{"id":"W2759614181","doi":"10.1344/ara.v6i2.19076","title":"De smart city a smart destination. El caso de tres ciudades canadienses","year":2017,"lang":"es","type":"article","venue":"Ara","topic":"Smart Cities and Technologies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Humanities; Art; Political science; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001891561,0.0002442904,0.0002429972,0.0001177367,0.0006376012,0.0004826895,0.0005235631,0.000225246,0.00009440325],"category_scores_gemma":[0.0009023394,0.0002599523,0.00009309944,0.00006657175,0.0002543016,0.0002173612,0.0001397796,0.0002681774,0.0000387601],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000284792,"about_ca_system_score_gemma":0.0001314574,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03866053,"about_ca_topic_score_gemma":0.0111286,"domain_scores_codex":[0.9987602,0.00002132551,0.0001928615,0.0002347787,0.0001225791,0.0006682328],"domain_scores_gemma":[0.998852,0.0001585699,0.00009227409,0.0007102729,0.000056143,0.0001307372],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001027999,0.00003045997,0.9517778,0.0001533993,0.000139632,0.0002092057,0.0007393539,0.000395952,0.0006341177,0.01561472,0.006485562,0.02380951],"study_design_scores_gemma":[0.0002689786,0.00005950347,0.95324,0.0001693857,0.00006568203,0.0000840555,0.000357823,0.004751633,0.006183486,0.003488065,0.03097066,0.0003606913],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9825734,0.000957654,0.0005024469,0.001019885,0.0004242654,0.0001228358,0.00005668543,0.0004476574,0.01389513],"genre_scores_gemma":[0.9967411,0.0003931296,0.001795129,0.00009190802,0.0001769149,0.00003457503,0.000004763091,0.00004038025,0.0007221657],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02753193,"threshold_uncertainty_score":0.9999853,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02221905077637864,"score_gpt":0.2535357183396439,"score_spread":0.2313166675632652,"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."}}