{"id":"W2603867707","doi":"","title":"就労支援：チーム医療・支援が患者の人生を変える","year":2016,"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":[0.001379919,0.0002417225,0.000183217,0.0007490342,0.001875809,0.003286625,0.0003868387,0.001051473,0.01303911],"category_scores_gemma":[0.00229962,0.0001892172,0.0002330578,0.0004227837,0.003584769,0.001659789,0.0007238818,0.001295821,0.003975877],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001958973,"about_ca_system_score_gemma":0.003027302,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005313753,"about_ca_topic_score_gemma":0.005040787,"domain_scores_codex":[0.9992328,0.0001199948,0.00004545127,0.0001290522,0.0003902678,0.000082435],"domain_scores_gemma":[0.9987178,0.0003236302,0.0001283086,0.0001213426,0.0005669474,0.0001420136],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.00009711853,0.0001529484,0.004604599,0.0002443395,0.00003802288,0.0004908079,0.003111328,0.0009697975,0.01176431,0.7815701,0.01469907,0.1822575],"study_design_scores_gemma":[0.00003321269,0.0003429334,0.0141355,0.0002470253,0.00008738004,0.001213439,0.00544656,0.00188467,0.03333765,0.291061,0.6521132,0.00009740811],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.08032744,0.006371073,0.03451928,0.01232329,0.001429035,0.0002119862,0.0001979181,0.0001769628,0.8644431],"genre_scores_gemma":[0.7063838,0.005179483,0.02272941,0.003334802,0.0007316302,0.0001098057,0.000108905,0.00005293748,0.2613693],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01303911,"threshold_uncertainty_score":0.04362017,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01582649590257975,"score_gpt":0.253217112530854,"score_spread":0.2373906166282743,"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."}}