{"id":"W4405546772","doi":"10.1007/978-981-97-8309-0_2","title":"National Geodatabase to Map Consumptions for Energy Transition","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in civil engineering","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University; Ontario Medical Association","funders":"","keywords":"Spatial database; Geography; Database; Cartography; Environmental science; Computer science; Spatial analysis; Remote sensing","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":[],"consensus_categories":[],"category_scores_codex":[0.0003798024,0.000195002,0.0002143449,0.0004756375,0.0001430585,0.00006702646,0.0001370158,0.0002704383,0.0007702821],"category_scores_gemma":[0.000262131,0.0002274747,0.0001702625,0.0001300767,0.00004841898,0.00005720025,0.0000140352,0.000256466,0.00005011261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003989149,"about_ca_system_score_gemma":0.0002202553,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001102152,"about_ca_topic_score_gemma":0.1310668,"domain_scores_codex":[0.9988454,0.00001089131,0.0002439153,0.0003494806,0.0003274917,0.00022284],"domain_scores_gemma":[0.9990075,0.0006002044,0.00002968397,0.0001375968,0.0001344642,0.00009051865],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000007244435,0.00001486559,7.463595e-7,0.0002296539,0.00008762115,0.000004599168,0.002650854,0.5425411,0.00006034437,0.4494416,0.0005217295,0.004439543],"study_design_scores_gemma":[0.0001496581,0.00002281968,0.000003623266,0.0006465372,0.0001347894,7.121951e-7,0.00001852121,0.06034784,0.00006003108,0.1187426,0.8193244,0.000548411],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00001142015,0.001009726,0.9763445,0.004452381,0.0004544892,0.0003422814,0.0004450186,0.0001715011,0.01676871],"genre_scores_gemma":[0.9400782,0.0002659009,0.004494901,0.002039673,0.00378725,0.0005727457,0.002040387,0.0001868274,0.0465341],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9718496,"threshold_uncertainty_score":0.9276149,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01895218429076523,"score_gpt":0.2732094094428261,"score_spread":0.2542572251520609,"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."}}