0.000002924295,0.0002104093],"genre_scores_gemma":[0.9994625,0.0002823524,0.00006494926,0.00007659566,0.00006719821,1.218354e-7,4.975394e-8,0.000004219451,0.00004203521],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1833072,"threshold_uncertainty_score":0.163118,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2107256424","doi":"10.1167/6.8.7","title":"Adaptation aftereffects in the perception of gender from biological motion","year":2006,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Animal Behavior and Reproduction","field":"Agricultural and Biological Sciences","cited_by":129,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Queen's University","funders":"Volkswagen Foundation; National Science Foundation","keywords":"Biological motion; Adaptation (eye); Perception; Psychology; Cognitive psychology; Motion (physics); Motion perception; Visual perception; Communication; Computer vision; Computer science; Neuroscience","retraction":null,"screen_n_in":null,"score":{"opus":0.04665630424829471,"gpt":0.2717705290024811,"spread":0.2251142247541864,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003940478,0.0000441276,0.00008505445,0.0000142111,0.00003330905,0.00001156675,0.00007256021,0.00006047756,0.00007012006],"category_scores_gemma":[0.00001879135,0.00001172683,0.00006943077,0.0001175586,0.00002086245,0.0001142405,0.000007352529,0.00008782746,0.000002890249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000016134,"about_ca_system_score_gemma":0.000001652254,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002390282,"about_ca_topic_score_gemma":0.00003700894,"domain_scores_codex":[0.9993301,0.0001373868,0.0002286882,0.00007632115,0.0001735776,0.00005390343],"domain_scores_gemma":[0.9996801,0.00005855958,0.0001714709,0.00001997343,0.00005970262,0.00001016798],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00007725374,0.0001465039,0.04250782,9.508211e-7,8.337646e-7,0.000002234237,0.0001217802,0.0000447389,0.8779683,0.00001703735,0.00007588309,0.07903667],"study_design_scores_gemma":[0.00009290795,0.0004366211,0.9968257,0.00001459625,0.000006740458,0.00001097574,0.000714622,0.00005338536,0.0008195218,0.0008799211,0.0001170202,0.0000279912],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993494,0.0001307454,0.00008204915,0.0002353397,0.00009265064,0.00006016577,0.000002027635,0.000002700227,0.00004487648],"genre_scores_gemma":[0.9994043,0.0000428094,0.000133598,0.00001463127,0.0003873715,5.769756e-7,0.00001308208,2.361846e-7,0.000003407739],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9543179,"threshold_uncertainty_score":0.07677656,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2077760499","doi":"10.1167/14.12.6","title":"Time to wave good-bye to phase scrambling: Creating controlled scrambled images using diffeomorphic transformations","year":2014,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":127,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"","keywords":"Scrambling; Artificial intelligence; Perception; Pattern recognition (psychology); Computer science; Visual perception; Visual processing; Distortion (music); Texture (cosmology); Computer vision; Set (abstract data type); Communication; Image (mathematics); Psychology; Neuroscience; Algorithm","retraction":null,"screen_n_in":null,"score":{"opus":0.03332970293972583,"gpt":0.3160956066320331,"spread":0.2827659036923073,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008511147,0.0001634354,0.0004235986,0.0004053062,0.0003355139,0.0002135432,0.0001711698,0.00005330328,0.0001154305],"category_scores_gemma":[0.001489414,0.0001210325,0.0001927612,0.0004147731,0.00002671149,0.0005038122,0.00003597404,0.0002301335,0.0000801796],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007271513,"about_ca_system_score_gemma":0.00003568337,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003200074,"about_ca_topic_score_gemma":5.851494e-7,"domain_scores_codex":[0.9981462,0.0002041601,0.0006945374,0.0001939647,0.0005039105,0.0002572253],"domain_scores_gemma":[0.9985283,0.0004764173,0.0003719439,0.0001488399,0.0001997966,0.0002746823],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006735625,0.0001727165,0.000003222211,0.000007847703,0.000006121464,0.00001269345,0.0001327693,0.003908044,0.9846292,0.00009124749,0.0002727452,0.01008984],"study_design_scores_gemma":[0.01242895,0.004251496,0.0004297603,0.0004649961,0.0001128548,0.0003313711,0.00004760488,0.8497115,0.1289009,0.0005562399,0.002411659,0.0003527038],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.937348,0.000007139662,0.05834182,0.002372942,0.0003345828,0.0004044418,0.000009574014,0.00002461583,0.00115685],"genre_scores_gemma":[0.9951833,0.000006277341,0.002732824,0.001401148,0.000251351,0.000002517468,0.000001137776,0.0000211711,0.0004002799],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8557283,"threshold_uncertainty_score":0.4935563,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2073989558","doi":"10.1167/8.5.3","title":"Perception of animacy and direction from local biological motion signals","year":2008,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Animal Vocal Communication and Behavior","field":"Biochemistry, Genetics and Molecular Biology","cited_by":126,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Queen's University","funders":"","keywords":"Animacy; Biological motion; Perception; Psychology; Motion (physics); Point (geometry); Orientation (vector space); Communication; Artificial intelligence; Cognitive psychology; Computer science; Mathematics; Neuroscience","retraction":null,"screen_n_in":null,"score":{"opus":0.03828380624688172,"gpt":0.3221647216599073,"spread":0.2838809154130256,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001382745,0.00005161895,0.0001039451,0.00003060169,0.00004584391,0.000003798469,0.00006584067,0.00009166247,0.00003980622],"category_scores_gemma":[0.00003827639,0.00003800098,0.00006255887,0.00003371082,0.00009236202,0.000007852727,0.00003972794,0.00007682337,0.000001618174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008826036,"about_ca_system_score_gemma":0.00001243443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001512603,"about_ca_topic_score_gemma":0.000001281518,"domain_scores_codex":[0.9994863,0.00008043218,0.0002234693,0.00007383958,0.00009104345,0.00004489763],"domain_scores_gemma":[0.9995727,0.00001211513,0.0001720343,0.00007633375,0.0001262006,0.00004063138],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.000194055,0.0001004827,0.01185974,0.000001301315,0.000005904276,0.000001264428,0.00003327108,0.000005419621,0.9576018,0.000002853833,0.0001925145,0.03000141],"study_design_scores_gemma":[0.0004332177,0.001672299,0.9292943,0.00002309906,0.00001463051,0.00008331157,0.000205408,0.0001021896,0.0666041,0.0000472442,0.001459614,0.00006057167],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9906325,0.0005480947,0.008624587,0.00006800391,0.00003486062,0.00002899715,0.00000264834,0.000001986129,0.00005827252],"genre_scores_gemma":[0.9970025,0.001713094,0.001129084,0.00003855583,0.00008151771,3.154093e-7,0.00001354151,0.000003530254,0.00001783508],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9174346,"threshold_uncertainty_score":0.1549635,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2800118457","doi":"10.1167/18.4.18","title":"Eye movement training is most effective when it involves a task-relevant sensorimotor decision","year":2018,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Motor Control and Adaptation","field":"Neuroscience","cited_by":120,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"Bangladesh Agricultural University Research System","keywords":"Eye movement; Task (project management); Eye–hand coordination; Modalities; Modality (human–computer interaction); Computer science; Training (meteorology); Movement (music); Physical medicine and rehabilitation; Psychology; Artificial intelligence; Cognitive psychology; Medicine; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.02954489333415971,"gpt":0.3078787426132198,"spread":0.2783338492790601,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006763345,0.0001553996,0.000269663,0.0002045008,0.0002004444,0.0001029604,0.0002149176,0.0000680865,0.0001352868],"category_scores_gemma":[0.001164177,0.0001103623,0.000140101,0.0001751292,0.0000717039,0.0004807747,0.00005328654,0.0002151945,0.00006697456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009756769,"about_ca_system_score_gemma":0.00006452825,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001037773,"about_ca_topic_score_gemma":0.000007146833,"domain_scores_codex":[0.9980648,0.0001668159,0.0005356245,0.0002479736,0.0007549771,0.0002298035],"domain_scores_gemma":[0.9983816,0.0005224698,0.0005225798,0.0001603882,0.0002612783,0.0001516511],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000562703,0.00009421205,0.00005714822,0.000006378607,0.000009863514,0.00003695048,0.003452467,0.00002284343,0.8390315,0.00006305021,0.002202909,0.15446],"study_design_scores_gemma":[0.01422474,0.02570247,0.1047041,0.003273127,0.0002187168,0.0001782474,0.002601699,0.0742415,0.5537814,0.0316496,0.1882636,0.001160711],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9830458,0.00007832281,0.01296533,0.001958316,0.001081937,0.0003250757,0.000009394706,0.0000164757,0.0005193228],"genre_scores_gemma":[0.9926817,0.0000655581,0.002787405,0.003514928,0.000719383,0.000003191406,2.933855e-7,0.00001715326,0.0002104272],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.28525,"threshold_uncertainty_score":0.4500444,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2067147689","doi":"10.1167/8.1.9","title":"More efficient scanning for familiar faces","year":2008,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":114,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"","keywords":"Chin; Recall; Forehead; Psychology; Task (project management); Eye movement; Cognitive psychology; Face (sociological concept); Facial recognition system; Audiology; Communication; Artificial intelligence; Computer science; Pattern recognition (psychology); Medicine; Neuroscience; Anatomy","retraction":null,"screen_n_in":null,"score":{"opus":0.06985580579372011,"gpt":0.3498888719859511,"spread":0.280033066192231,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000176714,0.00005554662,0.0001005847,0.0001098826,0.0001637026,0.0000167619,0.00008363571,0.00003368654,0.00005248501],"category_scores_gemma":[0.0002624671,0.00004119023,0.00009834265,0.00009618063,0.0000446312,0.0001189083,0.00001115655,0.00009663642,0.00003085098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002711025,"about_ca_system_score_gemma":0.00002681127,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":8.945886e-7,"about_ca_topic_score_gemma":1.518334e-7,"domain_scores_codex":[0.9993027,0.00003403258,0.0002127774,0.00008538592,0.0002630735,0.0001020614],"domain_scores_gemma":[0.9995396,0.00009942355,0.0001589101,0.00004746952,0.00009141036,0.00006319577],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001054343,0.0001017094,0.0001304636,0.0000116254,0.000001352398,0.00001745056,0.0009779035,0.002556469,0.9749316,0.00001344648,0.004000351,0.0171522],"study_design_scores_gemma":[0.005734247,0.0034544,0.1351724,0.0007886508,0.00005045858,0.002758326,0.002227841,0.09962863,0.6639533,0.0003820677,0.08523816,0.0006114781],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950265,0.00003251767,0.003513477,0.0005354705,0.0003839831,0.00008172524,0.000004521725,0.00001025407,0.0004115586],"genre_scores_gemma":[0.9981735,0.00023047,0.000917631,0.0003705248,0.0001081158,8.516254e-7,4.203631e-7,0.00000638725,0.0001921059],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3109783,"threshold_uncertainty_score":0.1679689,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2013129535","doi":"10.1167/4.10.2","title":"Low spatial frequencies are suppressively masked across spatial scale, orientation, field position, and eye of origin","year":2004,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":112,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"Engineering and Physical Sciences Research Council; Canadian Institutes of Health Research","keywords":"Position (finance); Scale (ratio); Orientation (vector space); Spatial ecology; Geography; Cartography; Geometry; Mathematics; Biology","retraction":null,"screen_n_in":null,"score":{"opus":0.02319714075296459,"gpt":0.3471674475519855,"spread":0.3239703067990209,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002143444,0.0001080233,0.0001993935,0.00009272661,0.0001974406,0.0000903609,0.0001421558,0.00008667582,0.0001062482],"category_scores_gemma":[0.0003057022,0.00008656735,0.00006540905,0.0001495661,0.00009956014,0.0004586256,0.00003461873,0.0001826934,0.000006413651],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003762258,"about_ca_system_score_gemma":0.00007167351,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005649564,"about_ca_topic_score_gemma":0.00002502756,"domain_scores_codex":[0.9987448,0.00006934686,0.000428221,0.0001621468,0.0004498832,0.0001456105],"domain_scores_gemma":[0.9989274,0.0000646959,0.0005627642,0.00008553348,0.0002622682,0.00009739858],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002276137,0.0001327929,0.001151356,0.00004494334,0.000002297632,0.00002687429,0.001662851,0.0001221897,0.9914274,0.00006913314,0.00009203813,0.005040519],"study_design_scores_gemma":[0.001469031,0.001196462,0.04684133,0.0004150313,0.00001326318,0.0001174766,0.0003849015,0.000144078,0.9460136,0.003210134,0.00007807383,0.0001165776],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9542314,0.00001971375,0.04408113,0.001058247,0.0004712607,0.00006731974,0.00001745677,0.00001086384,0.0000426363],"genre_scores_gemma":[0.9980005,0.00006821177,0.001160744,0.0005353912,0.000176778,7.236828e-7,0.000001392115,0.000009352085,0.00004692667],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04568997,"threshold_uncertainty_score":0.3530114,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2053646610","doi":"10.1167/12.4.12","title":"Competition increases binding errors in visual working memory","year":2012,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Neural and Behavioral Psychology Studies","field":"Neuroscience","cited_by":111,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"","keywords":"Working memory; Recall; Sample (material); Encoding (memory); Psychology; Object (grammar); Representation (politics); Competition (biology); Computer science; Cognitive psychology; Artificial intelligence; Neuroscience; Cognition; Biology","retraction":null,"screen_n_in":null,"score":{"opus":0.1380062555933388,"gpt":0.419177624746932,"spread":0.2811713691535931,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000352894,0.00007644312,0.0001553707,0.0002130235,0.0000901818,0.00001499097,0.0000952522,0.00003728698,0.0000399438],"category_scores_gemma":[0.0001272074,0.00005420736,0.00006008043,0.0002171522,0.00005858394,0.0003960464,0.00004694421,0.0002315791,0.00002702257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003742113,"about_ca_system_score_gemma":0.000005824781,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005719842,"about_ca_topic_score_gemma":0.000003355509,"domain_scores_codex":[0.9990924,0.0001315121,0.0002821038,0.00008525231,0.0002178419,0.0001908833],"domain_scores_gemma":[0.9995257,0.0001271727,0.0002197256,0.00004250122,0.00001816699,0.00006677737],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00008718628,0.0003984712,0.08714281,0.00000318971,0.000001121886,0.00006357433,0.0001519972,0.000004188495,0.9046356,0.00001962047,0.0002005261,0.007291737],"study_design_scores_gemma":[0.001300401,0.0007975201,0.7189193,0.00051191,0.00002916891,0.0006673727,0.0006862746,0.00002223489,0.275331,0.0001352639,0.001377104,0.0002225015],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983255,0.0001508189,0.000004596454,0.0003049916,0.0007951099,0.00003932667,4.3837e-7,0.000008272002,0.000370909],"genre_scores_gemma":[0.9993482,0.00008011232,0.00006368433,0.000239365,0.0002255211,4.772965e-7,1.570589e-7,0.000005677576,0.00003679294],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6317765,"threshold_uncertainty_score":0.2210512,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2056709066","doi":"10.1167/11.12.18","title":"When more is less: Extraction of summary statistics benefits from larger sets","year":2011,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":106,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"International Laboratory for Brain, Music and Sound Research","funders":"","keywords":"Set (abstract data type); Statistics; Summary statistics; Computer science; Mode (computer interface); Object (grammar); Process (computing); Extraction (chemistry); Data mining; Artificial intelligence; Mathematics; Human–computer interaction","retraction":null,"screen_n_in":null,"score":{"opus":0.1136992071772839,"gpt":0.365900095340348,"spread":0.2522008881630641,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002336257,0.00008639813,0.0001664383,0.0001107706,0.0000688575,0.00002783459,0.0001595694,0.0000759373,0.001073509],"category_scores_gemma":[0.000141188,0.00006788464,0.00005981565,0.00008075759,0.00003412595,0.0004136648,0.00002795411,0.0001945752,0.00002692148],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001908363,"about_ca_system_score_gemma":0.00004052703,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002273364,"about_ca_topic_score_gemma":0.000002670051,"domain_scores_codex":[0.9988754,0.00007241271,0.0003910235,0.0001243222,0.0004343079,0.0001025628],"domain_scores_gemma":[0.9990504,0.00008709921,0.0005143283,0.0001061104,0.000159392,0.00008269926],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002113329,0.0002710291,0.0002806266,0.00002216091,0.000005242944,0.00002700854,0.003307767,0.000008209873,0.9206955,0.0002132405,0.01001665,0.06494123],"study_design_scores_gemma":[0.001411079,0.001474457,0.07871927,0.0007965901,0.00008919933,0.0001391472,0.001089668,0.00359686,0.8823,0.02668165,0.003384423,0.0003176145],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9838175,0.0001323255,0.01463145,0.0002046947,0.0006622414,0.00004445932,0.0001238726,0.00001111233,0.0003723969],"genre_scores_gemma":[0.9845361,0.000327627,0.01410094,0.0007179951,0.00008025712,2.56147e-7,0.000002793322,0.00001412522,0.0002199669],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07843865,"threshold_uncertainty_score":0.9998397,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2170586335","doi":"10.1167/2.1.6","title":"Optimal methods for calculating classification images: Weighted sums","year":2002,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":106,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University; University of Toronto","funders":"","keywords":"Observer (physics); Pattern recognition (psychology); Artificial intelligence; Pixel; Mathematics; Noise power; Computer science; Noise (video); Classifier (UML); Algorithm; Image (mathematics); Power (physics); Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.1508094583381225,"gpt":0.4506874559374864,"spread":0.299877997599364,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007841607,0.00008570724,0.0001527927,0.0001352742,0.0001914662,0.0001011108,0.0001551378,0.00006705118,0.0002714585],"category_scores_gemma":[0.0007159471,0.00006518632,0.000117347,0.0001903046,0.00003062725,0.0003810794,0.00001662638,0.0001650857,0.00002303832],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003872819,"about_ca_system_score_gemma":0.00001286815,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":2.200361e-7,"about_ca_topic_score_gemma":2.300315e-8,"domain_scores_codex":[0.9988919,0.0001956788,0.0004011763,0.0001474763,0.0002230417,0.0001407627],"domain_scores_gemma":[0.9989846,0.0002788033,0.0004072251,0.00008974654,0.000153071,0.00008651258],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002976238,0.00006409136,0.000003079945,0.00001121588,0.000001154103,0.000001494902,0.000213149,0.0000395832,0.8162561,0.0001661398,0.000654712,0.1825595],"study_design_scores_gemma":[0.0008453858,0.0007527553,0.0004675276,0.0001048566,0.0000224848,0.0001312664,0.0001794863,0.58838,0.4009056,0.0009085071,0.007163001,0.0001391932],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1567861,0.0000950967,0.8409174,0.0009731129,0.00051393,0.0001154178,0.000001977228,0.00002875912,0.0005681815],"genre_scores_gemma":[0.7327744,0.00006554367,0.266205,0.0003197232,0.000149429,0.000001772005,4.464643e-7,0.00001424681,0.0004694568],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5883403,"threshold_uncertainty_score":0.297228,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2126487483","doi":"10.1167/9.1.10","title":"Binocular depth discrimination and estimation beyond interaction space","year":2009,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":101,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Binocular disparity; Monocular; Depth perception; Stereopsis; Artificial intelligence; Binocular vision; Computer vision; Computer science; Stereoscopy; Mathematics; Psychology; Perception","retraction":null,"screen_n_in":null,"score":{"opus":0.04065600374643451,"gpt":0.3732164533141479,"spread":0.3325604495677134,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002398241,0.00006308129,0.00008629749,0.0001582292,0.00009962658,0.0001212141,0.00005445499,0.00003892073,0.00002662484],"category_scores_gemma":[0.0002529446,0.00004887841,0.00003320033,0.000116777,0.00001536359,0.0009230956,0.000008608247,0.0001297344,0.00001059405],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003231153,"about_ca_system_score_gemma":0.00001257446,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":6.162343e-7,"about_ca_topic_score_gemma":4.661023e-7,"domain_scores_codex":[0.9993143,0.00006480898,0.0002021386,0.00009553353,0.0002552822,0.00006793196],"domain_scores_gemma":[0.9995555,0.00003507894,0.0002426004,0.00004725615,0.00006146631,0.0000581307],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000484857,0.0000545144,0.000008061807,0.000006432519,4.279206e-7,0.00000525549,0.0003282195,0.0001296526,0.7860547,0.0008025889,0.0001755066,0.2123861],"study_design_scores_gemma":[0.001859156,0.004572394,0.05671217,0.0006050803,0.00006683615,0.001255826,0.0006658272,0.1590031,0.7237407,0.04905331,0.002114137,0.000351512],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9437683,0.00003928078,0.05266145,0.002404764,0.0003117065,0.00004690758,2.952268e-7,0.0000151002,0.0007521593],"genre_scores_gemma":[0.9959131,0.00009328959,0.003346173,0.0004886164,0.00006055368,1.422289e-7,5.857739e-7,0.000004206805,0.00009326158],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2120346,"threshold_uncertainty_score":0.1993204,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1977224048","doi":"10.1167/14.1.8","title":"The relationship between delay period eye movements and visuospatial memory","year":2014,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Gaze Tracking and Assistive Technology","field":"Computer Science","cited_by":95,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto; Baycrest Hospital","funders":"University of Washington; Canadian Institutes of Health Research; University of California, Santa Cruz","keywords":"Period (music); Eye movement; Psychology; Cognitive psychology; Audiology; Neuroscience; Medicine; Art","retraction":null,"screen_n_in":null,"score":{"opus":0.01915743113698923,"gpt":0.2994896895230041,"spread":0.2803322583860149,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008635414,0.00005757917,0.000102852,0.00007428486,0.000262932,0.0001064489,0.0003772349,0.00004949079,9.091668e-7],"category_scores_gemma":[0.0003371848,0.00003511578,0.0000373544,0.00009726374,0.00005618415,0.0001992414,0.0001046971,0.000224183,0.000005434097],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001828481,"about_ca_system_score_gemma":0.000018307,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000023109,"about_ca_topic_score_gemma":0.000001307394,"domain_scores_codex":[0.9992588,0.00009496194,0.0002384938,0.00008793157,0.0002143574,0.0001054381],"domain_scores_gemma":[0.9990882,0.0003755925,0.0002408702,0.0001666447,0.00008162695,0.00004708857],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001489244,0.00004136005,0.5456149,0.000006374249,0.00002435983,0.00001120593,0.0003426022,0.00002370934,0.001175353,0.01412105,0.0006305146,0.4379937],"study_design_scores_gemma":[0.0002917138,0.0003264425,0.9871644,0.00003427032,0.000005442389,0.00001683776,0.00001650654,0.001565387,0.0001412681,0.008678563,0.001714792,0.0000443611],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8214344,0.0001049558,0.1750337,0.003025922,0.0002079784,0.00002506949,1.733463e-7,0.00001794721,0.0001498308],"genre_scores_gemma":[0.9947652,0.000006106943,0.005005907,0.00004440221,0.0001055315,3.144365e-7,1.092207e-7,0.000003105665,0.00006937995],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4415495,"threshold_uncertainty_score":0.2022287,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2139711497","doi":"10.1167/10.6.19","title":"Stereoscopic perception of real depths at large distances","year":2010,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":94,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"Engineering and Physical Sciences Research Council","keywords":"Depth perception; Monocular; Binocular disparity; Stereopsis; Binocular vision; Stereoscopy; Optics; Perception; Scaling; Geodesy; Darkness; Mathematics; Physics; Artificial intelligence; Geology; Computer vision; Computer science; Geometry; Psychology","retraction":null,"screen_n_in":null,"score":{"opus":0.03176698494057428,"gpt":0.3605781491206254,"spread":0.3288111641800511,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000385431,0.0000768102,0.0001573215,0.00009971413,0.0001217222,0.0000331478,0.0001788647,0.00007209945,0.0008542688],"category_scores_gemma":[0.0001483738,0.00005582735,0.00008147692,0.0001169738,0.00005156731,0.0003069979,0.00004025755,0.0002344826,0.00004029767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002577592,"about_ca_system_score_gemma":0.00003023679,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001922802,"about_ca_topic_score_gemma":0.00002099823,"domain_scores_codex":[0.9989337,0.00007214416,0.0003521664,0.0001160443,0.0004012075,0.0001246843],"domain_scores_gemma":[0.9992695,0.00005364522,0.0003952005,0.0001083014,0.00009075339,0.00008253744],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00009480655,0.0001027463,0.0007355987,0.00002199885,7.835111e-7,0.000004626751,0.0004419592,0.000001167281,0.988171,0.0002346657,0.0002781415,0.009912515],"study_design_scores_gemma":[0.003412351,0.003614678,0.2409505,0.0005359873,0.00005400772,0.0004491887,0.001270608,0.002489554,0.7251285,0.003515743,0.01814497,0.0004339187],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996323,0.00000971093,0.001475714,0.0001443501,0.0008534638,0.00003846289,0.000004682121,0.00001056485,0.001140091],"genre_scores_gemma":[0.9978247,0.000143679,0.001126758,0.000139886,0.0001453452,2.844042e-7,5.711839e-7,0.000008654724,0.0006101577],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2630425,"threshold_uncertainty_score":0.9353645,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2030649313","doi":"10.1167/8.3.11","title":"It doesn't matter how you feel. The facial identity aftereffect is invariant to changes in facial expression","year":2008,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":94,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"National Institute of Mental Health","keywords":"Psychology; Expression (computer science); Facial expression; Identity (music); Cognitive psychology; Communication; Social psychology; Computer science; Aesthetics; Art","retraction":null,"screen_n_in":null,"score":{"opus":0.05159882905887763,"gpt":0.3222580236900636,"spread":0.270659194631186,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004620152,0.0001226331,0.0001836472,0.0002392796,0.00019592,0.0001214314,0.0002534247,0.00008586082,0.00139925],"category_scores_gemma":[0.0002284802,0.00007373613,0.0001014907,0.0002456039,0.00004747551,0.0006435587,0.00009045497,0.0003061308,0.0004298806],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006243939,"about_ca_system_score_gemma":0.00002456335,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001225673,"about_ca_topic_score_gemma":0.00007459844,"domain_scores_codex":[0.9984946,0.0003017104,0.0002476614,0.0001841612,0.000581361,0.0001904894],"domain_scores_gemma":[0.9994355,0.00008630413,0.0001878159,0.0001288181,0.00005748918,0.000104088],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0002650579,0.00009618045,0.00260506,0.00001147645,0.000001372909,0.00007728468,0.004494862,0.000008424475,0.9597712,9.077734e-7,0.02609498,0.006573163],"study_design_scores_gemma":[0.001918409,0.0009484011,0.5967584,0.0005735748,0.00001605331,0.0006284793,0.0005814877,0.0001346322,0.3531347,0.0001891783,0.04477048,0.0003461771],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9721123,0.00001034502,0.0003953518,0.02627356,0.000678462,0.0001979798,0.00001524785,0.000006976549,0.0003097484],"genre_scores_gemma":[0.9900964,0.0001978633,0.00008105273,0.008822501,0.0003104731,0.000004647684,6.382755e-7,0.00000988975,0.0004765349],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6066365,"threshold_uncertainty_score":0.9995136,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2547400687","doi":"10.1167/16.14.1","title":"Eye movement accuracy determines natural interception strategies","year":2016,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":94,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"International Collaboration On Repair Discoveries; University of British Columbia","funders":"","keywords":"Interception; Eye movement; Smooth pursuit; Artificial intelligence; Computer science; Perception; Heuristics; Computer vision; Saccadic masking; Cognitive psychology; Psychology; Neuroscience","retraction":null,"screen_n_in":null,"score":{"opus":0.0434642899019958,"gpt":0.3798841835464823,"spread":0.3364198936444865,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002378009,0.00009468295,0.000121471,0.0001277052,0.00008212774,0.0001356525,0.0001979542,0.00003998553,0.0003761899],"category_scores_gemma":[0.0003444263,0.00005014318,0.00008606688,0.00008812252,0.00004098407,0.001212152,0.0000405555,0.0001140713,0.00008176827],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004888844,"about_ca_system_score_gemma":0.00003893253,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":6.108251e-7,"about_ca_topic_score_gemma":0.000001069061,"domain_scores_codex":[0.9989861,0.00008319545,0.0003351956,0.0001230872,0.0003448879,0.0001275701],"domain_scores_gemma":[0.9993128,0.0001023098,0.0003311998,0.00008582282,0.0001035549,0.00006435491],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00007711595,0.00003910612,0.00001801763,0.000006749598,9.203993e-7,0.00000868199,0.0001574601,0.000002097914,0.8623941,0.0001516188,0.0003358161,0.1368083],"study_design_scores_gemma":[0.001723895,0.001899401,0.01510875,0.0009032481,0.00001701114,0.0001382512,0.0007252981,0.0007698881,0.960233,0.01371139,0.004486017,0.0002838911],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9894004,0.00002542852,0.008141536,0.001159607,0.000985167,0.0000430013,0.000001093645,0.00002086806,0.0002229093],"genre_scores_gemma":[0.9978276,0.0001505687,0.000392928,0.0007136622,0.0002279611,5.490094e-7,1.15614e-7,0.000008516628,0.0006780535],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1365244,"threshold_uncertainty_score":0.4119016,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2054914591","doi":"10.1167/7.10.12","title":"Peripheral vision: Good for biological motion, bad for signal noise segregation?","year":2007,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":93,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Queen's University; McGill University","funders":"","keywords":"Biological motion; Peripheral vision; Motion (physics); Perception; Noise (video); Motion perception; Computer vision; SIGNAL (programming language); Artificial intelligence; Computer science; Structure from motion; Peripheral; Communication; Neuroscience; Psychology","retraction":null,"screen_n_in":null,"score":{"opus":0.03082088930988142,"gpt":0.3187292387090656,"spread":0.2879083493991841,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009672472,0.0001146061,0.0001808521,0.0001187996,0.0002341291,0.0000729394,0.0001591464,0.00009891245,0.00005202847],"category_scores_gemma":[0.0005023278,0.00007737424,0.0002296759,0.0001599946,0.00004683022,0.0003375965,0.00002378802,0.0001429949,0.000003217494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006781856,"about_ca_system_score_gemma":0.00002630843,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":5.025335e-7,"about_ca_topic_score_gemma":0.000001274989,"domain_scores_codex":[0.9987554,0.00004959424,0.0004900247,0.0002043148,0.000279969,0.0002206936],"domain_scores_gemma":[0.9985766,0.0005932127,0.0003676718,0.00008482303,0.0002657776,0.0001119299],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001016702,0.0002268293,0.0003626156,0.00001318614,0.000004389588,0.00001046359,0.0000359316,0.0003531054,0.9278442,0.004026907,0.001712858,0.06439278],"study_design_scores_gemma":[0.01455467,0.03704931,0.1895874,0.0003953805,0.0001198174,0.001285761,0.0002360128,0.172023,0.3887686,0.08878758,0.1060192,0.0011734],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7532654,0.00002824029,0.2437717,0.001362767,0.001071229,0.0003348815,0.00001458668,0.00001690777,0.0001342824],"genre_scores_gemma":[0.9943716,0.00002040782,0.004139191,0.0006468236,0.0005546439,0.000003154773,0.000004168603,0.00001271109,0.0002473249],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5390757,"threshold_uncertainty_score":0.315523,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2084346734","doi":"10.1167/7.5.4","title":"Computations for geometrically accurate visually guided reaching in 3-D space","year":2007,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Motor Control and Adaptation","field":"Neuroscience","cited_by":91,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University; Canadian Institutes of Health Research","funders":"","keywords":"Gaze; Computer vision; Computer science; Rotation (mathematics); Eye movement; Artificial intelligence; Head (geology); Visual space; Saccade; Transformation (genetics); Eye tracking; Computation; Algorithm; Psychology; Neuroscience; Perception","retraction":null,"screen_n_in":null,"score":{"opus":0.06518901778499131,"gpt":0.3801205501212688,"spread":0.3149315323362775,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001494029,0.00006679882,0.0001508561,0.0005380446,0.00007414727,0.00005760933,0.0001360301,0.00003832136,0.000005013694],"category_scores_gemma":[0.002944832,0.00005322606,0.0000830674,0.0004707841,0.00001313345,0.0003507842,0.00001636041,0.0001549546,0.00000346531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000690296,"about_ca_system_score_gemma":0.00004476632,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005853372,"about_ca_topic_score_gemma":0.000005900015,"domain_scores_codex":[0.9988191,0.00006362063,0.0005371487,0.0001113344,0.0003055787,0.0001631962],"domain_scores_gemma":[0.9981841,0.001110985,0.0004210416,0.00005818781,0.0001486776,0.00007699944],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.000325831,0.0002012486,0.0002338935,0.0000124436,0.00000315172,0.00006332817,0.0004684797,0.00700898,0.9374121,0.003492922,0.0003019352,0.05047573],"study_design_scores_gemma":[0.01297002,0.004054664,0.6451079,0.0005957104,0.00005684792,0.0004145443,0.0004565096,0.2567699,0.03813786,0.01991739,0.02091673,0.0006018917],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6281207,0.00003400132,0.3699468,0.001210422,0.0002525066,0.0001383616,0.000001338292,0.000007711937,0.0002882213],"genre_scores_gemma":[0.9899533,0.00001894416,0.009490118,0.0003389922,0.0001337677,6.105005e-7,4.476161e-7,0.000007799474,0.00005599923],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8992742,"threshold_uncertainty_score":0.3525451,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1970058136","doi":"10.1167/3.1.4","title":"Orienting of attention without awareness is affected by measurement-induced attentional control settings","year":2003,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Neural and Behavioral Psychology Studies","field":"Neuroscience","cited_by":91,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Dalhousie University","funders":"National Research Council Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Facilitation; Inhibition of return; Psychology; Cognitive psychology; Rapid serial visual presentation; Sensory cue; Selective attention; Perception; Attentional control; Control (management); Audiology; Visual attention; Cognition; Neuroscience; Medicine; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.09483524831940965,"gpt":0.3737049801959736,"spread":0.2788697318765639,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009209197,0.0001318669,0.0002969254,0.0001089178,0.0002103445,0.00002376857,0.0001385716,0.0000611924,0.00004330745],"category_scores_gemma":[0.0005086144,0.00009578071,0.0001706564,0.0002230259,0.00006732911,0.0002686207,0.00001838186,0.0002472914,0.000006942154],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003796331,"about_ca_system_score_gemma":0.00002994557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002549994,"about_ca_topic_score_gemma":6.372071e-7,"domain_scores_codex":[0.9979426,0.0003216821,0.0005358111,0.0002147513,0.0007929193,0.0001922066],"domain_scores_gemma":[0.9985356,0.0000647643,0.0007965131,0.00009781081,0.0004422682,0.00006301689],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00007428581,0.0003077183,0.034541,0.00001327727,0.00001288405,0.000008253607,0.00003707573,6.855646e-7,0.9617161,0.000009563745,0.002379033,0.0009001009],"study_design_scores_gemma":[0.003052266,0.0007911867,0.1237911,0.0002569951,0.000107434,0.0001250713,0.00009733744,0.00002159908,0.8707726,0.0001277942,0.0007050293,0.0001516273],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978997,0.00007917632,0.0003262052,0.0006962132,0.0007668724,0.000122381,0.000007827893,0.00001033118,0.00009137069],"genre_scores_gemma":[0.9994649,0.00001291654,0.00006612721,0.0003199157,0.00004145206,0.000001450111,3.898346e-7,0.000009709839,0.00008315301],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09094352,"threshold_uncertainty_score":0.3905824,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2087971418","doi":"10.1167/13.10.5","title":"Abnormality in face scanning by children with autism spectrum disorder is limited to the eye region: Evidence from multi-method analyses of eye tracking data","year":2013,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Autism Spectrum Disorder Research","field":"Neuroscience","cited_by":87,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development","keywords":"Autism spectrum disorder; Abnormality; Eye movement; Psychology; Autism; Eye contact; Eye tracking; Pupil; Typically developing; Audiology; Developmental psychology; Optometry; Medicine; Computer vision; Neuroscience; Psychiatry; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.1132229114371968,"gpt":0.4298872907372605,"spread":0.3166643793000637,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001287092,0.0002306349,0.0004592662,0.000332059,0.0001939031,0.0002173828,0.002014108,0.00008365225,0.0001298429],"category_scores_gemma":[0.001018879,0.000142949,0.0000914142,0.001332615,0.0001371486,0.001898418,0.0006167988,0.0007723793,0.00001943147],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000805787,"about_ca_system_score_gemma":0.000111228,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005059651,"about_ca_topic_score_gemma":0.000268623,"domain_scores_codex":[0.9961601,0.0008105637,0.0008124058,0.0005795644,0.001188672,0.0004486212],"domain_scores_gemma":[0.9972796,0.0006876421,0.0007421737,0.001073096,0.00004323096,0.0001742997],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004878551,0.000829411,0.7608103,0.0000299085,0.00009616682,0.00008026719,0.005345751,0.006451032,0.2030972,0.00003355063,0.002460011,0.02027855],"study_design_scores_gemma":[0.0007857729,0.0004202904,0.93999,0.0006150648,0.00003327296,0.00004027818,0.0002154347,0.03162716,0.02581146,0.0001887926,0.00008990908,0.0001825731],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9043345,0.001195924,0.05825663,0.03561468,0.00005404299,0.0004883852,0.00003143884,0.0000128853,0.00001148713],"genre_scores_gemma":[0.9935917,0.0005395547,0.005397331,0.000336633,0.0000356963,0.000003728521,0.000003478384,0.00002754662,0.00006429187],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1791797,"threshold_uncertainty_score":0.7648713,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1992489403","doi":"10.1167/5.10.1","title":"Spatial scaling factors explain eccentricity effects on face ERPs","year":2005,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":83,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; McMaster University","keywords":"Foveal; Stimulus (psychology); Eccentricity (behavior); Magnification; Scaling; Psychology; Event-related potential; Face (sociological concept); Cognitive psychology; Communication; Optics; Neuroscience; Physics; Electroencephalography; Geometry; Mathematics; Biology; Social psychology","retraction":null,"screen_n_in":null,"score":{"opus":0.03230394907559354,"gpt":0.3149323902562124,"spread":0.2826284411806189,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002401227,0.0001028061,0.0001492658,0.0001714866,0.0001161389,0.00005657763,0.0001157008,0.00006723194,0.0002227858],"category_scores_gemma":[0.0005981693,0.00007497332,0.0001181339,0.0001230116,0.00001718047,0.0003381815,0.00001806982,0.0002813188,0.0001932925],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009761032,"about_ca_system_score_gemma":0.00001851228,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004470545,"about_ca_topic_score_gemma":0.000002623149,"domain_scores_codex":[0.9988042,0.0001853439,0.0002720184,0.0001292555,0.0004549955,0.0001541471],"domain_scores_gemma":[0.9991368,0.0003981766,0.000224892,0.00007243323,0.00004177111,0.0001258924],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001990573,0.0002446757,0.0008148773,0.00001560113,0.000002575128,0.0000240371,0.0005577194,0.001630942,0.6620509,0.000009326489,0.001630811,0.3328195],"study_design_scores_gemma":[0.001282577,0.0008716215,0.03918991,0.0002904901,0.00001398123,0.00006888416,0.00008581425,0.007068597,0.9415439,0.00005580107,0.009356737,0.0001716515],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941216,0.00001558513,0.004104279,0.0006274695,0.0006567866,0.00008734071,0.000003148986,0.00001778174,0.0003660013],"genre_scores_gemma":[0.9985645,0.0001166326,0.0001654292,0.0005535817,0.0005167814,2.837739e-7,7.305537e-7,0.000009031509,0.00007297964],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3326478,"threshold_uncertainty_score":0.3057323,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1976580685","doi":"10.1167/15.3.3","title":"Modulation of microsaccade rate by task difficulty revealed through between- and within-trial comparisons","year":2015,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":83,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"Fundamental Research Funds for the Central Universities; Natural Sciences and Engineering Research Council of Canada","keywords":"Microsaccade; Stimulus (psychology); Task (project management); Fixation (population genetics); Cognitive psychology; Cognition; Psychology; Audiology; Eye movement; Computer science; Neuroscience; Medicine; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.1109372445811974,"gpt":0.3829495186371782,"spread":0.2720122740559808,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000654921,0.00009522019,0.000267898,0.00005943128,0.00008622844,0.00006172249,0.0001236969,0.00008235187,0.000009804371],"category_scores_gemma":[0.0002752218,0.00007018705,0.0000500834,0.0001546335,0.00006634009,0.0004038801,0.00003427636,0.0002092996,0.000005033468],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002679842,"about_ca_system_score_gemma":0.00004694481,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004655453,"about_ca_topic_score_gemma":5.717303e-7,"domain_scores_codex":[0.9986482,0.0002240782,0.0005342673,0.0001366542,0.0003559277,0.0001008423],"domain_scores_gemma":[0.9988667,0.00009419247,0.0007082073,0.00007898238,0.0001359665,0.0001159437],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001478894,0.0001046422,0.0001282908,0.0000121607,0.000002723537,0.000001855535,0.0007725179,0.00007620994,0.9905291,0.00004107665,0.006049327,0.0008031882],"study_design_scores_gemma":[0.05753237,0.007937448,0.02111776,0.0006614862,0.000144838,0.0002594903,0.0008517397,0.009487595,0.8867568,0.008573013,0.006097506,0.0005799739],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9884788,0.00004766236,0.01057213,0.0003695165,0.0003686201,0.0001020726,0.00001248356,0.000009436451,0.0000392611],"genre_scores_gemma":[0.9980633,0.00003563167,0.001514688,0.0001312551,0.0001426602,3.024996e-7,0.000002849997,0.000008731824,0.0001006306],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1037723,"threshold_uncertainty_score":0.2862145,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2114082655","doi":"10.1167/13.5.19","title":"Interocular suppression in amblyopia for global orientation processing","year":2013,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":81,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"Canadian Institutes of Health Research","keywords":"Coherence (philosophical gambling strategy); Contrast (vision); Visual cortex; Psychology; Orientation (vector space); Neuroscience; Artificial intelligence; Communication; Computer science; Physics; Mathematics; Geometry","retraction":null,"screen_n_in":null,"score":{"opus":0.04066620122061524,"gpt":0.3821027797157434,"spread":0.3414365784951281,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000241308,0.00007680606,0.0001252034,0.00009535869,0.00007867773,0.0001357524,0.0001387769,0.0000571101,0.00008652051],"category_scores_gemma":[0.0002901107,0.00005676783,0.00005673054,0.0002013897,0.00001991121,0.0008694615,0.00002308908,0.0001052861,0.00001857355],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007370162,"about_ca_system_score_gemma":0.00003992314,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002363334,"about_ca_topic_score_gemma":0.000001037194,"domain_scores_codex":[0.9990435,0.00006407737,0.0003580099,0.0001328306,0.0002679812,0.0001336035],"domain_scores_gemma":[0.999427,0.00003391351,0.0002722115,0.00005226341,0.000147032,0.0000675992],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00009680645,0.0000950369,0.000186728,0.00004005937,5.141915e-7,0.000003002379,0.0002567084,0.00004154994,0.8992299,0.0001734547,0.0005570513,0.09931916],"study_design_scores_gemma":[0.007768714,0.004331075,0.06400264,0.003010119,0.00004299951,0.0004128281,0.002082685,0.09555042,0.757755,0.05906025,0.005352465,0.0006308496],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9551725,0.00003317256,0.04350222,0.000455122,0.0004695862,0.0001700688,9.67747e-7,0.00001177815,0.0001845695],"genre_scores_gemma":[0.9963674,0.00001485169,0.003103116,0.0003436777,0.00008134913,0.000004468572,6.920149e-7,0.000007164268,0.00007726504],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.141475,"threshold_uncertainty_score":0.2314925,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2152847456","doi":"10.1167/9.2.10","title":"Uncovering gender discrimination cues in a realistic setting","year":2009,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":79,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Psychology; Cognitive psychology; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.06716946727653153,"gpt":0.381128471948262,"spread":0.3139590046717304,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004117705,0.00005600589,0.00009116086,0.0001631559,0.00005880479,0.00006408813,0.00008995493,0.00003195048,0.00002893896],"category_scores_gemma":[0.0004530989,0.00004402765,0.00003531791,0.0001594344,0.000008600654,0.0003859147,0.00001048077,0.0001493141,0.000006386682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005422554,"about_ca_system_score_gemma":0.00002309907,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000139407,"about_ca_topic_score_gemma":0.000001210536,"domain_scores_codex":[0.9991938,0.00007556845,0.0002696646,0.00008896347,0.0002737671,0.00009824919],"domain_scores_gemma":[0.999638,0.00004792892,0.0001881249,0.00004646729,0.00003787086,0.00004167613],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00003882361,0.00006769723,0.00004612197,0.0000119499,2.331858e-7,0.00003140577,0.0009572166,0.000624981,0.9398571,0.0004178242,0.0001253908,0.05782121],"study_design_scores_gemma":[0.003823592,0.004002519,0.3639039,0.002404576,0.00004799634,0.001107902,0.002323465,0.04191792,0.3616007,0.2165513,0.001548755,0.000767481],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9912702,0.00002657477,0.0064657,0.0006593193,0.0002095954,0.00003178145,4.967299e-7,0.00001187437,0.001324447],"genre_scores_gemma":[0.9982179,0.00004807373,0.0009098302,0.0006884314,0.0000798593,1.140593e-7,2.560242e-7,0.000004253472,0.00005125064],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5782565,"threshold_uncertainty_score":0.1795395,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2052178546","doi":"10.1167/9.1.25","title":"Spatial characteristics of center-surround antagonism in younger and older adults","year":2009,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":71,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University; York University","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Stimulus (psychology); Spatial frequency; Summation; Age groups; Contrast (vision); Audiology; Mathematics; Psychology; Physics; Optics; Medicine; Neuroscience; Demography","retraction":null,"screen_n_in":null,"score":{"opus":0.02160049971584018,"gpt":0.3191139716894563,"spread":0.2975134719736161,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000221905,0.00007062563,0.0001718091,0.0001219461,0.00003400659,0.00003798408,0.00008500718,0.00005025091,0.00004001602],"category_scores_gemma":[0.0001056428,0.00005537058,0.00003506233,0.00008587925,0.00002661974,0.000284008,0.00001457392,0.000153763,0.000002744257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001576584,"about_ca_system_score_gemma":0.00001982408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003384945,"about_ca_topic_score_gemma":5.874953e-7,"domain_scores_codex":[0.9991249,0.00005908666,0.0003715967,0.00009997506,0.0002468891,0.0000975251],"domain_scores_gemma":[0.9994956,0.00002841331,0.0003021531,0.00005528663,0.00006014659,0.0000583533],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0002989833,0.0002926726,0.0005787662,0.00002126665,5.107652e-7,0.00003097303,0.0006021485,3.724754e-7,0.883142,0.00006254898,0.0000250372,0.1149447],"study_design_scores_gemma":[0.002946787,0.002074452,0.8846908,0.0009230301,0.000009089094,0.0003356903,0.0001291326,0.001201872,0.106483,0.0007518647,0.0002980337,0.0001562866],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985163,0.0000237526,0.0007180511,0.0002796772,0.0003269368,0.0000433878,0.000004310437,0.000003587916,0.00008402295],"genre_scores_gemma":[0.9990442,0.0001909104,0.0001515681,0.0004950523,0.0000863383,7.89091e-8,5.733106e-7,0.000004577209,0.00002673458],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.884112,"threshold_uncertainty_score":0.2257947,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2090253169","doi":"10.1167/7.5.15","title":"Neuronal activity in superior colliculus signals both stimulus identity and saccade goals during visual conjunction search","year":2007,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":69,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Queen's University; Canadian Institutes of Health Research","funders":"Ontario Ministry of Research and Innovation; Canadian Institutes of Health Research","keywords":"Saccade; Superior colliculus; Stimulus (psychology); Neuroscience; Psychology; Eye movement; Premovement neuronal activity; Visual search; Neuron; Sensory system; Cognitive psychology","retraction":null,"screen_n_in":null,"score":{"opus":0.05063258639235296,"gpt":0.3884307589878739,"spread":0.3377981725955209,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001623261,0.0001265791,0.0002336328,0.0003631949,0.0002108983,0.0001841393,0.0001317925,0.00009584419,0.0001341083],"category_scores_gemma":[0.0003266956,0.0001096625,0.00006366101,0.000394747,0.00007420427,0.001274711,0.00007740914,0.0004569583,0.00001255139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001171838,"about_ca_system_score_gemma":0.00006961019,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001573436,"about_ca_topic_score_gemma":0.00001898093,"domain_scores_codex":[0.9981388,0.0002389213,0.0004204184,0.0002302524,0.0006982486,0.0002733076],"domain_scores_gemma":[0.9992759,0.0001922187,0.0002051805,0.00006315231,0.00008162205,0.0001819334],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000703538,0.0002020479,0.001430172,0.00003242356,0.000001525683,0.00008922524,0.0002465081,0.0001544082,0.9895176,0.00001889182,0.000009018043,0.007594621],"study_design_scores_gemma":[0.001135079,0.0007564684,0.3911744,0.0001011666,0.000006409691,0.0002119127,0.0001286139,0.002415012,0.6038361,0.0000970576,0.00003094596,0.0001067858],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949903,0.00003024819,0.004314906,0.0001635157,0.0003216834,0.000112307,0.000001810725,0.00001547318,0.00004968664],"genre_scores_gemma":[0.9993349,0.0001026963,0.0001038381,0.0002092602,0.0001392359,4.332921e-7,1.43766e-7,0.0000135656,0.00009597422],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3897443,"threshold_uncertainty_score":0.4471906,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2963138386","doi":"10.1167/19.4.29","title":"Using deep learning to probe the neural code for images in primary visual cortex","year":2019,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":67,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Canadian Institute for Advanced Research","funders":"National Institutes of Health; U.S. National Library of Medicine; National Institute of General Medical Sciences; Canadian Institute for Advanced Research","keywords":"Unicode; Computer science; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.02633690741515225,"gpt":0.3249912870791114,"spread":0.2986543796639591,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004322963,0.00007487582,0.0001396165,0.0001149996,0.00009653685,0.00007672433,0.0001460444,0.00002825084,0.000009064095],"category_scores_gemma":[0.0002919867,0.00004636057,0.00007496656,0.0001820526,0.00001641097,0.0002847863,0.00005642699,0.00025954,0.000005248653],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000660694,"about_ca_system_score_gemma":0.00002391646,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000171351,"about_ca_topic_score_gemma":0.000002278339,"domain_scores_codex":[0.9990868,0.00009765436,0.0002744159,0.0001356107,0.0002497408,0.0001557874],"domain_scores_gemma":[0.9993187,0.0002816848,0.0002316803,0.00006356615,0.00006184385,0.00004249829],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002318396,0.00003842876,0.001660691,0.00001254337,8.141706e-7,0.000008562397,0.00007770763,0.00928681,0.9760208,0.00001939811,0.00003751511,0.0126049],"study_design_scores_gemma":[0.001750595,0.00376338,0.2384401,0.0002316355,0.00002001668,0.0003755378,0.0001955852,0.714233,0.03745886,0.0004233558,0.002865472,0.0002424442],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952418,0.00002087142,0.003093153,0.0007073931,0.00057891,0.0002825494,0.000001182439,0.000005663556,0.0000684437],"genre_scores_gemma":[0.9982738,0.00001210633,0.0006095797,0.0008279578,0.0001012218,0.000001053124,3.416547e-7,0.00001262812,0.0001612728],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9385619,"threshold_uncertainty_score":0.1890529,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2052175166","doi":"10.1167/9.8.496","title":"Mixed emotions: Holistic and analytic perception of facial expressions","year":2010,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":67,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Kwantlen Polytechnic University; University of Victoria","funders":"","keywords":"Perception; Psychology; Facial expression; Cognitive psychology; Social psychology; Communication; Neuroscience","retraction":null,"screen_n_in":null,"score":{"opus":0.07853013166251317,"gpt":0.3568123304579789,"spread":0.2782821987954658,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002515752,0.00006587313,0.0001393454,0.0002170568,0.00009983223,0.00003112565,0.00007891266,0.00007216122,0.000650925],"category_scores_gemma":[0.0007357501,0.00005028239,0.00007779826,0.000131791,0.00009692103,0.0002924055,0.00002206638,0.0002690259,0.00002566753],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001121607,"about_ca_system_score_gemma":0.00002722458,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003028949,"about_ca_topic_score_gemma":0.000004371004,"domain_scores_codex":[0.9991559,0.00008896188,0.0003145384,0.000099936,0.0002590879,0.0000815441],"domain_scores_gemma":[0.9993467,0.0001149762,0.0002507592,0.00008239115,0.0001107278,0.00009442867],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00003204487,0.00008172951,0.0002239316,0.00001006027,0.000001044828,0.000002339438,0.0002207093,0.000009189172,0.9675383,0.00005229572,0.0002757558,0.03155259],"study_design_scores_gemma":[0.001796801,0.0009102599,0.939424,0.0003804014,0.00008471039,0.0006102463,0.001182506,0.004535852,0.04528155,0.002617697,0.002941094,0.0002348686],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978773,0.0000058387,0.0008930689,0.0002455929,0.0005833111,0.00005232091,0.000009996686,0.000006785638,0.0003258017],"genre_scores_gemma":[0.9986515,0.0001869683,0.0008909332,0.00006002088,0.0001239471,3.910411e-7,0.000001041972,0.000005397364,0.00007978289],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9392001,"threshold_uncertainty_score":0.7127172,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W824117140","doi":"10.1167/15.5.1","title":"Modeling probability and additive summation for detection across multiple mechanisms under the assumptions of signal detection theory","year":2015,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":67,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"Canadian Institutes of Health Research","keywords":"Psychometric function; Summation; Weibull distribution; Monte Carlo method; Function (biology); Detection theory; SIGNAL (programming language); Mathematics; Computer science; Psychophysics; Statistical physics; Statistics; Physics; Perception","retraction":null,"screen_n_in":null,"score":{"opus":0.1088646181869008,"gpt":0.3689203382132337,"spread":0.260055720026333,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002128979,0.00008868476,0.0001349935,0.00007060183,0.0003102466,0.00006851481,0.00009405156,0.0000832245,0.000008602495],"category_scores_gemma":[0.0007832852,0.00005900511,0.0000794945,0.0001360712,0.00006405374,0.0004819198,0.00002938932,0.0001715539,0.000001574538],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007422364,"about_ca_system_score_gemma":0.00004248823,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004703345,"about_ca_topic_score_gemma":0.00002843715,"domain_scores_codex":[0.9987463,0.0002924324,0.0003695826,0.0001453736,0.0003276025,0.000118665],"domain_scores_gemma":[0.9987624,0.0003338071,0.0003337566,0.0000808695,0.0004185576,0.00007059469],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005231449,0.00006882531,0.000001223082,0.0000175728,0.000003530168,1.486843e-7,0.0009429545,0.01094628,0.9364592,0.0007293689,0.000002408683,0.05030528],"study_design_scores_gemma":[0.0007011459,0.0008179317,0.0001424727,0.00004709016,0.00001891054,0.00003641541,0.001942773,0.3882006,0.4843865,0.1236305,0.00001562317,0.00005995613],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4755925,0.00001010959,0.5240321,0.0000481257,0.000158833,0.0001379396,0.000007718865,0.00000847629,0.000004204358],"genre_scores_gemma":[0.9978288,0.00001421612,0.001970749,0.00007413991,0.00007593618,0.000008489751,7.897268e-7,0.00001011753,0.00001676897],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5222363,"threshold_uncertainty_score":0.2406159,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2067316362","doi":"10.1167/10.14.22","title":"Motion-induced blindness and microsaccades: Cause and effect","year":2010,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":66,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"National Institutes of Health; University of Haifa; Bundesministerium für Bildung und Forschung; National Eye Institute; York University","keywords":"Microsaccade; Perception; Psychology; Eye movement; Communication; Neuroscience","retraction":null,"screen_n_in":null,"score":{"opus":0.03802543797081305,"gpt":0.364280429938412,"spread":0.3262549919675989,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000470328,0.00007879567,0.0001277557,0.0001131659,0.0001404504,0.0001406734,0.00007799197,0.00008235328,0.000050978],"category_scores_gemma":[0.0003891758,0.00005502832,0.00002765515,0.00009213627,0.00004432118,0.0003046436,0.00002978712,0.0003436023,0.000007990203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005274637,"about_ca_system_score_gemma":0.00001783942,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001156964,"about_ca_topic_score_gemma":0.0000013924,"domain_scores_codex":[0.9993448,0.00007671752,0.0001814836,0.0001234988,0.0001821825,0.00009133479],"domain_scores_gemma":[0.9994943,0.000122141,0.0001558665,0.00006349416,0.00004668517,0.0001175344],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004701287,0.0000330334,0.000230721,0.00001700209,9.123726e-7,0.00001162832,0.000196209,2.501274e-7,0.9621263,0.00004869574,0.00003943224,0.03724878],"study_design_scores_gemma":[0.001408025,0.001463466,0.01873496,0.0001106828,0.00002372649,0.001039213,0.00004948743,0.0005900658,0.9750031,0.000716676,0.0007250594,0.0001355682],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987507,0.00001940534,0.0002308677,0.0003129908,0.0005714816,0.00004872822,7.45501e-7,0.000009606009,0.00005542591],"genre_scores_gemma":[0.9992782,0.00005226839,0.000230406,0.0002575755,0.0001147384,3.017605e-7,8.931416e-8,0.000008032995,0.00005840352],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03711321,"threshold_uncertainty_score":0.224399,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}