{"id":"W2884408080","doi":"10.3791/58059","title":"The Identification of Sea Lamprey Pheromones Using Bioassay-Guided Fractionation","year":2018,"lang":"en","type":"article","venue":"Journal of Visualized Experiments","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fisheries and Oceans Canada; College of Engineering, Michigan State University; U.S. Fish and Wildlife Service; U.S. Geological Survey; Michigan State University; Great Lakes Fishery Commission","keywords":"Sex pheromone; Bioassay; Pheromone; Lamprey; Biology; Fractionation; Olfaction; Identification (biology); Computational biology; Chromatography; Neuroscience; Chemistry; Zoology; Ecology; Fishery","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006952852,0.00007006559,0.0001195246,0.00004121173,0.0003209568,0.00002092867,0.0001739513,0.00003629323,0.0003528607],"category_scores_gemma":[0.0001243632,0.00005003083,0.00005275393,0.0001369955,0.0002562116,0.0003121329,0.00009414656,0.00004921429,0.0000392024],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001089898,"about_ca_system_score_gemma":0.000007783288,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004720525,"about_ca_topic_score_gemma":0.00003067471,"domain_scores_codex":[0.9988768,0.00009640319,0.0005141904,0.00008728574,0.0003146789,0.0001107155],"domain_scores_gemma":[0.9989677,0.00005510932,0.0007722187,0.0001065747,0.00007363908,0.00002476883],"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":[0.0003870986,0.0005553887,0.08832153,0.00001021744,0.0003799698,0.000004468617,0.00261393,0.0001739723,0.8488393,0.0003307474,0.05649344,0.001889976],"study_design_scores_gemma":[0.001655145,0.0003463011,0.2487301,0.00003092685,0.0001026827,0.00002321813,0.001749977,0.003067431,0.726805,0.001372951,0.01593562,0.0001806008],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946965,0.00006540376,0.00235078,0.0002330277,0.0006973522,0.0001188121,7.822737e-7,0.000006056067,0.001831269],"genre_scores_gemma":[0.9982069,0.00009097919,0.001094665,0.0001052395,0.00008316879,0.000003688318,6.619443e-7,0.000006064721,0.0004086847],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1604086,"threshold_uncertainty_score":0.3863578,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04447227848606827,"score_gpt":0.4219864321402672,"score_spread":0.3775141536541989,"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."}}