{"id":"W4248222343","doi":"10.1515/iupac.88.1384","title":"Surfactant, Pulmonary","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Environmental Chemistry and Analysis","field":"Environmental Science","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":[0.0007385474,0.0009087144,0.00123843,0.003178941,0.0005461252,0.002437392,0.001444643,0.001195431,0.1160197],"category_scores_gemma":[0.0103568,0.0003283481,0.001352999,0.005875889,0.0002834812,0.002410397,0.001097519,0.001548377,0.06137092],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001004648,"about_ca_system_score_gemma":0.002300496,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01090934,"about_ca_topic_score_gemma":0.01470947,"domain_scores_codex":[0.9987043,0.0001871173,0.0004059545,0.0003535372,0.0002410365,0.0001079619],"domain_scores_gemma":[0.9971966,0.0009834497,0.0006020204,0.0004263284,0.0006390653,0.0001525737],"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":[0.0005757525,0.00003870368,0.008123815,0.01012631,0.0002220215,0.0001242469,0.00004394879,0.0002639353,0.0003221257,0.002180655,0.9177396,0.06023884],"study_design_scores_gemma":[0.0003952373,0.00003996833,0.01430541,0.003505819,0.0002094908,0.0004247489,0.00008079778,0.0002020418,0.0002508018,0.003985937,0.9765669,0.00003280104],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0006600547,0.003818249,0.0002977971,0.0004737646,0.0001395776,0.00008581898,0.9868968,0.0002614261,0.007366448],"genre_scores_gemma":[0.005464301,0.005062236,0.001340881,0.0009400093,0.0001518936,0.000295448,0.9811554,0.0001413799,0.005448435],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1160197,"threshold_uncertainty_score":0.3881245,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009938854250633193,"score_gpt":0.3623252927578778,"score_spread":0.3523864385072446,"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."}}