{"id":"W7126343209","doi":"","title":"La georeferenziazione dei numeri civici ai tempi della Misura 1.3.1. del PNRR","year":2025,"lang":"it","type":"article","venue":"DOAJ (DOAJ: Directory of Open Access Journals)","topic":"Urban Planning and Valuation","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"SAIT Polytechnic","funders":"","keywords":"Context (archaeology); Geospatial analysis; Modernization theory; Field (mathematics); Measure (data warehouse); Corporate governance","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003701467,0.0007466369,0.001222287,0.0008864317,0.0007986156,0.002379988,0.004165502,0.0004628141,0.04180325],"category_scores_gemma":[0.0005237074,0.0007201346,0.0003740648,0.002216311,0.0005069839,0.00261459,0.001918773,0.001214508,0.0006027943],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005404912,"about_ca_system_score_gemma":0.0003461631,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004847998,"about_ca_topic_score_gemma":0.0001826114,"domain_scores_codex":[0.9935619,0.00126844,0.001660302,0.001098658,0.001511618,0.0008991091],"domain_scores_gemma":[0.9961774,0.000893271,0.001229562,0.0009939751,0.0002055441,0.0005002729],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002531818,0.00057426,0.6482697,0.0001367059,0.0003656363,0.00005134658,0.0003814855,0.002296633,0.03742953,0.0001293656,0.2685485,0.04156373],"study_design_scores_gemma":[0.001099411,0.00002585935,0.8875129,0.001588187,0.0004476709,0.0000276388,0.0001855201,0.002384803,0.01183248,0.0043361,0.08970173,0.0008576601],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8966022,0.02979262,0.002581809,0.001146653,0.00153304,0.001037911,0.0001750348,0.00009168486,0.0670391],"genre_scores_gemma":[0.9793518,0.008917159,0.0003097214,0.001183528,0.0001697864,0.00004836969,0.00005707085,0.00008040536,0.009882221],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2392433,"threshold_uncertainty_score":0.999525,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2183899001162096,"score_gpt":0.5357690688303065,"score_spread":0.3173791687140969,"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."}}