{"id":"W6926632692","doi":"10.25384/sage.c.4205225.v1","title":"Political parties in Canada: What determines entry, exit and the duration of their lives?","year":2018,"lang":"en","type":"other","venue":"Sage Journals Data","topic":"Microbial Natural Products and Biosynthesis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Margin (machine learning); Politics; Immigration; Hazard model; Duration (music)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006800859,0.0001455587,0.0002933681,0.0014691,0.004234442,0.002038891,0.000786219,0.0004651197,0.005619397],"category_scores_gemma":[0.0028873,0.0001311014,0.000328645,0.002500834,0.00131019,0.000502949,0.001267832,0.001059032,0.0004099399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02811674,"about_ca_system_score_gemma":0.02590225,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9886485,"about_ca_topic_score_gemma":0.995948,"domain_scores_codex":[0.9990391,0.00007062915,0.00001713913,0.00007423419,0.0001933818,0.0006055402],"domain_scores_gemma":[0.9980117,0.0001994875,0.0003551947,0.00005949155,0.0005020757,0.0008719966],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000426051,0.00008796077,0.9161316,0.000058184,0.00003926461,0.00032213,0.01898554,0.0002651892,0.0004061761,0.004877556,0.005739899,0.05266042],"study_design_scores_gemma":[0.000006343891,0.00002376421,0.9735831,0.00005636042,0.00001377638,0.00006675854,0.01719465,0.0003135155,0.00009915805,0.000290362,0.008330363,0.00002187921],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.9871617,0.0006925035,0.0001195637,0.0008610599,0.00001644447,0.00002298342,0.001612632,0.000006725609,0.009506359],"genre_scores_gemma":[0.9932665,0.0004536037,0.0001028433,0.00008724994,0.000006880033,0.000009758925,0.0007296046,0.000006116509,0.005337576],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.02811674,"threshold_uncertainty_score":0.2040022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03738444453853855,"score_gpt":0.2769285158797043,"score_spread":0.2395440713411657,"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."}}