{"id":"W2492965065","doi":"","title":"吸入指導勉強会による薬剤師の意識変化について：京都府薬剤師会伏見支部吸入指導勉強会アンケートからの検討（研究）","year":2014,"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0009491634,0.0006378836,0.0007193391,0.0003019536,0.0002740365,0.00005183708,0.00102331,0.000699433,0.006380558],"category_scores_gemma":[0.0003597179,0.0006501671,0.0002226388,0.0005074266,0.0005509657,0.0003092141,0.0001713572,0.001573755,0.002866831],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009248233,"about_ca_system_score_gemma":0.00008197354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005959086,"about_ca_topic_score_gemma":0.00002558039,"domain_scores_codex":[0.9966657,0.0001936791,0.0007446098,0.0006592568,0.0005844737,0.00115225],"domain_scores_gemma":[0.998092,0.0003301818,0.00009923658,0.0009086842,0.00007291468,0.0004970075],"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":[0.0002205054,0.0007108165,0.001972453,0.00298537,0.001933444,0.0005342826,0.007030978,0.002563707,0.01560164,0.2376582,0.425011,0.3037775],"study_design_scores_gemma":[0.003737999,0.0004542134,0.001317519,0.0004895781,0.0005023724,0.0002014144,0.001133303,0.1002058,0.008321432,0.02817361,0.8535615,0.001901331],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.09092877,0.02423622,0.009615328,0.008438116,0.01031985,0.0007990028,0.0001109609,0.004080467,0.8514713],"genre_scores_gemma":[0.9921117,0.003126785,0.0008120289,0.000782045,0.001397937,0.00005412279,0.00004561069,0.0001126515,0.001557164],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9011829,"threshold_uncertainty_score":0.999595,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01336018377594647,"score_gpt":0.2487507868395274,"score_spread":0.2353906030635809,"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."}}