{"id":"W6986686547","doi":"","title":"Profile of census divisions and subdivisions in Ontario","year":2004,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"Child Development and Digital Technology","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Census; Subdivision; Population; Work (physics); Demographic analysis","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002723859,0.0002695205,0.0002600795,0.005034967,0.001867914,0.00107903,0.000636938,0.0002393596,0.01849602],"category_scores_gemma":[0.002244731,0.0004583538,0.0003074126,0.01377563,0.0004414311,0.0004155833,0.0007531544,0.0002884133,0.002558537],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01282556,"about_ca_system_score_gemma":0.03455037,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9858711,"about_ca_topic_score_gemma":0.9953879,"domain_scores_codex":[0.9993238,0.00003076266,0.00005763291,0.00004993176,0.0003270961,0.0002106999],"domain_scores_gemma":[0.9975204,0.000156241,0.0004471048,0.00006765058,0.001302918,0.0005055915],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003669587,0.0000663201,0.6277021,0.001264507,0.0001045759,0.0006930573,0.01887899,0.001090272,0.002502151,0.007172072,0.2572938,0.08286528],"study_design_scores_gemma":[0.0000107862,0.00001669832,0.8856483,0.00009708535,0.00001557286,0.000103668,0.006204859,0.0002995177,0.0001529921,0.0001350523,0.1072968,0.00001861032],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.532578,0.002170325,0.0007442101,0.001810996,0.00008129227,0.000562883,0.3195423,0.0003044487,0.1422056],"genre_scores_gemma":[0.6252558,0.005376646,0.002658448,0.0003083451,0.00003221701,0.0005135577,0.09985719,0.0001152344,0.2658826],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01849602,"threshold_uncertainty_score":0.09305644,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00904216581200653,"score_gpt":0.2078779071898302,"score_spread":0.1988357413778236,"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."}}