{"id":"W4311152974","doi":"10.5194/isprs-archives-xlviii-4-w3-2022-111-2022","title":"<i>k</i>CV-B: BOOTSTRAP WITH CROSS-VALIDATION FOR DEEP LEARNING MODEL DEVELOPMENT, ASSESSMENT AND SELECTION","year":2022,"lang":"en","type":"article","venue":"˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"National Science Foundation","keywords":"Computer science; Resampling; Estimator; Artificial intelligence; Generalization; Cross-validation; Machine learning; Model selection; Test data; Inference; Data mining; Point cloud; Statistics; Mathematics","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":[0.01690666,0.001743923,0.00154326,0.002860886,0.0009121334,0.0017623,0.003180559,0.002747114,0.002881345],"category_scores_gemma":[0.05349208,0.0008809306,0.00118974,0.002329095,0.001431996,0.001982415,0.002752601,0.00473705,0.001818671],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001203916,"about_ca_system_score_gemma":0.002343992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004457768,"about_ca_topic_score_gemma":0.005298114,"domain_scores_codex":[0.990661,0.005868134,0.0006832659,0.001012334,0.001481275,0.0002939811],"domain_scores_gemma":[0.9768438,0.01398703,0.001122246,0.003804798,0.003785953,0.0004561779],"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":[0.0008661003,0.0006567723,0.01009687,0.0005804215,0.001002549,0.0003033618,0.0002444529,0.3410566,0.007466016,0.02983925,0.03168204,0.5762055],"study_design_scores_gemma":[0.00002323908,0.00007573103,0.0007140827,0.00005192969,0.00002162451,0.00006353118,0.0000155646,0.9893557,0.002844958,0.0052106,0.001603571,0.00001942954],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005323682,0.0003429456,0.9901639,0.0001851218,0.00008214352,0.0001218673,0.000152874,0.002919707,0.0007077238],"genre_scores_gemma":[0.1647836,0.0002695613,0.8290648,0.0004123099,0.00009548465,0.0009388501,0.001659605,0.001286179,0.001489655],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01690666,"threshold_uncertainty_score":0.08941203,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01966725645165505,"score_gpt":0.2804338496737686,"score_spread":0.2607665932221135,"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."}}