{"id":"W1967320999","doi":"10.1016/s0308-521x(02)00051-3","title":"Application of decision tree technology for image classification using remote sensing data","year":2003,"lang":"en","type":"article","venue":"Agricultural Systems","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":140,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Tillage; Cropping; Hyperspectral imaging; Decision tree; Residue (chemistry); Remote sensing; Conventional tillage; Mathematics; Environmental science; Computer science; Agronomy; Artificial intelligence; Geography; Agriculture","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":[0.001606208,0.000645953,0.0007208504,0.001914244,0.0005089549,0.0009228513,0.0005692345,0.0006251911,0.001618464],"category_scores_gemma":[0.004532274,0.0003042081,0.0006434813,0.001921855,0.0002668132,0.0009610211,0.000527591,0.0007392742,0.000594129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003412547,"about_ca_system_score_gemma":0.0005129644,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002813247,"about_ca_topic_score_gemma":0.002153988,"domain_scores_codex":[0.9991346,0.0003076544,0.0001025737,0.0001009967,0.0003017024,0.00005253051],"domain_scores_gemma":[0.9971981,0.001880388,0.0001439846,0.0001549616,0.0005626858,0.00005992481],"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":[0.0003421006,0.0002748386,0.005586994,0.0003463977,0.0001998723,0.0002191211,0.0002231179,0.08774394,0.02539572,0.006817379,0.003090207,0.8697603],"study_design_scores_gemma":[0.00003938832,0.0001592199,0.003239457,0.00005208121,0.0001060931,0.0001763426,0.00007084267,0.9636341,0.0155187,0.01255142,0.004418103,0.00003435346],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03987025,0.0005717858,0.9557097,0.000198814,0.00009638631,0.0001020905,0.0002717492,0.001288177,0.001891037],"genre_scores_gemma":[0.3890963,0.0005892973,0.6079707,0.00008219105,0.00007272569,0.0001391039,0.0006438984,0.0001040129,0.001301908],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002813247,"threshold_uncertainty_score":0.008494556,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02986565230212062,"score_gpt":0.267543422615159,"score_spread":0.2376777703130384,"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."}}