{"id":"W4234896089","doi":"10.1515/iupac.88.0581","title":"Centromere, Acrocentric","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Chromosomal and Genetic Variations","field":"Agricultural and Biological Sciences","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; Biology; Linguistics; Data mining; Philosophy","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000950355,0.001670616,0.001571575,0.00540732,0.001141208,0.003098362,0.002485947,0.001604069,0.128081],"category_scores_gemma":[0.009936648,0.0007106839,0.001116347,0.009536114,0.0005712909,0.002472418,0.002175768,0.00181332,0.09738488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000959256,"about_ca_system_score_gemma":0.002431855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01771686,"about_ca_topic_score_gemma":0.03126508,"domain_scores_codex":[0.9988537,0.0001628562,0.0002573674,0.0004025491,0.0002052196,0.0001184795],"domain_scores_gemma":[0.9964494,0.001280253,0.0006282402,0.0008390291,0.0005935168,0.0002095481],"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":[0.0001660865,0.00001523358,0.002779735,0.002614654,0.00005236052,0.00007471606,0.0000585708,0.0002475865,0.0003034971,0.001078414,0.9843203,0.008288806],"study_design_scores_gemma":[0.0001436436,0.00001443895,0.006748877,0.0006844515,0.00004331055,0.0001764436,0.00007879509,0.0001043175,0.0002149272,0.002149101,0.9896136,0.00002806184],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001909646,0.0003413278,0.0001680885,0.00007427013,0.00004319123,0.00001564683,0.9972966,0.0002446885,0.001625155],"genre_scores_gemma":[0.0007304958,0.0003412132,0.0005205885,0.0001357347,0.0000154843,0.0001049456,0.9970495,0.00009138363,0.001010655],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.871919,"threshold_uncertainty_score":0.4284738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01768321247201902,"score_gpt":0.3641490128602287,"score_spread":0.3464658003882096,"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."}}