{"id":"W4406979612","doi":"10.1093/plankt/fbae078","title":"Identifying zooplankton fecal pellets from <i>in situ</i> images","year":2025,"lang":"en","type":"article","venue":"Journal of Plankton Research","topic":"Marine and coastal ecosystems","field":"Earth and Planetary Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Fisheries and Oceans Canada; Memorial University of Newfoundland","funders":"Institut Universitaire de France; Canada Excellence Research Chairs, Government of Canada; Agence Nationale de la Recherche; Centre National de la Recherche Scientifique; Sorbonne Université; Université Laval","keywords":"Pellets; Zooplankton; Pellet; Feces; Environmental science; Bay; Settling; Oceanography; Biology; Ecology; Geology; Environmental engineering","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":[0.002634452,0.0001129996,0.0003088703,0.0007043393,0.0001404638,0.0002293401,0.0005152942,0.00009623258,0.001558683],"category_scores_gemma":[0.0001734322,0.00008890356,0.00009164252,0.0006108892,0.00006641143,0.0003018411,0.00006105992,0.0009171725,0.0002049206],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002116097,"about_ca_system_score_gemma":0.000270212,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008468826,"about_ca_topic_score_gemma":0.0160405,"domain_scores_codex":[0.9975285,0.0004266285,0.0005452475,0.0001980069,0.0008642674,0.0004373417],"domain_scores_gemma":[0.9984864,0.0008831734,0.000128131,0.0001734857,0.0001837756,0.000145033],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006677244,0.00009128587,0.8563568,0.0001352377,0.00008501873,0.001738602,0.0003364,0.0002965848,0.00483856,0.0001056074,0.05308531,0.0822629],"study_design_scores_gemma":[0.001818558,0.0004276691,0.8990339,0.0007217088,0.00002325526,0.000128457,0.00217038,0.001497688,0.005010783,0.007090252,0.08180697,0.0002703873],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8872144,0.00244164,0.0001315664,0.0007617056,0.0007020719,0.0001315075,0.00006579769,0.000008143033,0.1085432],"genre_scores_gemma":[0.9968485,0.0003469936,0.0001969582,0.00008346382,0.0002535456,4.530444e-7,0.0000304556,0.000002828489,0.002236791],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1096341,"threshold_uncertainty_score":0.999354,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04075092036270472,"score_gpt":0.3235524240231746,"score_spread":0.2828015036604699,"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."}}