{"id":"W7037759129","doi":"","title":"Estado e impacto de la R+D y la innovación en Barcelona y su área metropolitana","year":2016,"lang":"ca","type":"report","venue":"Repositori Obert de Coneixement de lAjuntament de Barcelona","topic":"Sesquiterpenes and Asteraceae Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Università degli Studi di Salerno; European University Institute; London School of Economics and Political Science; University of Essex; Queen Mary University of London; Università di Bologna; University of Leicester; Centre National de la Recherche Scientifique; University of Ottawa","keywords":"Metropolitan area; Population; State (computer science); Context (archaeology); Product (mathematics)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.004425942,0.002079598,0.00196311,0.0005144651,0.0007411924,0.0008810807,0.001444304,0.002341845,0.0003020386],"category_scores_gemma":[0.0008029112,0.001911635,0.001211513,0.0004875356,0.0007079691,0.00005179251,0.001624688,0.00130671,0.00005031135],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006289705,"about_ca_system_score_gemma":0.004970045,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00325025,"about_ca_topic_score_gemma":0.0001020628,"domain_scores_codex":[0.9882663,0.002346514,0.002125962,0.002310215,0.001576465,0.003374577],"domain_scores_gemma":[0.9937263,0.0008446823,0.001266363,0.002114931,0.000775669,0.001272087],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001085388,0.001276315,0.2703529,0.001656129,0.00731298,0.003280713,0.00187667,0.00003031862,0.6392544,0.001398891,0.05235593,0.02011933],"study_design_scores_gemma":[0.002665069,0.001192935,0.02498969,0.001478813,0.00150303,0.003777592,0.001133297,0.00004995709,0.1286503,0.0003927844,0.8316619,0.002504623],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8237486,0.03503101,0.007486287,0.002481979,0.004079251,0.00270598,0.0008964829,0.0002562222,0.1233142],"genre_scores_gemma":[0.941446,0.02665532,0.002413856,0.001077072,0.006253947,0.0005085145,0.0006444383,0.0004376106,0.02056322],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7793059,"threshold_uncertainty_score":0.9991946,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006941167515129917,"score_gpt":0.3048917036681557,"score_spread":0.2979505361530258,"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."}}