{"id":"W4252021813","doi":"10.1515/iupac.88.1488","title":"Viability","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Terminology; Relation (database); Computer science; Linguistics; Philosophy; Data mining","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":[0.001855927,0.001348974,0.001355682,0.0035435,0.001185429,0.004403477,0.002775041,0.001981681,0.275286],"category_scores_gemma":[0.01946665,0.0006402059,0.001817608,0.006263646,0.0004428078,0.003677859,0.002906207,0.001964772,0.2233263],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001894674,"about_ca_system_score_gemma":0.003720961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01807186,"about_ca_topic_score_gemma":0.02724153,"domain_scores_codex":[0.9970798,0.0004801542,0.0006504058,0.0008315739,0.0006541737,0.0003038012],"domain_scores_gemma":[0.992367,0.002264139,0.0008072029,0.001760308,0.002419161,0.0003823095],"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":[0.000132398,0.00001557437,0.001504345,0.001270087,0.00003385081,0.00002257504,0.00004107191,0.0001081641,0.00005939162,0.001900801,0.9823011,0.01261054],"study_design_scores_gemma":[0.00009565873,0.00001295372,0.002720769,0.0009534271,0.00002606616,0.00005949933,0.00009786401,0.00009358647,0.0001035553,0.001985005,0.9938318,0.00001983747],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000193074,0.0002220031,0.000187953,0.0002579221,0.00009257786,0.00005983047,0.9918961,0.0003069963,0.006783484],"genre_scores_gemma":[0.0008753632,0.0002880521,0.0005738022,0.0003922301,0.0000345435,0.0002816605,0.9923595,0.0001611646,0.005033814],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.275286,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0238938421122965,"score_gpt":0.4598363290527138,"score_spread":0.4359424869404173,"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."}}