{"id":"W2749368005","doi":"10.1007/s10530-017-1545-7","title":"Early detection of a highly invasive bivalve based on environmental DNA (eDNA)","year":2017,"lang":"en","type":"article","venue":"Biological Invasions","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":77,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; National Natural Science Foundation of China; Canada Research Chairs","keywords":"Environmental DNA; Biology; Mussel; Abundance (ecology); Primer (cosmetics); Invasive species; Sampling (signal processing); Ecology; Zoology; 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":[0.0003799847,0.0003615268,0.0002102244,0.0007689371,0.0003279268,0.0005618591,0.0003221639,0.001093564,0.00142694],"category_scores_gemma":[0.0009252425,0.0002432836,0.0002010998,0.0002731825,0.0004653255,0.0004511513,0.000833041,0.0005069622,0.0006192458],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001410592,"about_ca_system_score_gemma":0.0001390644,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007644832,"about_ca_topic_score_gemma":0.002083106,"domain_scores_codex":[0.9996551,0.00003336891,0.00001703386,0.0001348011,0.00009285802,0.00006683786],"domain_scores_gemma":[0.999045,0.0003126426,0.0001787372,0.00005940894,0.0002189932,0.0001852145],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000286017,0.00006241573,0.1785201,0.0001128573,0.0000253416,0.0004487527,0.0004333878,0.000122446,0.8039019,0.0002006968,0.0001597762,0.01572633],"study_design_scores_gemma":[0.00001680691,0.0007367372,0.787632,0.0001027464,0.00008928282,0.003844396,0.001360262,0.002234658,0.1973855,0.0006553245,0.005907353,0.00003494332],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9852347,0.0005408575,0.008804587,0.0001013696,0.00005071417,0.00004172382,0.0004045128,0.00007199322,0.004749621],"genre_scores_gemma":[0.9883741,0.0001680282,0.008047547,0.0001990896,0.00001415715,0.00002643204,0.0003579587,0.000009798049,0.002802952],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9992355,"threshold_uncertainty_score":0.004773557,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09632139981685059,"score_gpt":0.2280252472359032,"score_spread":0.1317038474190526,"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."}}