{"id":"W4307849690","doi":"10.36227/techrxiv.21430644","title":"Image Prediction Using Coordinated Hyperspectral and RGB Video of Dynamic Natural Water Scenes","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Hyperspectral imaging; RGB color model; Remote sensing; Artificial intelligence; Computer science; Computer vision; Chemical imaging; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0001559308,0.0003815497,0.0001594869,0.0003425454,0.0001676077,0.0003302809,0.0003107035,0.000217259,0.0008798988],"category_scores_gemma":[0.0004497206,0.0001299057,0.000216147,0.0003501639,0.0001956835,0.0003455296,0.0001436979,0.0002352096,0.000305621],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005904214,"about_ca_system_score_gemma":0.0004531959,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02828423,"about_ca_topic_score_gemma":0.03717965,"domain_scores_codex":[0.9998997,0.000006555985,0.000002468536,0.000048125,0.00002722371,0.0000158378],"domain_scores_gemma":[0.9998703,0.00002536946,0.00001822925,0.00001651929,0.00005727721,0.00001218627],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0004401022,0.0003549229,0.03668863,0.00005561777,0.00004999686,0.0001701889,0.0001143785,0.7072185,0.1059071,0.0007071226,0.003299129,0.1449944],"study_design_scores_gemma":[0.000004306785,0.00001921249,0.010988,0.000001268479,0.000003281514,0.000009133241,0.00002224885,0.979763,0.008869037,0.0001105321,0.0002042414,0.000005773694],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8716429,0.00004664393,0.123161,0.00009311458,0.0000279351,0.00005242548,0.001028826,0.001483148,0.002463978],"genre_scores_gemma":[0.9661188,0.00003026108,0.03167983,0.00001770785,0.000006601957,0.00002206272,0.000911104,0.00005676583,0.001157037],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02828423,"threshold_uncertainty_score":0.05623919,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01137528221848148,"score_gpt":0.2362595119016589,"score_spread":0.2248842296831775,"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."}}