{"id":"W4289767955","doi":"10.55227/ijhet.v1i2.10","title":"Decision Support System In Land Selection For Rubber Tree Planting Using The Moora Method","year":2022,"lang":"en","type":"article","venue":"International Journal of Health Engineering and Technology","topic":"Decision Support System Applications","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Flexibility (engineering); Natural rubber; Agricultural engineering; Productivity; Decision tree; Process (computing); Quality (philosophy); Decision support system; Selection (genetic algorithm); Tree planting; Computer science; Engineering; Environmental science; Mathematics; Agroforestry; Statistics; Data mining; Artificial intelligence; Economics; Materials science","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":[0.001674738,0.0006819651,0.0008415622,0.001750207,0.0008201551,0.002058515,0.000866539,0.000753941,0.01171879],"category_scores_gemma":[0.003309004,0.0003220252,0.0009179928,0.001122848,0.0002336902,0.001229668,0.0008441539,0.000676271,0.002704109],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005174485,"about_ca_system_score_gemma":0.001166588,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003813468,"about_ca_topic_score_gemma":0.003260605,"domain_scores_codex":[0.9987842,0.0004290323,0.0001618366,0.0002342298,0.0002945758,0.00009612415],"domain_scores_gemma":[0.9986896,0.0006807629,0.0001040853,0.00006766176,0.0003760582,0.00008188572],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001535331,0.0004808158,0.005657684,0.001383701,0.0002743679,0.0008989505,0.0008640836,0.06847619,0.02129683,0.01540558,0.02712826,0.8565982],"study_design_scores_gemma":[0.0004357403,0.0003875784,0.005743954,0.0003532514,0.0002220462,0.0006320865,0.0005850794,0.8636729,0.02375524,0.009363936,0.09468205,0.000166173],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02927729,0.0004210989,0.9374882,0.0004023641,0.0001262339,0.0009405987,0.001557862,0.01637124,0.01341505],"genre_scores_gemma":[0.213021,0.0003863207,0.7748434,0.0001820115,0.00005914461,0.001083758,0.001503818,0.0002259836,0.008694575],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01171879,"threshold_uncertainty_score":0.03920323,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02187355860819583,"score_gpt":0.3137615509903303,"score_spread":0.2918879923821344,"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."}}