{"id":"W4404689549","doi":"10.1109/oceans55160.2024.10753841","title":"Evaluating an Autonomous eDNA Sampler for Marine Environmental Monitoring: Short- and Long-Term Applications","year":2024,"lang":"en","type":"article","venue":"","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Tula Foundation; Bedford Institute of Oceanography; Fisheries and Oceans Canada","funders":"Tula Foundation","keywords":"Term (time); Environmental DNA; Environmental science; Computer science; Marine engineering; Oceanography; Remote sensing; Engineering; Geology; Ecology; Biology; Biodiversity","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":[0.001895785,0.00050702,0.0004582813,0.0004988786,0.0003832368,0.0007457344,0.000752731,0.0008845706,0.0008691052],"category_scores_gemma":[0.002354927,0.0002626787,0.0003069379,0.000416877,0.0004734789,0.0008682671,0.0008533261,0.0003492667,0.0003540315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004439931,"about_ca_system_score_gemma":0.0006481206,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002330861,"about_ca_topic_score_gemma":0.006403411,"domain_scores_codex":[0.998813,0.0002099497,0.00006131738,0.0002922478,0.0005497019,0.00007378865],"domain_scores_gemma":[0.9986159,0.0004225408,0.0002355073,0.0001197271,0.0005005833,0.0001057833],"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":[0.0005849427,0.0002571961,0.05215403,0.0004810851,0.0001065065,0.0001261707,0.0003527375,0.003774847,0.8623366,0.0002836034,0.000426519,0.07911576],"study_design_scores_gemma":[0.00008153027,0.006666687,0.1456612,0.0001417887,0.0004146182,0.0009298126,0.001236414,0.06160142,0.7623369,0.001017024,0.01972884,0.00018384],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8619783,0.001615128,0.1317261,0.000303287,0.0001698462,0.0006337824,0.001091496,0.0005435039,0.001938524],"genre_scores_gemma":[0.7813771,0.001221716,0.2123886,0.0003370705,0.00006437811,0.0008138533,0.001019688,0.00008425164,0.002693383],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002330861,"threshold_uncertainty_score":0.01002598,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05929223183682236,"score_gpt":0.3230543276197088,"score_spread":0.2637620957828864,"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."}}