{"id":"W4240310825","doi":"10.1515/iupac.88.0416","title":"Agenesis","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":[0.001175069,0.001223098,0.00143136,0.00409524,0.0007277757,0.002092553,0.001421916,0.001187483,0.1252973],"category_scores_gemma":[0.009921536,0.0005340717,0.001854031,0.005318132,0.000540182,0.001888861,0.001737309,0.001700961,0.05509381],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001069693,"about_ca_system_score_gemma":0.002160889,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01003307,"about_ca_topic_score_gemma":0.01635985,"domain_scores_codex":[0.9982197,0.0002416287,0.0006268503,0.000454915,0.0002842405,0.0001726207],"domain_scores_gemma":[0.996108,0.001254496,0.001088928,0.0007232878,0.0006377093,0.0001876195],"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":[0.0003287826,0.00001878654,0.006406361,0.004527331,0.0001199792,0.0002063844,0.00006028815,0.0002188087,0.0001653281,0.002156405,0.9613736,0.02441795],"study_design_scores_gemma":[0.0002198862,0.0000289569,0.01294739,0.00422941,0.00009216957,0.001021106,0.0001643498,0.0001128751,0.0002014982,0.002897886,0.9780442,0.00004008728],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0006772715,0.001742091,0.0003253696,0.0002851546,0.0001945648,0.000121062,0.9891618,0.0001973105,0.007295378],"genre_scores_gemma":[0.004136044,0.003759037,0.001437675,0.0007412951,0.0001182725,0.000503258,0.9839892,0.0001877082,0.005127573],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8747027,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02835131378325725,"score_gpt":0.468805698082658,"score_spread":0.4404543842994008,"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."}}