{"id":"W4206703138","doi":"10.3386/w29061","title":"Mechanizing Agriculture","year":2021,"lang":"en","type":"report","venue":"National Bureau of Economic Research","topic":"Agricultural Economics and Policy","field":"Agricultural and Biological Sciences","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Sloan School of Management, Massachusetts Institute of Technology; Agricultural Technology Adoption Initiative","keywords":"Agriculture; Computer science; Geography; Archaeology","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":[0.002047383,0.0003948802,0.0008244704,0.0002085458,0.0002996438,0.0005316343,0.0005002424,0.001219911,0.007891604],"category_scores_gemma":[0.003523614,0.0002010498,0.0007168371,0.0002326939,0.0007576058,0.0003920018,0.0003439714,0.00104351,0.0003471248],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004464464,"about_ca_system_score_gemma":0.0007927041,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009110686,"about_ca_topic_score_gemma":0.001384636,"domain_scores_codex":[0.9984689,0.0009419677,0.00005770037,0.0002209908,0.000125707,0.0001846398],"domain_scores_gemma":[0.9987576,0.0007095423,0.0002650951,0.000110845,0.0000547992,0.0001020439],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"randomized_trial","study_design_gemma":"observational","study_design_scores_codex":[0.4333522,0.09972411,0.01018691,0.00526187,0.002484676,0.0001886056,0.0003160845,0.01247024,0.01814471,0.01037596,0.005495815,0.4019989],"study_design_scores_gemma":[0.36994,0.4872339,0.05961729,0.001622723,0.003347535,0.0002318478,0.0005065707,0.01430076,0.01744973,0.01735805,0.02829662,0.00009498768],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9806163,0.002889116,0.00245472,0.00177296,0.0007415833,0.002602724,0.0003812821,0.00009792171,0.008443405],"genre_scores_gemma":[0.9920197,0.0008905467,0.002778967,0.0007585219,0.0001105049,0.001463314,0.0001091069,0.000006309122,0.001863025],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007891604,"threshold_uncertainty_score":0.02640003,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4388127525690164,"score_gpt":0.4856423744895364,"score_spread":0.04682962192051998,"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."}}