{"id":"W4244338716","doi":"10.1515/iupac.83.0318","title":"Glossary of Terms Used in Biomolecular ScreeningSponsoring body: IUPAC Chemistry and Human Health Division, Subcommittee on Medicinal Chemistry and Drug Development: see more details on p. 1157.","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Chemistry and Chemical Engineering","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Glossary; Chemical nomenclature; Context (archaeology); Multidisciplinary approach; Process (computing); Field (mathematics); Computer science; Data science; Drug discovery; Management science; Chemistry; Engineering; Sociology; Linguistics; Mathematics; History; Social science; Archaeology","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":[0.002172954,0.001896531,0.001805385,0.007511598,0.000975172,0.003259083,0.002429304,0.001532604,0.1301035],"category_scores_gemma":[0.01336996,0.0009080652,0.001468142,0.01500135,0.0005786193,0.003267799,0.002748075,0.002977104,0.151758],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002216192,"about_ca_system_score_gemma":0.003799203,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01515633,"about_ca_topic_score_gemma":0.02642572,"domain_scores_codex":[0.9977284,0.0003922473,0.0006776255,0.0004924274,0.0005263154,0.0001830626],"domain_scores_gemma":[0.993625,0.00231614,0.0009788505,0.001165647,0.001540641,0.0003736167],"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":[0.00004372642,0.00001299161,0.0005385317,0.001258587,0.00002026537,0.00001765286,0.00002319683,0.00009846227,0.00008569723,0.0005471343,0.9947616,0.002592134],"study_design_scores_gemma":[0.0001387337,0.00001142422,0.0035793,0.0007528869,0.000026038,0.0000828097,0.00006597747,0.0001141544,0.0001921787,0.001186583,0.9938208,0.00002909071],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000422071,0.00009909617,0.00008323346,0.00004463429,0.00001693795,0.00002207281,0.9988856,0.0001158722,0.0006902768],"genre_scores_gemma":[0.0001399776,0.0001256957,0.0002577763,0.00006643257,0.000005926398,0.0001379992,0.9988114,0.00005187154,0.0004030101],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1301035,"threshold_uncertainty_score":0.4352397,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006739250068503734,"score_gpt":0.3218554344138824,"score_spread":0.3151161843453786,"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."}}