{"id":"W2602162772","doi":"","title":"実地医療の現場から：閉経後骨粗鬆症の内服治療の現状、そして今後の展望（総説）","year":2005,"lang":"ja","type":"article","venue":"Pharma Medica","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":[0.001285969,0.0002234004,0.0002173744,0.000672267,0.002127906,0.002728773,0.0004471519,0.001170765,0.0188244],"category_scores_gemma":[0.002646625,0.0002438577,0.0002755341,0.0003567157,0.003537358,0.001869238,0.0007048246,0.00141386,0.005233794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001773083,"about_ca_system_score_gemma":0.002302128,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004696885,"about_ca_topic_score_gemma":0.003736414,"domain_scores_codex":[0.9990978,0.0001097581,0.00004880743,0.0001642283,0.0004797837,0.00009963791],"domain_scores_gemma":[0.9983538,0.0004069499,0.0001726587,0.0001546136,0.0007030833,0.0002087629],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002342238,0.000239354,0.005212744,0.0003319442,0.00006748559,0.0006126991,0.003228548,0.001300788,0.03184521,0.7390598,0.02081832,0.1970489],"study_design_scores_gemma":[0.00007744032,0.0005296811,0.01853579,0.0002410873,0.0001160936,0.001254422,0.005953721,0.001675651,0.07301744,0.3338977,0.5645667,0.0001343526],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"review","genre_scores_codex":[0.1156787,0.005955546,0.03048023,0.01599484,0.001807194,0.0001997361,0.0002713953,0.0001744513,0.8294379],"genre_scores_gemma":[0.7567862,0.004041292,0.01816111,0.003607331,0.0007872791,0.0001029006,0.0001614175,0.00005462812,0.2162979],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.0188244,"threshold_uncertainty_score":0.06297386,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01511952508600746,"score_gpt":0.2586597855071774,"score_spread":0.2435402604211699,"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."}}