{"id":"W4237632648","doi":"10.1002/9781118445112.stat05834","title":"Conditionality Principle","year":2014,"lang":"en","type":"other","venue":"Wiley StatsRef: Statistics Reference Online","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Conditionality; Encyclopedia; Citation; Library science; Computer science; Operations research; Political science; Mathematics; Law","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004990364,0.001252411,0.001478364,0.0006837191,0.0001646835,0.0001347749,0.001069124,0.0008027857,0.04923046],"category_scores_gemma":[0.00084946,0.001235541,0.0001207588,0.0004517828,0.0007953562,0.00008328154,0.0003406667,0.001282012,0.02612986],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004148842,"about_ca_system_score_gemma":0.0008119195,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007465358,"about_ca_topic_score_gemma":0.005831286,"domain_scores_codex":[0.9939212,0.000476567,0.001193732,0.001516452,0.001719364,0.001172719],"domain_scores_gemma":[0.9949378,0.0004604371,0.001571667,0.001844789,0.0005505405,0.0006347178],"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":[0.0000450826,0.0004876963,0.0001870007,0.0003565067,0.0002348259,0.00006207038,0.00001696999,0.00001213302,0.0000492199,0.1711555,0.8254251,0.001967814],"study_design_scores_gemma":[0.001127468,0.0001833237,0.001094765,0.000733425,0.000228794,0.00001698806,0.00001643698,0.0006134547,0.000007269729,0.0185899,0.9760214,0.001366789],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.00003556283,0.0005978669,0.08177743,0.0000558714,0.0007154517,0.001011764,0.6147898,0.001506829,0.2995094],"genre_scores_gemma":[0.000463069,0.0007290581,0.2041995,0.0003603345,0.001071966,0.0001093804,0.1770079,0.003043266,0.6130155],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.437782,"threshold_uncertainty_score":0.9990094,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05049268381664106,"score_gpt":0.3578373398320252,"score_spread":0.3073446560153841,"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."}}