{"id":"W7097253348","doi":"","title":"On probability matching priors / Àpropos des lois a priori appariées en probabilité","year":2013,"lang":"en","type":"article","venue":"","topic":"Census and Population Estimation","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Prior probability; A priori and a posteriori; Matching (statistics); Range (aeronautics); Service (business); Productivity","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":[0.02577784,0.00163517,0.002914311,0.005376846,0.001849734,0.005880023,0.004580365,0.003305674,0.02339801],"category_scores_gemma":[0.1395584,0.002357268,0.002489343,0.005399983,0.008764934,0.01316288,0.004605179,0.008342308,0.003757491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003887925,"about_ca_system_score_gemma":0.003217998,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007782373,"about_ca_topic_score_gemma":0.009099644,"domain_scores_codex":[0.9883891,0.007653099,0.000441897,0.001429478,0.001657116,0.0004292924],"domain_scores_gemma":[0.8768209,0.1125818,0.002330376,0.004831636,0.002474002,0.0009612944],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00009743229,0.00005776197,0.0008769383,0.0001659282,0.00006378088,0.0001224513,0.0002353145,0.0521044,0.0001781897,0.898846,0.005124567,0.04212721],"study_design_scores_gemma":[0.00002239125,0.00002402501,0.0003901601,0.0001661241,0.00002592694,0.00009238899,0.00005563653,0.136067,0.000225509,0.8588032,0.004097112,0.00003048898],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007303168,0.001636938,0.9755205,0.001800996,0.0002082376,0.00008382806,0.0002386006,0.0002027623,0.01300487],"genre_scores_gemma":[0.2712287,0.007910154,0.6728352,0.001741002,0.003327651,0.001326386,0.001623823,0.001229784,0.03877733],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02577784,"threshold_uncertainty_score":0.1363279,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0425836796855702,"score_gpt":0.3061820271627247,"score_spread":0.2635983474771545,"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."}}