{"id":"W6888978192","doi":"10.25384/sage.12902168","title":"online_supp_Connell – Supplemental material for Evaluating the Strength of Local Legislative Frameworks to Protect Farmland: City of Richmond and Metro Vancouver, British Columbia","year":2020,"lang":"en","type":"article","venue":"Sage Journals Data","topic":"Agricultural Economics and Policy","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Legislature; Local government; Legislative history; Metropolitan area; Urban planning","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002308157,0.0009507595,0.001094413,0.005095932,0.003191266,0.00465439,0.002557538,0.001588683,0.6618201],"category_scores_gemma":[0.024546,0.001105088,0.0006311267,0.009258863,0.0006212874,0.001574879,0.002167992,0.001626306,0.2129136],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009557233,"about_ca_system_score_gemma":0.0248938,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8077544,"about_ca_topic_score_gemma":0.9177687,"domain_scores_codex":[0.9967706,0.0002148553,0.0002358396,0.0001860492,0.002134674,0.0004579554],"domain_scores_gemma":[0.9483948,0.007486308,0.001113568,0.002009135,0.03749984,0.00349633],"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":[0.0000253782,0.00005250448,0.001154932,0.00007419218,0.00000469159,0.00001255255,0.00002937019,0.00008243186,0.00001926045,0.0001335151,0.9935638,0.0048475],"study_design_scores_gemma":[0.000499566,0.0000781451,0.0810222,0.0006039577,0.00004734355,0.00003984728,0.002058741,0.0007230261,0.0006144122,0.0009933226,0.9131866,0.0001327381],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.001425492,0.00005360521,0.0002739972,0.0009726331,0.0003555892,0.0004061336,0.9071855,0.0006450893,0.08868196],"genre_scores_gemma":[0.01913781,0.0003429859,0.003085926,0.001295497,0.0002351875,0.001705656,0.6566342,0.001362413,0.3162003],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.6618201,"threshold_uncertainty_score":0.4823725,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06307736747760316,"score_gpt":0.3101410177867898,"score_spread":0.2470636503091866,"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."}}