{"id":"W4252917118","doi":"10.1515/iupac.83.0368","title":"False Negative","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Glossary; Context (archaeology); Computer science; Field (mathematics); Multidisciplinary approach; Process (computing); Data science; Management science; Sociology; Engineering; Linguistics; Biology; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005743479,0.002222354,0.002689432,0.004141344,0.002026908,0.004858941,0.004015195,0.002962157,0.05318988],"category_scores_gemma":[0.03653275,0.0007694928,0.002974338,0.003815706,0.001252082,0.002421875,0.002451327,0.003635657,0.04754449],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001936981,"about_ca_system_score_gemma":0.002488262,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008918663,"about_ca_topic_score_gemma":0.01839485,"domain_scores_codex":[0.9896222,0.001682642,0.002046092,0.00337232,0.002183525,0.001093176],"domain_scores_gemma":[0.9802115,0.007675398,0.001971302,0.006398151,0.003205761,0.0005379278],"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":[0.001137704,0.0001508984,0.02264632,0.002055099,0.0003232843,0.0004835473,0.00006831308,0.001066437,0.0003996676,0.00234863,0.9267298,0.04259037],"study_design_scores_gemma":[0.00130963,0.0002133744,0.02734164,0.002022841,0.0006235896,0.004846643,0.0002622296,0.005845509,0.003607565,0.02157631,0.9321383,0.0002124086],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01100174,0.004509536,0.006194642,0.001212104,0.002267673,0.0007337349,0.9549293,0.003485801,0.0156654],"genre_scores_gemma":[0.02343907,0.001097026,0.006512241,0.00252543,0.0003780022,0.0009866462,0.9557512,0.0006104714,0.008699975],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05318988,"threshold_uncertainty_score":0.1779379,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02169331443517463,"score_gpt":0.4322660487283823,"score_spread":0.4105727342932076,"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."}}