{"id":"W4242239960","doi":"10.1515/iupac.79.1574","title":"Mass Median Diameter","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; Hazard; Computer science; Multidisciplinary approach; Toxicology; Chemistry; Philosophy; Biology; Linguistics; Sociology; Social science","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":[0.0009461783,0.002777547,0.00220512,0.004987129,0.0008516832,0.003626015,0.002969954,0.001673498,0.07845543],"category_scores_gemma":[0.007154485,0.0005254236,0.002268041,0.006060457,0.0004444064,0.002601667,0.001796559,0.001798042,0.1554169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001597225,"about_ca_system_score_gemma":0.001890728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01556162,"about_ca_topic_score_gemma":0.02503936,"domain_scores_codex":[0.9983281,0.0001545359,0.0002408435,0.0007364386,0.000366464,0.0001735742],"domain_scores_gemma":[0.9976872,0.0005458752,0.0002698664,0.000612128,0.0007223689,0.0001624578],"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":[0.0001535707,0.00003171173,0.002969628,0.0008157403,0.0000743921,0.00002844671,0.00001661073,0.0006308445,0.0001476719,0.0006451597,0.9835955,0.01089053],"study_design_scores_gemma":[0.0002338153,0.00004350967,0.009175109,0.0004195971,0.00007848354,0.0002205374,0.00009970544,0.001437444,0.0006660619,0.003213822,0.9843584,0.00005361559],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003025673,0.000291226,0.0001703302,0.00007708144,0.00006929961,0.00001864372,0.9969149,0.0005419787,0.001613959],"genre_scores_gemma":[0.001108837,0.0002439769,0.0005764327,0.00009213736,0.00003372889,0.00007214206,0.9964982,0.0000826092,0.001291949],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07845543,"threshold_uncertainty_score":0.2624595,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01267887600601479,"score_gpt":0.3771074445771921,"score_spread":0.3644285685711773,"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."}}