{"id":"W3205085355","doi":"10.1016/j.marpolbul.2021.113036","title":"Nation-wide hierarchical and spatially-explicit framework to characterize seagrass meadows in New-Caledonia, and its potential application to the Indo-Pacific","year":2021,"lang":"en","type":"article","venue":"Marine Pollution Bulletin","topic":"Marine and coastal plant biology","field":"Earth and Planetary Sciences","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Seagrass; Coral reef; Reef; Marine habitats; Geography; Habitat; Oceanography; Environmental resource management; Distribution (mathematics); Spatial distribution; Field (mathematics); Remote sensing; Ecology; Environmental science; Physical geography; Geology; Biology","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":[0.0005422604,0.0002490059,0.0002699973,0.0009607601,0.0004602282,0.001149368,0.0008464972,0.0003741247,0.000999543],"category_scores_gemma":[0.001476615,0.0002018995,0.0005647482,0.001948465,0.0003259202,0.0006199857,0.0009690906,0.0004248073,0.00008738942],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00168835,"about_ca_system_score_gemma":0.002051341,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.337004,"about_ca_topic_score_gemma":0.5446883,"domain_scores_codex":[0.9998277,0.00006369792,0.00001491365,0.00004969313,0.00001446972,0.00002945973],"domain_scores_gemma":[0.9995245,0.0001902503,0.00007502958,0.00006548841,0.00008509591,0.0000596961],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00008137058,0.0001765157,0.4458756,0.00009197845,0.0005067975,0.0003816359,0.0005702372,0.5124433,0.0009378777,0.0104798,0.002791242,0.02566363],"study_design_scores_gemma":[0.00000842318,0.00001349242,0.1767328,0.00003059051,0.00006782478,0.00003172006,0.0009247856,0.8173076,0.00008343268,0.002816463,0.001964899,0.00001806874],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.969663,0.0003662228,0.02240347,0.0004094001,0.00002148778,0.00003505648,0.004654909,0.00008672998,0.002359546],"genre_scores_gemma":[0.9847682,0.0001259943,0.01215447,0.00003029487,0.000006403252,0.00003220735,0.00230145,0.000008720779,0.0005721535],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.337004,"threshold_uncertainty_score":0.6700848,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008675617514099157,"score_gpt":0.193236082431171,"score_spread":0.1845604649170719,"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."}}