{"id":"W2143380823","doi":"10.2112/si_62_9","title":"Benthic Classifications Using Bathymetric LIDAR Waveforms and Integration of Local Spatial Statistics and Textural Features","year":2011,"lang":"en","type":"article","venue":"Journal of Coastal Research","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Rimouski; Institut National de la Recherche Scientifique","funders":"","keywords":"Benthic habitat; Cluster analysis; Bathymetry; Pattern recognition (psychology); Lidar; Statistics; Principal component analysis; Support vector machine; Geostatistics; Benthic zone; Spatial analysis; Computer science; Artificial intelligence; Remote sensing; Mathematics; Geography; Cartography; Spatial variability; Geology; Oceanography","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":[0.0007858277,0.0005288258,0.0003795144,0.003216588,0.0001585373,0.0007699747,0.0002150612,0.0002371292,0.0008869117],"category_scores_gemma":[0.002043978,0.0001245899,0.0003453166,0.002407015,0.000189604,0.0006871589,0.0004885449,0.0001706439,0.000505572],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001566898,"about_ca_system_score_gemma":0.0002743874,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00226985,"about_ca_topic_score_gemma":0.004825534,"domain_scores_codex":[0.9995454,0.00009661849,0.00005781036,0.00009298137,0.0001671009,0.00004013096],"domain_scores_gemma":[0.9991001,0.0002055192,0.0002486066,0.00008047938,0.0003070057,0.00005833375],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005476942,0.0001779741,0.3788892,0.0004157084,0.0001503669,0.0002205086,0.0003763235,0.01820714,0.09620762,0.0005698739,0.0007236075,0.5035139],"study_design_scores_gemma":[0.0000212139,0.0004485087,0.822977,0.00006250407,0.0001111133,0.0003842036,0.0008955925,0.1515906,0.02165256,0.0005546045,0.001233159,0.00006896791],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9442261,0.000209613,0.05269304,0.00002813466,0.0000144656,0.00007118465,0.0006413059,0.0002957291,0.001820311],"genre_scores_gemma":[0.959154,0.0001780982,0.03872688,0.0000120019,0.0000172868,0.00004537826,0.0009962067,0.00002630521,0.0008438625],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003216588,"threshold_uncertainty_score":0.004513323,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09511683994219643,"score_gpt":0.3428706667248489,"score_spread":0.2477538267826525,"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."}}