{"id":"W434030437","doi":"","title":"地域情報化最新事例 小さくても世界の中でキラッと光る『ユビキタウンふくみつ』をめざして--富山県西砺波郡福光町","year":2002,"lang":"ja","type":"article","venue":"Theory and applications of categories","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":[0.001557648,0.0002624186,0.0003143585,0.001297487,0.002207748,0.005351981,0.0006403691,0.001101621,0.008549802],"category_scores_gemma":[0.003561287,0.0002469551,0.0004127816,0.001034804,0.01151659,0.006237093,0.001283289,0.001716141,0.002107608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002286697,"about_ca_system_score_gemma":0.001521718,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004491611,"about_ca_topic_score_gemma":0.003430329,"domain_scores_codex":[0.9990696,0.0002925053,0.00005199536,0.0002157659,0.000270726,0.00009939187],"domain_scores_gemma":[0.9983808,0.0005896889,0.0001148607,0.0002110293,0.0005889067,0.0001147898],"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":[0.000005618003,0.000002838948,0.0002344317,0.00002135432,0.000003173212,0.00001524984,0.0008345016,0.00007305513,0.0002139094,0.9924779,0.001011698,0.005106251],"study_design_scores_gemma":[0.000003681765,0.00000826207,0.0004588361,0.00002176408,0.000006187096,0.00007417265,0.001004999,0.0002686462,0.0004030711,0.9518265,0.04591424,0.000009544691],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.06238806,0.008372528,0.262026,0.01410801,0.001495235,0.0001279599,0.000521732,0.0002286137,0.6507319],"genre_scores_gemma":[0.8362741,0.003989553,0.0744797,0.001437428,0.000642546,0.0001770873,0.0004146493,0.000149913,0.08243498],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008549802,"threshold_uncertainty_score":0.02860194,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007933391280043722,"score_gpt":0.2091435530025807,"score_spread":0.201210161722537,"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."}}