{"id":"W2988412519","doi":"","title":"Editorial: Celebrating Innovation in Florence (October 2019)","year":2019,"lang":"en","type":"editorial","venue":"Technology Innovation Management Review","topic":"International Science and Diplomacy","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Political science; Library science; Regional science; Geography; 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"],"consensus_categories":[],"category_scores_codex":[0.005322356,0.0003204195,0.0005625077,0.002796003,0.0002573826,0.0001293634,0.001400867,0.001039688,0.00039215],"category_scores_gemma":[0.005055898,0.0003276191,0.00005419677,0.01518268,0.0002686107,0.0006335416,0.0003210103,0.00107865,0.0007601271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006517729,"about_ca_system_score_gemma":0.0005646027,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000322914,"about_ca_topic_score_gemma":0.0001666244,"domain_scores_codex":[0.9951019,0.0001330438,0.001524663,0.0007276085,0.001968551,0.0005442743],"domain_scores_gemma":[0.9959486,0.0001991877,0.001229914,0.0005515539,0.002052035,0.00001866907],"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":[0.000001798503,0.00002309752,0.00006239069,0.0004379541,0.0000131154,0.000002258226,0.00003028445,8.305161e-7,0.00000635582,0.3383467,0.6476954,0.01337982],"study_design_scores_gemma":[0.0002321203,0.00002398901,0.00001164851,0.003399549,0.00002818103,1.008446e-7,0.00011264,0.000002392864,0.000006003143,0.01413869,0.9817188,0.0003258742],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.00003665905,0.002502157,0.0001754523,0.005873723,0.9036885,0.001656703,0.00001468156,0.0002943386,0.08575781],"genre_scores_gemma":[0.0001309071,0.03796074,0.0008359082,0.001286069,0.9456744,0.0004011507,0.0008262993,0.00003640841,0.01284814],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.3340235,"threshold_uncertainty_score":0.9999176,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01672429156773119,"score_gpt":0.3680375498558535,"score_spread":0.3513132582881223,"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."}}