{"id":"W3092700726","doi":"","title":"Datafication on the Farm: An Exploration of the Social Impacts of Agricultural Big Data on Canadian Crop Farms","year":2020,"lang":"en","type":"dissertation","venue":"The Atrium (University of Guelph)","topic":"Smart Agriculture and AI","field":"Agricultural and Biological Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Agriculture; Crop; Big data; Agricultural economics; Agricultural science; Business; Geography; Economics; Environmental science; Forestry; Computer science; Archaeology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002202351,0.0001714317,0.0002282624,0.00001904003,0.0006391907,0.0000255303,0.001894567,0.0001728486,0.00005831322],"category_scores_gemma":[0.00005536556,0.00004969455,0.0001457906,0.0006022825,0.0001099284,0.0002489805,0.0001091702,0.0002570954,0.00001212185],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004012283,"about_ca_system_score_gemma":0.00006661654,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.05254445,"about_ca_topic_score_gemma":0.4165711,"domain_scores_codex":[0.9988202,0.00019766,0.0001681239,0.0002750795,0.0003758743,0.0001630408],"domain_scores_gemma":[0.9988521,0.0001097007,0.0005097551,0.0002740333,0.0001851584,0.00006926939],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0003379086,0.0001807511,0.0002768681,0.00005680358,0.0001586904,0.000001366386,0.0126141,0.00002051634,0.9393497,0.003940466,0.02218729,0.02087557],"study_design_scores_gemma":[0.0001189529,0.000250414,0.9301192,0.00005872104,0.0001643412,4.66876e-7,0.05642058,0.0000115492,0.003812705,0.0001039053,0.008772814,0.0001663279],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.981939,0.00003137846,4.442247e-7,0.01494877,0.0002547476,0.0003952399,0.0009115362,0.00001192381,0.001507007],"genre_scores_gemma":[0.9928726,0.00006003508,0.000002519007,0.0001319209,0.0003719483,4.494626e-7,0.006158451,0.000001409402,0.0004006906],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.935537,"threshold_uncertainty_score":0.9537647,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0820764232589149,"score_gpt":0.242046268382421,"score_spread":0.1599698451235061,"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."}}