{"id":"W4250504782","doi":"10.5670/oceanog.2021.305","title":"An Optical Imaging System for Capturing Images in Low-Light Aquatic Habitats Using Only Ambient Light","year":2021,"lang":"en","type":"article","venue":"Oceanography","topic":"Coral and Marine Ecosystems Studies","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"California Sea Grant, University of California, San Diego; Natural Sciences and Engineering Research Council of Canada","keywords":"Visibility; Underwater; Remote sensing; Environmental science; Kelp forest; Computer science; Software deployment; Image quality; Sampling (signal processing); Real-time computing; Habitat; Computer vision; Ecology; Geology; Image (mathematics); Optics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0008399076,0.0006236837,0.000321363,0.001390385,0.0005755717,0.0008407107,0.00103914,0.0008178365,0.01290391],"category_scores_gemma":[0.001018722,0.0005960109,0.000485296,0.0007379298,0.0004318982,0.0009909336,0.0008162833,0.0008502051,0.002973922],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000672298,"about_ca_system_score_gemma":0.0009340352,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001815293,"about_ca_topic_score_gemma":0.005529897,"domain_scores_codex":[0.9993683,0.00008546711,0.00003903353,0.0001864802,0.0002825526,0.00003815558],"domain_scores_gemma":[0.999154,0.0002118338,0.0001447637,0.0001413755,0.0002705169,0.0000776382],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00009228854,0.0001543462,0.002531742,0.0005533581,0.00004520425,0.0001176203,0.0001390424,0.0004178848,0.8562821,0.002362805,0.01059447,0.126709],"study_design_scores_gemma":[0.0002481673,0.001543267,0.04764205,0.000351701,0.0003254863,0.005472373,0.0002515177,0.03199175,0.6216496,0.00181421,0.2883851,0.0003248605],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06448311,0.001264952,0.8961295,0.0006858133,0.0004737006,0.00184298,0.001381248,0.004872294,0.02886636],"genre_scores_gemma":[0.06982679,0.0008447801,0.9117303,0.0005811567,0.0001106959,0.001283677,0.0006404911,0.0002424422,0.01473974],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01290391,"threshold_uncertainty_score":0.04316783,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008383717014529014,"score_gpt":0.2254310029004297,"score_spread":0.2170472858859007,"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."}}