{"id":"W4241385094","doi":"10.1515/iupac.79.1391","title":"Hemoglobin","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; Computer science; 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":[0.0014692,0.001950754,0.001427771,0.003035926,0.0009679267,0.003291988,0.002867943,0.00190695,0.1732769],"category_scores_gemma":[0.01092843,0.0005653842,0.001774282,0.004658868,0.0003649241,0.002254606,0.001918221,0.001741261,0.2401166],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001455712,"about_ca_system_score_gemma":0.002681077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01469414,"about_ca_topic_score_gemma":0.02943076,"domain_scores_codex":[0.9979254,0.0003394501,0.0002952226,0.0008017924,0.0004116895,0.0002263888],"domain_scores_gemma":[0.9960014,0.0009779527,0.0003373409,0.00113354,0.001244945,0.0003048778],"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":[0.0001088297,0.00002122188,0.001173009,0.0006202402,0.0000315194,0.00001613238,0.00001536337,0.0001489345,0.00007067775,0.0005460824,0.990435,0.006813088],"study_design_scores_gemma":[0.000171525,0.00002166091,0.003081763,0.0004103897,0.00003590921,0.00006498878,0.00006469702,0.0002835528,0.000218722,0.001742261,0.9938796,0.00002493046],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001275798,0.0001124864,0.0001256912,0.0001098085,0.00004999609,0.00002670705,0.9972198,0.0004205212,0.00180748],"genre_scores_gemma":[0.0003654653,0.0000858292,0.0003755357,0.0001512668,0.00001369426,0.0001042116,0.9974346,0.00007685834,0.001392583],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1732769,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01203238333041812,"score_gpt":0.3825474722399095,"score_spread":0.3705150889094914,"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."}}