{"id":"W4200147751","doi":"10.3390/su132413920","title":"Exploring Social Media Data to Understand How Stakeholders Value Local Food: A Canadian Study Using Twitter","year":2021,"lang":"en","type":"article","venue":"Sustainability","topic":"Organic Food and Agriculture","field":"Agricultural and Biological Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; University of Ottawa; Université du Québec à Montréal","funders":"Mitacs","keywords":"Social media; Locality; Context (archaeology); Local language; Valuation (finance); Value (mathematics); Sample (material); Data science; Advertising; Marketing; Business; Geography; Computer science; World Wide Web; Accounting","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001774753,0.0003665331,0.0003843535,0.003560634,0.008210683,0.003134004,0.0009052339,0.0007999548,0.002355145],"category_scores_gemma":[0.00682389,0.0003679552,0.0004538718,0.008666382,0.001740859,0.002339605,0.001827615,0.001103799,0.0004350716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02664476,"about_ca_system_score_gemma":0.02726714,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9869011,"about_ca_topic_score_gemma":0.9932856,"domain_scores_codex":[0.9987424,0.0002150435,0.00005521083,0.000183836,0.0004013547,0.0004021708],"domain_scores_gemma":[0.9956526,0.001194789,0.0004822576,0.0001710969,0.001983706,0.00051559],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003487996,0.0003897828,0.4861977,0.0004317791,0.000096948,0.001425703,0.4419341,0.000350742,0.00397016,0.003772229,0.01046111,0.05062075],"study_design_scores_gemma":[0.00002280178,0.00009165809,0.3677606,0.0001912358,0.0000663165,0.000184315,0.5917673,0.001701345,0.0007009718,0.0003738741,0.03701799,0.0001216381],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9893013,0.00019297,0.0002815119,0.001385043,0.00001392697,0.0001260174,0.002847497,0.0000145149,0.0058373],"genre_scores_gemma":[0.991729,0.0006858864,0.0009501412,0.0005488158,0.00001149958,0.0001216018,0.001881198,0.00002679546,0.004045119],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02664476,"threshold_uncertainty_score":0.1933222,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3848612924930976,"score_gpt":0.2860288901277093,"score_spread":0.09883240236538837,"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."}}