{"id":"W4398713667","doi":"10.7910/dvn/itvlik/iacm82","title":"E7DB1968","year":2020,"lang":"nl","type":"dataset","venue":"Harvard Dataverse","topic":"Diverse Specialized Academic Research","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":["research_integrity","insufficient_payload"],"category_scores_codex":[0.001400155,0.0009676881,0.002006129,0.0009228433,0.0003737328,0.0007817923,0.004202877,0.001368001,0.4671814],"category_scores_gemma":[0.002372783,0.001291939,0.0006363544,0.00104237,0.0005087456,0.001084919,0.00339162,0.002934732,0.9892836],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006595691,"about_ca_system_score_gemma":0.0003459542,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009529701,"about_ca_topic_score_gemma":0.00002377331,"domain_scores_codex":[0.9933466,0.0001488209,0.002048553,0.002502472,0.000429188,0.001524391],"domain_scores_gemma":[0.9943412,0.0002275842,0.001324047,0.00298032,0.0001072313,0.00101963],"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":[0.0001689343,0.0001892441,0.0002290659,0.0003998678,0.0004804413,0.0005135011,0.00009760126,0.000006868767,0.000003985772,0.01689076,0.9806948,0.0003249731],"study_design_scores_gemma":[0.001791995,0.000148686,0.0001190729,0.0001231541,0.00009874499,0.00001494876,0.0001928538,0.0002519145,0.000009508916,0.001119471,0.9948529,0.001276775],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00002280852,0.00003292167,0.00009480854,0.0001706905,0.003660027,0.0009023408,0.9609563,0.00008444162,0.0340756],"genre_scores_gemma":[0.0000407074,0.01696023,0.0004677019,0.002115987,0.002849079,0.00005789911,0.9646142,0.0001330451,0.01276122],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.5221022,"threshold_uncertainty_score":0.9999284,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05892287407056033,"score_gpt":0.2637497410350108,"score_spread":0.2048268669644505,"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."}}