{"id":"W4243977334","doi":"10.1515/iupac.83.0453","title":"Screen","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); Field (mathematics); Computer science; Process (computing); Multidisciplinary approach; Data science; Management science; Sociology; Engineering; Biology; Linguistics; Social science; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001460802,0.002421777,0.001541423,0.002603089,0.001171314,0.002852466,0.003760019,0.00185627,0.06785434],"category_scores_gemma":[0.005391091,0.0006717898,0.001925064,0.003363227,0.0004577437,0.001978387,0.00227405,0.002258305,0.1354885],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001833617,"about_ca_system_score_gemma":0.002511008,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0158334,"about_ca_topic_score_gemma":0.0396399,"domain_scores_codex":[0.9982973,0.0002487717,0.0002234985,0.0005617968,0.0004622411,0.0002064852],"domain_scores_gemma":[0.997787,0.0003878165,0.0002113596,0.0007958058,0.0006272743,0.0001907062],"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":[0.0001413117,0.00003668631,0.001552512,0.0006205771,0.00003939491,0.00002855101,0.0000229102,0.0003208205,0.0001947753,0.001012449,0.9909635,0.005066575],"study_design_scores_gemma":[0.0002089371,0.00003192013,0.004030769,0.0002780189,0.00003989963,0.0001326136,0.0000716932,0.0007221066,0.0008563636,0.002263673,0.99133,0.00003398456],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003174801,0.0001117063,0.0002949424,0.00009860911,0.0000408584,0.00003981824,0.995641,0.001079545,0.002376084],"genre_scores_gemma":[0.0004477329,0.00006097442,0.0005178829,0.00009178826,0.000005865354,0.00008006296,0.9975713,0.0001035075,0.001120949],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9321457,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0221830991466521,"score_gpt":0.4340770008921213,"score_spread":0.4118939017454691,"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."}}