{"id":"W2991378322","doi":"","title":"Medical Scope：新たなサーベイランスによる百日咳対策の変化","year":2019,"lang":"ja","type":"article","venue":"Pharma Medica","topic":"Military Technology and Strategies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Scope (computer science); Business; 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":[0.0008122269,0.0004276419,0.0005833561,0.0002033284,0.00009632651,0.0000260073,0.001007088,0.0007944916,0.07523375],"category_scores_gemma":[0.000240402,0.0004119082,0.0001605356,0.0003778955,0.0003635711,0.0002545056,0.0001987494,0.00172097,0.01185364],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007116144,"about_ca_system_score_gemma":0.0002592588,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004930102,"about_ca_topic_score_gemma":0.00001735701,"domain_scores_codex":[0.9969099,0.00009825012,0.0006051764,0.0005211053,0.001009061,0.0008564772],"domain_scores_gemma":[0.9984409,0.000231316,0.00005686788,0.0006716449,0.00004383907,0.0005554284],"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":[0.0003890528,0.001054344,0.009976993,0.006108163,0.003162985,0.003594368,0.005943038,0.0009184289,0.01082965,0.1142858,0.6110847,0.2326524],"study_design_scores_gemma":[0.009154079,0.0006620197,0.002486526,0.002350893,0.0004196428,0.0006549673,0.002331337,0.1006754,0.008120209,0.006946919,0.8636063,0.00259171],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2808769,0.05700126,0.0003590948,0.007391428,0.009555045,0.0007113001,0.00005203512,0.001620166,0.6424327],"genre_scores_gemma":[0.9852631,0.01084152,0.0002087431,0.0007898566,0.0006462347,0.00002709484,0.00003004298,0.00006748492,0.002125906],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7043862,"threshold_uncertainty_score":0.9998333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0123130734711566,"score_gpt":0.2623126927252281,"score_spread":0.2499996192540715,"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."}}