{"id":"W4224325754","doi":"10.1111/itor.13145","title":"Collaboration and optimization in farmland exchanges","year":2022,"lang":"en","type":"article","venue":"International Transactions in Operational Research","topic":"Agricultural Innovations and Practices","field":"Agricultural and Biological Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Arable land; Profitability index; Business; Cost reduction; Agricultural science; Environmental economics; Agricultural economics; Agriculture; Agricultural engineering; Computer science; Environmental science; Economics; Marketing; Geography; Engineering","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":[0.003289247,0.001103078,0.001750069,0.001050161,0.0008710963,0.002217915,0.001376715,0.001650654,0.008361553],"category_scores_gemma":[0.007679461,0.0005547365,0.001356615,0.001789801,0.001299515,0.00296951,0.001787897,0.00124008,0.0003360111],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001791816,"about_ca_system_score_gemma":0.0012701,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005136974,"about_ca_topic_score_gemma":0.002982466,"domain_scores_codex":[0.9974374,0.001567314,0.00008432394,0.0003486179,0.00015407,0.0004082867],"domain_scores_gemma":[0.99266,0.005856065,0.0006749796,0.0002079166,0.0002260321,0.0003750257],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000720597,0.00006580053,0.0008684106,0.00005998993,0.00004906973,0.0001136129,0.00004942946,0.9721742,0.0001376167,0.02076747,0.0006711981,0.004971102],"study_design_scores_gemma":[0.00003651843,0.00005994224,0.0006003152,0.00001992677,0.00001509221,0.00002887597,0.0001215949,0.9596556,0.0001517397,0.03794683,0.001352403,0.00001112705],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3879481,0.001416249,0.5735259,0.001737689,0.0001198685,0.0003717172,0.001088467,0.0002902589,0.03350178],"genre_scores_gemma":[0.9525797,0.0003692573,0.04215939,0.0000835565,0.00003225915,0.0002196402,0.0002951586,0.00005920061,0.004201872],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008361553,"threshold_uncertainty_score":0.02797216,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09672003605152384,"score_gpt":0.37840394728163,"score_spread":0.2816839112301061,"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."}}