{"id":"W4256308008","doi":"10.1515/iupac.88.1301","title":"Rostral","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"","field":"","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001850127,0.001471431,0.001337603,0.004280287,0.00113679,0.004246109,0.002576795,0.001932204,0.2632438],"category_scores_gemma":[0.01859186,0.0006815767,0.001853306,0.00809407,0.0004417226,0.003648569,0.00273215,0.001965876,0.2777899],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002153961,"about_ca_system_score_gemma":0.004196099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0204116,"about_ca_topic_score_gemma":0.03160575,"domain_scores_codex":[0.9966935,0.0005169709,0.000701165,0.001004375,0.0007252775,0.0003587711],"domain_scores_gemma":[0.9921374,0.001867537,0.0007626698,0.001832707,0.002989295,0.0004103995],"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":[0.00007517051,0.00001084035,0.0009042702,0.0009090703,0.00002133954,0.00001316756,0.00002452898,0.00007216659,0.00005847501,0.001052021,0.9902309,0.006628062],"study_design_scores_gemma":[0.00008593525,0.00001095982,0.002405046,0.0007440326,0.000019198,0.00004408441,0.00008044403,0.00009636342,0.0001203639,0.001355693,0.9950182,0.00001960525],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001023226,0.0001157022,0.000128137,0.0001609365,0.00006432703,0.00003786932,0.9955435,0.0002699512,0.003577202],"genre_scores_gemma":[0.0003985628,0.0001526461,0.000408852,0.0002465115,0.00002135023,0.0001736356,0.9955152,0.0001271429,0.002956086],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7367562,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02566975484346257,"score_gpt":0.4717222152897979,"score_spread":0.4460524604463353,"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."}}