{"id":"W2115854441","doi":"10.1002/cjs.11235","title":"Combined composite likelihood","year":2014,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Composite number; Materials science; Composite material","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.01463743,0.001676638,0.003105204,0.003663488,0.001067996,0.006629889,0.004540617,0.002691145,0.02768083],"category_scores_gemma":[0.06086342,0.0009602595,0.002678144,0.004916714,0.002406896,0.006989156,0.005532756,0.005467657,0.006306641],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002352452,"about_ca_system_score_gemma":0.00354411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00306715,"about_ca_topic_score_gemma":0.00388546,"domain_scores_codex":[0.9880199,0.007746674,0.0003995798,0.001404206,0.002004853,0.0004247256],"domain_scores_gemma":[0.9526334,0.03315001,0.001845017,0.006394897,0.004781574,0.001195024],"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":[0.0007297892,0.0001671281,0.007089298,0.000819582,0.0006456529,0.0006502577,0.0004161109,0.1572813,0.001840132,0.5215999,0.0347149,0.2740458],"study_design_scores_gemma":[0.00006572918,0.0001420272,0.00180766,0.0002067919,0.0001699023,0.0008049396,0.0001451005,0.4256992,0.001650139,0.5427732,0.0264129,0.0001224645],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003369025,0.0007430966,0.9853388,0.0007380194,0.0001211779,0.00007387577,0.0007593705,0.0005429232,0.008313704],"genre_scores_gemma":[0.2679002,0.001183031,0.7052293,0.0007407805,0.0006809392,0.0004717404,0.003072304,0.001255042,0.01946655],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02768083,"threshold_uncertainty_score":0.09260154,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05080023715616969,"score_gpt":0.2985299299451911,"score_spread":0.2477296927890214,"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."}}