{"id":"W4302557274","doi":"","title":"Enablers for smart cities","year":2016,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Smart Cities and Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Architectural engineering; Geography; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002274329,0.0006669079,0.0005143459,0.001133936,0.001627936,0.007045014,0.0009055004,0.002956018,0.05415402],"category_scores_gemma":[0.004413906,0.0002305151,0.0005649641,0.001843822,0.002356007,0.01179122,0.007790073,0.00270054,0.008540764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001916492,"about_ca_system_score_gemma":0.001581756,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001863776,"about_ca_topic_score_gemma":0.001878379,"domain_scores_codex":[0.9986029,0.0003794849,0.00004731374,0.0001914623,0.0004251898,0.0003537047],"domain_scores_gemma":[0.9980302,0.0006276637,0.0001480178,0.0003188367,0.0004688922,0.0004063422],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001911939,0.00001954884,0.0002286059,0.0001883772,0.00001024066,0.0001144257,0.0005475556,0.0008876752,0.0004694769,0.9090419,0.06022538,0.02824774],"study_design_scores_gemma":[0.000007871236,0.00002157541,0.0003112095,0.0002005976,0.000009246684,0.00007382678,0.001026385,0.001209891,0.0004634504,0.2681485,0.7285119,0.00001548696],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"review","genre_scores_codex":[0.02328284,0.01441473,0.03864283,0.1204322,0.005320834,0.0001363376,0.001016329,0.001359643,0.7953943],"genre_scores_gemma":[0.644497,0.03109384,0.01261315,0.01246419,0.004734322,0.0003989314,0.001252897,0.0005265287,0.292419],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.05415402,"threshold_uncertainty_score":0.1811632,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01533563027045638,"score_gpt":0.2050000666132543,"score_spread":0.1896644363427979,"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."}}