{"id":"W4214564532","doi":"10.1111/soru.12369","title":"Disciplining land through data: The role of agricultural technologies in farmland assetisation","year":2022,"lang":"en","type":"article","venue":"Sociologia Ruralis","topic":"Agriculture, Land Use, Rural Development","field":"Agricultural and Biological Sciences","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; University of Regina; York University; University of Guelph","funders":"","keywords":"Agriculture; Business; Sustainability; Agricultural land; Land tenure; Natural resource economics; Scholarship; Agricultural economics; Economics; Economic growth; Geography; Ecology","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.01769759,0.0001756377,0.000230828,0.002618929,0.002955226,0.008700319,0.001063655,0.001175311,0.003925739],"category_scores_gemma":[0.04422214,0.0002082066,0.000227162,0.003087855,0.0222885,0.01250638,0.007075487,0.00201906,0.0002120679],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004796253,"about_ca_system_score_gemma":0.002813175,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002708431,"about_ca_topic_score_gemma":0.003498209,"domain_scores_codex":[0.9903643,0.006534779,0.0003819414,0.000730304,0.001404166,0.0005845029],"domain_scores_gemma":[0.9098209,0.07461672,0.00603549,0.004767527,0.003735868,0.001023474],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001084077,0.0001017864,0.06403829,0.0004649317,0.00003175572,0.001640158,0.4164045,0.0009118275,0.002707357,0.3941485,0.002268579,0.1171741],"study_design_scores_gemma":[0.00001736283,0.0001208686,0.03931261,0.001389974,0.00003259488,0.001202548,0.5675554,0.003332194,0.004749157,0.2043023,0.1779205,0.00006459383],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8116996,0.001952085,0.03872466,0.02686313,0.0001462365,0.000203631,0.0002293031,0.00005222958,0.1201291],"genre_scores_gemma":[0.9960927,0.000287629,0.002178437,0.000262123,0.00001695454,0.00002446017,0.00002053743,0.00001176616,0.00110528],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9970448,"threshold_uncertainty_score":0.09359491,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02919886897386668,"score_gpt":0.2453897827503264,"score_spread":0.2161909137764597,"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."}}