{"id":"W7077065499","doi":"10.18280/isi.300601","title":"Evaluation of Some Supervised Machine Learning Techniques for the Prediction of Soil Macro-Nutrients for Cash Crop Production","year":2025,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Covenant University Centre for Research, Innovation and Discovery; Covenant University","keywords":"Cash crop; Production (economics); Crop production; Crop yield; Crop","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":[0.003713671,0.001245021,0.0007498672,0.001142032,0.0003618253,0.0006060004,0.0008089707,0.0009561113,0.0005453276],"category_scores_gemma":[0.005651872,0.0002186695,0.00108457,0.0008183573,0.0002149771,0.0006889169,0.0003651364,0.000882062,0.0002474602],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005658306,"about_ca_system_score_gemma":0.001029148,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008357955,"about_ca_topic_score_gemma":0.007094074,"domain_scores_codex":[0.9989246,0.0004355631,0.0001389541,0.0002078679,0.0002155499,0.00007753543],"domain_scores_gemma":[0.9956895,0.002796157,0.0003328616,0.0002090312,0.0009044476,0.00006808803],"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":[0.0006167725,0.0005996018,0.02186668,0.000466762,0.0005009196,0.0002251501,0.0001507638,0.6652479,0.006550309,0.000570689,0.001765487,0.301439],"study_design_scores_gemma":[0.00001595173,0.0002974014,0.005309989,0.00003061047,0.00005477767,0.00004283362,0.00006272964,0.9897857,0.003727977,0.000302788,0.0003560398,0.0000131594],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8002874,0.005068918,0.1855308,0.0007996097,0.0002511116,0.0002835916,0.001217733,0.0020679,0.004493068],"genre_scores_gemma":[0.9203069,0.0008511092,0.07610161,0.00009011268,0.00004525864,0.0001136926,0.001310987,0.00003427443,0.001145979],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008357955,"threshold_uncertainty_score":0.01963997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02401694057809154,"score_gpt":0.2553751046024739,"score_spread":0.2313581640243823,"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."}}