{"id":"W2129314265","doi":"10.5267/j.msl.2014.8.012","title":"An optimization technique for cropping patterns and land consolidation: A case study for irrigation network","year":2014,"lang":"en","type":"article","venue":"Management Science Letters","topic":"Rice Cultivation and Yield Improvement","field":"Agricultural and Biological Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Consolidation (business); Cropping; Irrigation; Agricultural engineering; Computer science; Water resource management; Land consolidation; Environmental science; Business; Geography; Agriculture; Agronomy; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008666744,0.0004242811,0.0003613394,0.0006353111,0.0006088666,0.0008339889,0.00070518,0.001196395,0.001732992],"category_scores_gemma":[0.001554934,0.000281595,0.0007599736,0.001364975,0.0004454487,0.0008734858,0.0004753753,0.0005596592,0.0001012295],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001234347,"about_ca_system_score_gemma":0.0008645118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0125156,"about_ca_topic_score_gemma":0.01862855,"domain_scores_codex":[0.9995571,0.0002317714,0.00001600876,0.00005818443,0.00005891753,0.00007808513],"domain_scores_gemma":[0.9992749,0.0004821587,0.00007381757,0.00004205822,0.00007473052,0.00005230771],"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":[0.00007860341,0.0002887851,0.009754377,0.0001082219,0.00003953928,0.001476519,0.0001777312,0.9515297,0.00201719,0.007574024,0.0008612343,0.02609399],"study_design_scores_gemma":[0.00001498782,0.0001076692,0.00169156,0.000006418813,0.00001612805,0.0001607264,0.0002679079,0.9942238,0.0008277461,0.001307867,0.001364971,0.00001023754],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8621849,0.0005241225,0.1225593,0.0006839609,0.00002530642,0.0002280736,0.0002509178,0.0001163589,0.0134271],"genre_scores_gemma":[0.9569054,0.0002743775,0.03941344,0.00001997189,0.00000852847,0.00006529461,0.00008251658,0.00002027095,0.003210167],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0125156,"threshold_uncertainty_score":0.02488554,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02241893084068286,"score_gpt":0.2581378223931071,"score_spread":0.2357188915524243,"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."}}