{"id":"W3195308826","doi":"","title":"発達障害~適切な支援のための医療とは~多職種連携支援 3)地域での早期発見・早期支援","year":2019,"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":"Political 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":[0.00050609,0.0005032436,0.0006105323,0.000242589,0.0001233197,0.00003557366,0.00082568,0.0005714458,0.01931828],"category_scores_gemma":[0.00008915449,0.0005088947,0.0001992109,0.0004034643,0.0002869494,0.000335601,0.0001627881,0.001358816,0.009308141],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009545896,"about_ca_system_score_gemma":0.0001143988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007277318,"about_ca_topic_score_gemma":0.00001570966,"domain_scores_codex":[0.99729,0.00008651274,0.0005918372,0.0005805733,0.0005090416,0.0009419988],"domain_scores_gemma":[0.9985635,0.0001878312,0.00007714569,0.0008268455,0.00005525329,0.0002893939],"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":[0.0006427446,0.001115043,0.01085422,0.006593611,0.004323728,0.001904556,0.01377147,0.003280613,0.06331699,0.1458746,0.5211229,0.2271995],"study_design_scores_gemma":[0.005997525,0.0005024456,0.002015574,0.0006487776,0.0004464175,0.0001859205,0.002916083,0.05928984,0.01354956,0.009857111,0.9024764,0.002114336],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3439508,0.02395255,0.0002252675,0.003036805,0.007490174,0.0007074619,0.00007763541,0.001539424,0.6190199],"genre_scores_gemma":[0.9874876,0.004073351,0.0003464383,0.0004239083,0.0006080671,0.0000367975,0.0000382356,0.00008163075,0.006904018],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6435367,"threshold_uncertainty_score":0.9997362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01260705033648585,"score_gpt":0.2483419365207126,"score_spread":0.2357348861842267,"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."}}