{"id":"W7145012606","doi":"","title":"日本の産業におけるイノベーションの専有可能性と技術機会の変容 ; 1994-2020","year":2022,"lang":"ja","type":"report","venue":"Institutional Repositories DataBase (IRDB)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Competitor analysis; Competition (biology); Quarter (Canadian coin); Technological change; Innovation management; Manufacturing","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.00390142,0.0005075272,0.0003336454,0.01399838,0.001619887,0.003515702,0.001054289,0.0008917761,0.02188073],"category_scores_gemma":[0.009312863,0.0004125361,0.0002292399,0.01995103,0.0006006655,0.002085355,0.001201357,0.0009347987,0.01481928],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007381049,"about_ca_system_score_gemma":0.009809641,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2490968,"about_ca_topic_score_gemma":0.1877914,"domain_scores_codex":[0.9969372,0.0003153308,0.0003816744,0.0002492874,0.001615875,0.0005006266],"domain_scores_gemma":[0.9827384,0.002367137,0.00296303,0.0005544188,0.00925329,0.002123746],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0005488362,0.0006017858,0.2803121,0.0005442803,0.00003864542,0.0002418358,0.0009888733,0.0007013232,0.0004617198,0.004951761,0.6162185,0.09439027],"study_design_scores_gemma":[0.00005638611,0.0001466717,0.6655654,0.0001558601,0.00004982411,0.0002011745,0.001592652,0.0009193937,0.002332689,0.0003412073,0.3286069,0.00003186262],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.1241283,0.005020779,0.0009624421,0.007518534,0.0003442952,0.0007020979,0.7430815,0.0007486212,0.1174935],"genre_scores_gemma":[0.1669851,0.009447978,0.00359255,0.000941205,0.0003590241,0.001393206,0.6626785,0.000171665,0.1544307],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2490968,"threshold_uncertainty_score":0.4952937,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03466851448037749,"score_gpt":0.2978586196068691,"score_spread":0.2631901051264916,"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."}}