{"id":"W4387332271","doi":"10.3390/su151914479","title":"Recalibrating Data on Farm Productivity: Why We Need Small Farms for Food Security","year":2023,"lang":"en","type":"article","venue":"Sustainability","topic":"Agriculture, Land Use, Rural Development","field":"Agricultural and Biological Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University; Carleton University","funders":"","keywords":"Food security; Productivity; Agriculture; Agricultural productivity; Production (economics); Food systems; Food processing; Peasant; Agricultural economics; Argument (complex analysis); Scale (ratio); Economics; Business; Natural resource economics; Economic growth; Geography; Ecology; Political science; Microeconomics; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.02017811,0.000552673,0.0007480187,0.00354724,0.0009340046,0.003395612,0.001862648,0.001103168,0.003488957],"category_scores_gemma":[0.1100824,0.0003517465,0.0005255147,0.007462597,0.002865334,0.007953729,0.002315561,0.003380575,0.001262996],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001732335,"about_ca_system_score_gemma":0.00158599,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02959956,"about_ca_topic_score_gemma":0.03065225,"domain_scores_codex":[0.990969,0.004310572,0.0008295049,0.001174291,0.002205016,0.0005115573],"domain_scores_gemma":[0.899076,0.05467867,0.01366417,0.01160342,0.01885835,0.002119357],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006069593,0.00008216267,0.4223585,0.002005807,0.0005065481,0.0004314881,0.008682988,0.003253434,0.001871728,0.06063014,0.1554496,0.3441206],"study_design_scores_gemma":[0.0001127353,0.0003085771,0.5370993,0.00601594,0.0002266309,0.0005793534,0.01883105,0.007404409,0.002205906,0.104009,0.3229718,0.0002352663],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4759865,0.03524157,0.0643433,0.3394655,0.006778147,0.0001854566,0.02434315,0.0005087349,0.05314768],"genre_scores_gemma":[0.9391671,0.009569094,0.01705371,0.02161955,0.002008962,0.0001658914,0.006227818,0.0002258714,0.003961994],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02959956,"threshold_uncertainty_score":0.1067133,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05265342307594782,"score_gpt":0.2607656803623814,"score_spread":0.2081122572864336,"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."}}