{"id":"W4307849810","doi":"10.36227/techrxiv.21430644.v1","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":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Hyperspectral imaging; RGB color model; Remote sensing; Artificial intelligence; Computer science; Computer vision; 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":[0.0001571053,0.0004026449,0.0001703114,0.0003443781,0.0001525704,0.0003082111,0.000307002,0.0002058024,0.0007076902],"category_scores_gemma":[0.0004458532,0.0001250751,0.0002171115,0.000363591,0.0001808944,0.0003492592,0.0001576872,0.0002359823,0.0002292163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005338969,"about_ca_system_score_gemma":0.0004396053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02123526,"about_ca_topic_score_gemma":0.02752672,"domain_scores_codex":[0.9999045,0.000006636814,0.000002488582,0.00004592851,0.0000251464,0.00001525118],"domain_scores_gemma":[0.9998789,0.00002442185,0.00001732456,0.00001497179,0.00005353731,0.0000109401],"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":[0.0004390994,0.0003281533,0.03962374,0.00005998346,0.00005198175,0.000156536,0.0001100643,0.729441,0.1061426,0.0006533645,0.002138702,0.1208547],"study_design_scores_gemma":[0.000004320536,0.00002498421,0.01159374,0.000001327126,0.000003799546,0.000009974125,0.00002378953,0.9783976,0.009624749,0.0001226465,0.0001870456,0.000006012514],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8726067,0.00004603583,0.1236157,0.00006454238,0.00002036298,0.00004901288,0.0008188609,0.001082415,0.001696453],"genre_scores_gemma":[0.9675261,0.00003064648,0.03077167,0.00001470645,0.000005298154,0.00002400909,0.0007368812,0.00004460934,0.000846064],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02123526,"threshold_uncertainty_score":0.04222333,"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."}}