{"id":"W2481612658","doi":"10.1109/igarss.1997.615954","title":"Spectral identification of coral biological vigour","year":2002,"lang":"en","type":"article","venue":"","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Coral; Coral reef; Coral bleaching; Identification (biology); Environmental science; Remote sensing; Ecosystem; Reef; Computer science; Environmental resource management; Oceanography; Ecology; Geology; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005859703,0.00006026995,0.00007998813,0.00004475215,0.00001306824,0.00001425089,0.00006655787,0.00005011613,0.0002197024],"category_scores_gemma":[0.00003375476,0.00005349585,0.0000321479,0.0001139832,0.00003748354,0.00006711039,0.000005320765,0.00005497591,0.0002840763],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002794025,"about_ca_system_score_gemma":0.000001016917,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001611896,"about_ca_topic_score_gemma":9.308861e-7,"domain_scores_codex":[0.9995236,0.00001153113,0.0002066054,0.00009046548,0.00006945489,0.00009833532],"domain_scores_gemma":[0.9997317,0.00001632114,0.00002842318,0.0001703344,0.0000286858,0.00002450381],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001361709,0.00002611554,0.0007323076,0.00001163808,0.000009123244,0.000001371371,0.00006974878,0.001235924,0.9851412,0.0006628684,0.004334012,0.007774304],"study_design_scores_gemma":[0.0001294694,0.00002209654,0.06474284,0.000005550346,0.000005844156,0.00001049342,0.0000256121,0.6430943,0.2903739,0.0002033082,0.001259612,0.0001269603],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.931422,0.00006212074,0.04807868,0.000215176,0.0002515797,0.00009259071,0.000002606526,0.0003696409,0.01950558],"genre_scores_gemma":[0.9965153,0.00003706985,0.002732309,0.00001251548,0.0000417166,7.018201e-7,0.000005384295,0.000009240229,0.0006457518],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6947673,"threshold_uncertainty_score":0.3651321,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04366589940987069,"score_gpt":0.2266855366894947,"score_spread":0.183019637279624,"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."}}