{"id":"W6998605449","doi":"","title":"Alternative vs. conventional food networks: A geospatial analysis in relation to neighborhood sociodemographic characteristics in Montreal","year":2021,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Organic Food and Agriculture","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Relation (database); Geospatial analysis; Population; Field (mathematics)","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":[0.0006244206,0.0003116163,0.0003068413,0.002515558,0.002323333,0.002374695,0.001357381,0.0003094861,0.007428579],"category_scores_gemma":[0.003560648,0.0002843805,0.0006827416,0.006005246,0.0009980652,0.0008190192,0.00173877,0.0004355637,0.0003193485],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02730731,"about_ca_system_score_gemma":0.01426008,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9937937,"about_ca_topic_score_gemma":0.9970647,"domain_scores_codex":[0.9993778,0.0001102927,0.0000272974,0.0001514926,0.0001322587,0.0002008576],"domain_scores_gemma":[0.9984378,0.0001776112,0.0003252521,0.00007300213,0.0006032296,0.0003830656],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000166992,0.00005566588,0.9775662,0.00005990376,0.0001901822,0.0001585021,0.003353577,0.001112871,0.0004700109,0.002694706,0.003100783,0.01107068],"study_design_scores_gemma":[0.000006245741,0.00001570575,0.9938729,0.00001944264,0.00003297057,0.00002505036,0.00289949,0.001081686,0.00005841495,0.00009552266,0.001878167,0.00001445324],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9884543,0.0005203581,0.0002936487,0.0003788669,0.000009667345,0.00006367166,0.004483574,0.00002586028,0.005770159],"genre_scores_gemma":[0.995943,0.000207342,0.0002762227,0.00002761364,0.000004110797,0.0000262528,0.000936606,0.00001022722,0.002568666],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02730731,"threshold_uncertainty_score":0.1981293,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008767645551723097,"score_gpt":0.2032389848123063,"score_spread":0.1944713392605832,"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."}}