{"id":"W4241224820","doi":"10.1037/e403122005-002","title":"PsySR at APA Toronto 2003","year":2003,"lang":"en","type":"dataset","venue":"PsycEXTRA Dataset","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Library science; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0006202006,0.0006289842,0.000489947,0.00007740188,0.0002054524,0.0001105438,0.001436999,0.001044615,0.003648628],"category_scores_gemma":[0.0005721549,0.0005613834,0.000152746,0.000165722,0.0003675718,0.00001060378,0.0007754665,0.0003949773,0.002179182],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001327801,"about_ca_system_score_gemma":0.0003627749,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005332166,"about_ca_topic_score_gemma":0.004321166,"domain_scores_codex":[0.9963186,0.00015718,0.0007364951,0.0009179052,0.0008697338,0.001000116],"domain_scores_gemma":[0.9963343,0.00002260376,0.0002600904,0.002537461,0.0001996715,0.0006458871],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009464326,0.0001860453,0.000007240325,0.0002652816,0.0001473422,0.00001809605,0.000003647199,3.558936e-7,0.001073977,0.000001656741,0.9971967,0.001005063],"study_design_scores_gemma":[0.0006827459,0.0004212998,0.00001629685,0.00003395749,0.00008368617,0.00006691342,0.00002744512,0.000004309813,0.001453149,0.000007880281,0.9965122,0.0006901206],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003428744,0.003566897,0.00005275028,0.00009510289,0.001244827,0.0005341798,0.993735,0.00001039919,0.0007265854],"genre_scores_gemma":[0.000004164904,0.01367538,0.0006048683,0.001817112,0.0007326397,0.0000679108,0.9809583,0.00004104993,0.002098617],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01277671,"threshold_uncertainty_score":0.9996837,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01982289889403421,"score_gpt":0.3165125298720166,"score_spread":0.2966896309779824,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}