{"id":"W4206850212","doi":"10.1002/lno.12101","title":"Machine learning techniques to characterize functional traits of plankton from image data","year":2022,"lang":"en","type":"review","venue":"Limnology and Oceanography","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":97,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada; Dalhousie University; Université Laval","funders":"Agencia Estatal de Investigación; Natural Environment Research Council; Natural Sciences and Engineering Research Council of Canada; College of Natural Resources and Sciences, Humboldt State University; Ministerio de Ciencia e Innovación; Institut Universitaire de France; Centre National de la Recherche Scientifique; Belmont Forum; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Fonds Wetenschappelijk Onderzoek; Eidgenössische Technische Hochschule Zürich; Agence Nationale de la Recherche; Sight Research UK; Vlaamse regering; Université Laval; Gordon and Betty Moore Foundation; Sorbonne Université; Simons Foundation; National Science Foundation","keywords":"Plankton; Trait; Suite; Computer science; Artificial intelligence; Ecology; Machine learning; Biology; Geography","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002623432,0.0002579138,0.000757416,0.0002099444,0.0002784202,0.000008132632,0.0005043581,0.0001894345,0.004067971],"category_scores_gemma":[0.00004681371,0.0002269409,0.0001092957,0.0003295073,0.000341922,0.0001313233,0.002070318,0.000477822,0.00003739952],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001465705,"about_ca_system_score_gemma":0.000006418607,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003643395,"about_ca_topic_score_gemma":0.0001138614,"domain_scores_codex":[0.9985452,0.0001810619,0.0003210938,0.00061133,0.0001170159,0.0002242962],"domain_scores_gemma":[0.9991989,0.0002191691,0.000225202,0.0003107919,0.000002473836,0.00004349813],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000743577,0.0001924539,0.02682893,0.001125372,0.0008550383,0.00003604967,0.0001862776,3.605389e-7,0.00001119817,0.0001299788,0.03668734,0.9338726],"study_design_scores_gemma":[0.00007323625,0.0001619474,0.02777847,0.000109656,0.0003256295,0.000007049621,0.00002013746,0.000001436374,0.000001184828,0.00009515721,0.9712312,0.0001949363],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0008235042,0.9887935,0.0001542244,0.0003397882,0.0003486321,0.0008826707,0.001713259,0.0002092765,0.006735138],"genre_scores_gemma":[0.00004467589,0.9960322,0.001008804,0.0004004871,0.00003841982,0.00007020209,0.002161867,0.00001764845,0.0002256695],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9345438,"threshold_uncertainty_score":0.9968424,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04402984691256302,"score_gpt":0.260522148099483,"score_spread":0.21649230118692,"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."}}