{"id":"W2318044484","doi":"10.1142/9789814277426_0386","title":"RELATING SPATIAL SCALE TO BENTHOSCAPE PATTERNS WITH A HIGH-RESOLUTION BATHYMETRIC LIDAR","year":2009,"lang":"en","type":"article","venue":"","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Rimouski; Institut National de la Recherche Scientifique","funders":"","keywords":"Bathymetry; Lidar; Scale (ratio); Image resolution; Remote sensing; Spatial ecology; Geology; Computer science; Geography; Cartography; Artificial intelligence; 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":[0.00026379,0.0001601245,0.0001883339,0.0007666284,0.0002771092,0.000407223,0.0002682121,0.0002600657,0.0008032431],"category_scores_gemma":[0.001607542,0.0002472416,0.0001712664,0.0009535576,0.0002069629,0.0005342567,0.0004624525,0.0001903656,0.0002173427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002045917,"about_ca_system_score_gemma":0.0001791156,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009425118,"about_ca_topic_score_gemma":0.02372938,"domain_scores_codex":[0.9998853,0.00002332356,0.000004429174,0.00003530207,0.00003767129,0.00001393408],"domain_scores_gemma":[0.9993794,0.0002834961,0.00007859027,0.00007528595,0.0001421776,0.00004104516],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002911295,0.0001198603,0.7619145,0.0001141737,0.0001692008,0.0002376508,0.0006115414,0.02732181,0.1220034,0.000573546,0.0005875656,0.08605552],"study_design_scores_gemma":[0.00003366354,0.00007000371,0.9055001,0.000008119421,0.0000536003,0.0002013343,0.0001910291,0.08718459,0.005926239,0.000438295,0.0003684726,0.00002449283],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.984365,0.00007079323,0.01340848,0.00003302055,0.000005569955,0.00001616177,0.000274502,0.00008095341,0.001745576],"genre_scores_gemma":[0.9923029,0.00003166283,0.007305277,0.00001187098,0.000003667686,0.00000970892,0.0001401051,0.00001220527,0.0001826405],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009425118,"threshold_uncertainty_score":0.01874048,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006307805922575453,"score_gpt":0.2092139047884188,"score_spread":0.2029060988658434,"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."}}