{"id":"W4241247603","doi":"10.1515/iupac.79.0768","title":"Additive Effect","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"History and advancements in chemistry","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Computer science; Hazard; Toxicology; Chemistry; Philosophy; Biology; Linguistics; Organic chemistry","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":[0.001624501,0.00262995,0.002075887,0.003558273,0.001003391,0.003221079,0.003056818,0.001846825,0.1743517],"category_scores_gemma":[0.01217231,0.0007186928,0.004309995,0.00402288,0.0004054754,0.002469037,0.001882213,0.002115049,0.1263707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00138939,"about_ca_system_score_gemma":0.002396823,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0142918,"about_ca_topic_score_gemma":0.03016138,"domain_scores_codex":[0.997458,0.0003960697,0.00039766,0.001059264,0.0004798165,0.0002092813],"domain_scores_gemma":[0.9962713,0.001506073,0.0003520459,0.0009275991,0.0007775438,0.0001654604],"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":[0.0006770611,0.00009192448,0.006513261,0.003826726,0.0004618129,0.00007095749,0.00003759506,0.001152964,0.0003973386,0.002686751,0.9503842,0.03369941],"study_design_scores_gemma":[0.000397901,0.00006461469,0.00772135,0.0006894568,0.000399093,0.0001813346,0.00005900755,0.0006328133,0.0005437135,0.004160132,0.9850959,0.00005475673],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004830443,0.0007803739,0.0005809263,0.0001401232,0.0001737871,0.00006216974,0.9924074,0.000734172,0.004638094],"genre_scores_gemma":[0.003156477,0.0007400342,0.001849182,0.0004563704,0.00007785456,0.0002692639,0.9873573,0.0002807227,0.00581279],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1743517,"threshold_uncertainty_score":0.5832646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007724934290326284,"score_gpt":0.3780338138859802,"score_spread":0.3703088795956539,"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."}}