{"id":"W4391294110","doi":"10.1007/s00146-023-01859-y","title":"The changing face of Agrarian labor in the age of artificial intelligence and machine learning: balancing benefits and risks","year":2024,"lang":"en","type":"article","venue":"AI & Society","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Simon Fraser University; Social Science Research Council; Andrew W. Mellon Foundation","keywords":"Agrarian society; Face (sociological concept); Artificial intelligence; Performing arts; Computer science; Machine learning; Sociology; Agriculture; History; Social science; Visual arts; Art","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003467548,0.00006300626,0.00007214591,0.00001828278,0.00005420133,0.00007224065,0.00007239348,0.0000488214,0.000002110831],"category_scores_gemma":[0.00001808692,0.00004256149,0.00003075095,0.0002588768,0.00006486067,0.0001218557,0.0000182384,0.000266669,7.164814e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009744259,"about_ca_system_score_gemma":0.000006106291,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002132093,"about_ca_topic_score_gemma":0.00002178856,"domain_scores_codex":[0.999558,0.00001299139,0.0001648981,0.00006053627,0.00009046413,0.0001130904],"domain_scores_gemma":[0.9997221,0.0001807683,0.00001390325,0.00006101482,0.00001079976,0.00001146583],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00000733099,0.0000260545,0.007072876,0.001018149,0.0001624766,0.000004946523,0.2358979,0.09313288,0.002279242,0.03645644,0.0003760878,0.6235656],"study_design_scores_gemma":[0.0001806228,0.0001012578,0.01347387,0.0008608038,0.00006149411,0.00002078827,0.0965177,0.8557105,0.01686794,0.003422565,0.01234745,0.0004350011],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9831936,0.00681931,0.007853924,0.0007421455,0.000151263,0.0001652356,0.00005322346,0.00007349693,0.0009477809],"genre_scores_gemma":[0.9989967,0.000872681,0.00005650438,0.0000293413,0.00001828967,0.000004724384,0.000005075767,0.000006823289,0.000009885393],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7625776,"threshold_uncertainty_score":0.1735607,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03615493562367435,"score_gpt":0.2585840611745867,"score_spread":0.2224291255509123,"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."}}