{"id":"W2475266777","doi":"10.1177/2053951716648174","title":"Big Data in food and agriculture","year":2016,"lang":"en","type":"article","venue":"Big Data & Society","topic":"Agriculture, Land Use, Rural Development","field":"Agricultural and Biological Sciences","cited_by":418,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; St. Thomas University","funders":"","keywords":"Big data; Scholarship; Agriculture; Data science; Affordance; Computer science; Economics; Economic growth; Data mining","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":[0.01063897,0.0005828175,0.0009650872,0.005743846,0.002876698,0.009661448,0.00154663,0.004238881,0.006959909],"category_scores_gemma":[0.0274258,0.0004335706,0.0006398445,0.01427181,0.008925979,0.01702745,0.005218999,0.005784772,0.001107394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003729025,"about_ca_system_score_gemma":0.003497198,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004166545,"about_ca_topic_score_gemma":0.00361647,"domain_scores_codex":[0.9923255,0.004201814,0.0003908613,0.0008478306,0.00196163,0.0002722608],"domain_scores_gemma":[0.96515,0.02554414,0.002110405,0.00322985,0.002583137,0.001382419],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008228627,0.00004472697,0.008741904,0.002044542,0.0001386618,0.0003746615,0.003712026,0.001509775,0.0003022709,0.6647023,0.1275302,0.1908168],"study_design_scores_gemma":[0.0000113024,0.00002330433,0.00510446,0.00171192,0.00002000863,0.0002022971,0.003917491,0.00105988,0.0001821057,0.5640814,0.4236396,0.00004634204],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.01583079,0.3216169,0.03955976,0.4802744,0.01250061,0.0002096699,0.00618852,0.0005007359,0.1233185],"genre_scores_gemma":[0.4299515,0.3666719,0.0651126,0.08693279,0.02751768,0.0007539836,0.005398964,0.0003938799,0.01726672],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01063897,"threshold_uncertainty_score":0.05626494,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1138633693590624,"score_gpt":0.2399007308208972,"score_spread":0.1260373614618348,"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."}}