{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003840461,0.0002825008,0.0003687791,0.00002711847,0.0003292166,0.00006777505,0.000357409,0.0001230142,0.001744456],"category_scores_gemma":[0.0004159917,0.0002817948,0.000145814,0.0003193203,0.0004086045,0.0003178529,0.0008828693,0.0001866494,0.0001372635],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003246349,"about_ca_system_score_gemma":0.0001696929,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001721335,"about_ca_topic_score_gemma":0.0007138945,"domain_scores_codex":[0.9973772,0.0002232181,0.0003560777,0.0009729338,0.0002516972,0.0008188579],"domain_scores_gemma":[0.9984587,0.0001456046,0.00008853903,0.0009670259,0.0001125411,0.0002275173],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0007437308,0.007346165,0.4432116,0.0017091,0.002241994,0.0019065,0.08855011,0.02404206,0.01387239,0.3381696,0.0165,0.06170673],"study_design_scores_gemma":[0.0003417614,0.0001398222,0.03556994,0.000005113865,0.00002306468,0.000003417799,0.007600472,0.0002517132,0.005002808,0.892273,0.05842561,0.0003632466],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9409984,0.0003871819,0.0008755684,0.007328683,0.0001871189,0.0002750391,0.00007539122,0.0001485705,0.04972402],"genre_scores_gemma":[0.9980699,0.000006572814,0.0002117958,0.0004494064,0.00008693636,0.0001316213,0.00002665633,0.000027924,0.0009892259],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5541034,"threshold_uncertainty_score":0.9999634,"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."}}