{"id":"W4238886361","doi":"10.1515/iupac.79.2041","title":"Spreader","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"","field":"","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","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":[0.001533976,0.002044808,0.001682993,0.004816986,0.0009177961,0.003793982,0.002879939,0.001879168,0.2038028],"category_scores_gemma":[0.01161729,0.0007254011,0.001940906,0.007605765,0.0003738078,0.002860353,0.002657036,0.001948343,0.3202416],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001235223,"about_ca_system_score_gemma":0.00244734,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01311449,"about_ca_topic_score_gemma":0.02671758,"domain_scores_codex":[0.9981753,0.0003108791,0.0003182703,0.000621192,0.0003670829,0.0002072324],"domain_scores_gemma":[0.9957203,0.001131634,0.0004536994,0.001229783,0.001139219,0.0003253229],"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":[0.00007773025,0.00001338576,0.0007686409,0.0007727672,0.0000350226,0.00001285795,0.00002094311,0.0001487011,0.00007950909,0.0005536649,0.9926069,0.004909823],"study_design_scores_gemma":[0.0001811761,0.0000167921,0.002050024,0.000383475,0.00003377761,0.00004186433,0.00006304179,0.0002231075,0.000167316,0.001366314,0.9954502,0.00002304863],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007832245,0.00008258224,0.00009316415,0.00007291681,0.00003281798,0.00001650711,0.9980597,0.0004643502,0.0010996],"genre_scores_gemma":[0.000258861,0.00009489963,0.0003426265,0.0001019829,0.00001330361,0.00008284029,0.9975434,0.0001491907,0.001412897],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2038028,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01975388631479114,"score_gpt":0.4278922474574278,"score_spread":0.4081383611426366,"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."}}