{"id":"W6986650989","doi":"","title":"Profile of census tracts in Montréal, 2006 Census : map volume","year":2009,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Census; Volume (thermodynamics); Field (mathematics); Population; Data collection","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":[0.0003134063,0.001133102,0.0005312944,0.006127585,0.00127944,0.001503088,0.001536118,0.0003990557,0.1306332],"category_scores_gemma":[0.002436525,0.0006911397,0.0004823327,0.01566484,0.0002495702,0.0008423392,0.0006835783,0.0006886277,0.04068993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008508857,"about_ca_system_score_gemma":0.02536596,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9640433,"about_ca_topic_score_gemma":0.982885,"domain_scores_codex":[0.9995757,0.0000233421,0.00002827515,0.00007924059,0.0001859764,0.0001074967],"domain_scores_gemma":[0.9985884,0.00004007763,0.0001407495,0.00005019991,0.0009914547,0.0001891005],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002533596,0.00001539787,0.008205464,0.0002564742,0.00001137933,0.00003028774,0.0001332458,0.000286089,0.0001171438,0.000549994,0.9725969,0.01777233],"study_design_scores_gemma":[0.00003053286,0.00001707334,0.271326,0.0001850892,0.00002160133,0.00007734776,0.0003011135,0.0005156929,0.0001949608,0.0001436374,0.7271517,0.00003525156],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.004137455,0.001014943,0.0004861359,0.0003811989,0.00009899913,0.0002856007,0.9379221,0.0009733749,0.05470022],"genre_scores_gemma":[0.03076573,0.003388682,0.004178454,0.000272767,0.00007657844,0.0005999792,0.6580576,0.0005869124,0.3020733],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1306332,"threshold_uncertainty_score":0.4370118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005992010863277777,"score_gpt":0.1866118588390389,"score_spread":0.1806198479757612,"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."}}