{"id":"W4238244082","doi":"10.1515/iupac.79.0898","title":"Biased Sample","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; Multidisciplinary approach; Toxicology; Chemistry; Biology; Philosophy; 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":[0.005228628,0.001695653,0.002243343,0.003490236,0.001314718,0.003206379,0.004063633,0.002878558,0.1261342],"category_scores_gemma":[0.04619589,0.0006357881,0.002594621,0.005059139,0.0006595298,0.00219772,0.002226369,0.002325581,0.1155516],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002173743,"about_ca_system_score_gemma":0.004040143,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01422731,"about_ca_topic_score_gemma":0.02400957,"domain_scores_codex":[0.993389,0.001945101,0.001031606,0.002061481,0.001031646,0.0005411301],"domain_scores_gemma":[0.9858509,0.00535965,0.001165808,0.003398685,0.00380075,0.0004241946],"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":[0.0004880918,0.00007191566,0.005981221,0.001615129,0.0001843413,0.00006683628,0.00003888311,0.0004785478,0.0001053575,0.00142808,0.973044,0.01649762],"study_design_scores_gemma":[0.001548105,0.00008426733,0.01035483,0.001367286,0.0003121469,0.0002849126,0.0001837311,0.001346539,0.0004429459,0.006248235,0.9777637,0.00006342593],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001297922,0.0008455031,0.0009850983,0.0005912862,0.0003575638,0.0003571837,0.9904146,0.0005410453,0.004609718],"genre_scores_gemma":[0.003962736,0.0003123665,0.001864667,0.0009541473,0.0001334769,0.001451487,0.9867781,0.0001656084,0.004377241],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1261342,"threshold_uncertainty_score":0.4219611,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01906213838916488,"score_gpt":0.3957715304272613,"score_spread":0.3767093920380964,"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."}}