{"id":"W3189131910","doi":"","title":"P148親と家族育児家庭提供者の家庭および育児における子供の食事品質【JST・京大機械翻訳】","year":2019,"lang":"ja","type":"article","venue":"Journal of Nutrition Education and Behavior","topic":"Military Technology and Strategies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0003300385,0.0001885825,0.0001735933,0.0003422301,0.0005318046,0.001036541,0.0002787797,0.000667651,0.05406879],"category_scores_gemma":[0.001728247,0.0001128541,0.0002204663,0.0002325668,0.0008579424,0.0006441453,0.0002986342,0.0008412837,0.007839093],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003019529,"about_ca_system_score_gemma":0.0005694235,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001469635,"about_ca_topic_score_gemma":0.001243726,"domain_scores_codex":[0.9998301,0.00002924722,0.0000158159,0.00003176037,0.00006961729,0.00002331985],"domain_scores_gemma":[0.9993585,0.0001936056,0.0001113236,0.00004390022,0.0002195752,0.00007313373],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.002387575,0.0009374697,0.04423044,0.0008167804,0.0001479268,0.008892017,0.003224469,0.0005845893,0.1164113,0.0904355,0.09270439,0.6392275],"study_design_scores_gemma":[0.0003064985,0.001297191,0.2081134,0.0005156461,0.000206212,0.01404302,0.00576265,0.002186633,0.1136139,0.1166225,0.5372295,0.0001028144],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3658832,0.002776331,0.0118017,0.0132599,0.002840407,0.0002181856,0.001282804,0.0002462744,0.6016912],"genre_scores_gemma":[0.8296919,0.001593685,0.007084122,0.00154669,0.0008724242,0.0001125288,0.0006123394,0.00008845847,0.1583978],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05406879,"threshold_uncertainty_score":0.1808781,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01021966590140139,"score_gpt":0.2610370213728911,"score_spread":0.2508173554714898,"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."}}