{"id":"W4248763871","doi":"10.1515/iupac.79.1394","title":"Hemolysis","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; Toxicology; Computer science; 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":[0.001248564,0.001513197,0.001733673,0.002859658,0.0006441931,0.002752445,0.001916145,0.001515243,0.09068993],"category_scores_gemma":[0.01066315,0.0004349511,0.002146763,0.003433766,0.0002510766,0.001440476,0.00134588,0.001554893,0.0641095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00128269,"about_ca_system_score_gemma":0.002100592,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008743248,"about_ca_topic_score_gemma":0.0151606,"domain_scores_codex":[0.998398,0.0002244061,0.000403643,0.000535225,0.0003157974,0.0001230662],"domain_scores_gemma":[0.9959319,0.001227687,0.0008156206,0.0008488055,0.0009694531,0.0002064164],"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":[0.0008292773,0.0000559862,0.006322032,0.004534759,0.0002386675,0.0000559058,0.0000260991,0.0003737042,0.0002481618,0.0006732965,0.9639274,0.02271474],"study_design_scores_gemma":[0.0009962936,0.00009517764,0.02446683,0.002867179,0.0003922427,0.0004245361,0.00008042002,0.0006570445,0.0009121477,0.003050146,0.9659723,0.00008566147],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003311371,0.0004961527,0.000119133,0.00008704251,0.00004345662,0.00004418029,0.9969354,0.0002569533,0.001686695],"genre_scores_gemma":[0.001441991,0.0005164873,0.0004853875,0.0002445558,0.00003077801,0.0002177835,0.9955011,0.00005376474,0.001508215],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09068993,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01155571875508567,"score_gpt":0.3837056460334986,"score_spread":0.372149927278413,"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."}}