{"id":"W1981460220","doi":"10.5539/jas.v2n1p59","title":"Analysis of Profitability and Risk in New Agriculture Using Dynamic Non-Linear Programming Model","year":2010,"lang":"en","type":"article","venue":"Journal of Agricultural Science","topic":"Agricultural risk and resilience","field":"Agricultural and Biological Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Norges Miljø- og Biovitenskapelige Universitet; International Association for Applied Econometrics","keywords":"Cropping; Carnation; Gross margin; Agricultural economics; Agriculture; Agricultural science; Profit (economics); Profitability index; Mathematics; Irrigation; Economics; Agronomy; Geography; Environmental science; Horticulture; Biology","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":[0.001126054,0.0009219694,0.0011368,0.000782259,0.0005383642,0.002141138,0.001292862,0.001669553,0.004028848],"category_scores_gemma":[0.001898645,0.0006684838,0.001150949,0.0009105136,0.0006242106,0.001037892,0.0008174338,0.001593704,0.0002330512],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002158878,"about_ca_system_score_gemma":0.001916715,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03015107,"about_ca_topic_score_gemma":0.01893241,"domain_scores_codex":[0.9995134,0.000167427,0.00001748334,0.00008769609,0.00007034923,0.0001436248],"domain_scores_gemma":[0.9985487,0.001001548,0.0001853145,0.00002209173,0.0001639656,0.00007835724],"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":[0.00001168364,0.00001424937,0.000461014,0.00001250955,0.00000838198,0.00004756384,0.000008467346,0.9973392,0.00007102154,0.001187734,0.00009802113,0.0007402503],"study_design_scores_gemma":[0.000002003293,0.000008296857,0.0001414274,0.00000216596,0.000003142966,0.000003694737,0.00000993809,0.9992658,0.00001808631,0.0004736265,0.0000690922,0.000002587985],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5763278,0.001470935,0.3908325,0.001701047,0.0001247961,0.0002131802,0.001186765,0.0002818461,0.02786122],"genre_scores_gemma":[0.9762294,0.0005191711,0.01258247,0.0000646557,0.0000288793,0.0001482675,0.000325759,0.00003287493,0.01006857],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03015107,"threshold_uncertainty_score":0.05995113,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01086485256951928,"score_gpt":0.2563939951415712,"score_spread":0.245529142572052,"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."}}