{"id":"W4200249114","doi":"10.3390/su14010192","title":"A Food-Circular Economy-Women Nexus: Lessons from Guelph-Wellington","year":2021,"lang":"en","type":"article","venue":"Sustainability","topic":"Water-Energy-Food Nexus Studies","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Nexus (standard); Food security; Context (archaeology); Resource (disambiguation); Sustainable development; Agriculture; Sustainable agriculture; Circular economy; Economic growth; Geography; Business; Environmental resource management; Political science; Economics; Engineering; Ecology; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.003598077,0.0004153002,0.000428999,0.0008913288,0.01788106,0.004255112,0.001173404,0.001597207,0.004803519],"category_scores_gemma":[0.004723303,0.0003727921,0.0001914333,0.002354465,0.008732621,0.005209477,0.005903976,0.002268722,0.0003060242],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04412174,"about_ca_system_score_gemma":0.05060869,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.857694,"about_ca_topic_score_gemma":0.9665155,"domain_scores_codex":[0.9965342,0.001520601,0.00007158174,0.0004658625,0.0003094838,0.00109823],"domain_scores_gemma":[0.9944708,0.002297496,0.0003556144,0.0002471566,0.0008578111,0.001771017],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001234422,0.00009425651,0.02239074,0.0004755296,0.00001622065,0.004400919,0.862821,0.0001813999,0.001417699,0.04744549,0.02112814,0.03950514],"study_design_scores_gemma":[0.00001047826,0.00003981456,0.02228152,0.0006880413,0.000009882919,0.0002328612,0.8295704,0.0001123692,0.0005518242,0.004379534,0.142092,0.00003130119],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7558087,0.007009255,0.002504797,0.1170494,0.0002030271,0.0002354744,0.0002884238,0.00004201359,0.1168589],"genre_scores_gemma":[0.9628166,0.00299311,0.001956058,0.00763172,0.0000147634,0.00011924,0.000085239,0.00004754274,0.02433565],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.142306,"threshold_uncertainty_score":0.3201271,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01240412066745145,"score_gpt":0.232404654181735,"score_spread":0.2200005335142836,"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."}}