{"id":"W2561620318","doi":"10.1002/rob.21698","title":"Robotic Coral Reef Health Assessment Using Automated Image Analysis","year":2016,"lang":"en","type":"article","venue":"Journal of Field Robotics","topic":"Coral and Marine Ecosystems Studies","field":"Environmental Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Australian Centre for Field Robotics","keywords":"Coral reef; Computer science; Artificial intelligence; Support vector machine; Set (abstract data type); Data set; Data mining; Computer vision; Ecology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003640626,0.000509508,0.0005213619,0.002036043,0.0002751453,0.0006609163,0.0006882006,0.0004624215,0.001251402],"category_scores_gemma":[0.0008938024,0.0002862932,0.0003902254,0.0005336173,0.0003009295,0.000471448,0.000747167,0.0003119358,0.0006251595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003871383,"about_ca_system_score_gemma":0.0005870837,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004507372,"about_ca_topic_score_gemma":0.005431153,"domain_scores_codex":[0.9995402,0.0000619506,0.00001939536,0.0001216003,0.0002118892,0.00004494542],"domain_scores_gemma":[0.9995178,0.00009862067,0.0001199689,0.00007320211,0.0001616774,0.00002869262],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002344676,0.0001967219,0.01572383,0.00015025,0.00008931756,0.0001655555,0.0001466403,0.04315645,0.1377767,0.0006081941,0.003637747,0.7981143],"study_design_scores_gemma":[0.00004083948,0.0002086644,0.03647942,0.00003706203,0.0000469547,0.0003817234,0.0001620174,0.9069429,0.0506798,0.001209491,0.00374131,0.00006975064],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2652367,0.0005250965,0.7133791,0.0002844628,0.0000768239,0.000285378,0.0006460063,0.01099346,0.008572984],"genre_scores_gemma":[0.7411125,0.0001842479,0.2558505,0.00009998868,0.00003141145,0.0001286464,0.0004896363,0.0001329672,0.001970116],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004507372,"threshold_uncertainty_score":0.008962274,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02105942305630593,"score_gpt":0.3127273378393416,"score_spread":0.2916679147830357,"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."}}