{"id":"W7077040505","doi":"10.5061/dryad.kh18932kn","title":"Data for: Getting over it? A proteomic analysis of mechanisms driving multigenerational acclimation to organic ultraviolet filters in Daphnia magna","year":2025,"lang":"en","type":"dataset","venue":"Open MIND","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Daphnia magna; Acclimatization; Toxicity; Ecotoxicology; Xenobiotic; Invertebrate","routes":{"ca_aff":true,"ca_fund":false,"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":[0.002062545,0.0003328914,0.0006049065,0.0007881161,0.001371492,0.00225226,0.0005217994,0.001133575,0.007423216],"category_scores_gemma":[0.002580808,0.000317202,0.0007491469,0.001193075,0.0006160802,0.002959611,0.00153574,0.001732334,0.002658713],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007672931,"about_ca_system_score_gemma":0.0008894379,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002175256,"about_ca_topic_score_gemma":0.00350521,"domain_scores_codex":[0.9990001,0.0001308883,0.0001101851,0.0003175327,0.0003188381,0.0001225173],"domain_scores_gemma":[0.9975923,0.0002870213,0.0005262749,0.0003695474,0.0009052143,0.0003196334],"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":[0.001747166,0.0001993812,0.1053641,0.003002428,0.0005346966,0.002025121,0.003201468,0.0002323275,0.6865461,0.003801148,0.04942829,0.1439178],"study_design_scores_gemma":[0.00005782966,0.0006260535,0.484161,0.001267126,0.0005837314,0.002698189,0.007076915,0.001015106,0.1148709,0.005753755,0.3816697,0.0002197667],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.84137,0.02416553,0.01336427,0.04461645,0.003465359,0.0002608075,0.04844253,0.001213828,0.02310122],"genre_scores_gemma":[0.8465061,0.01464486,0.02520833,0.02312035,0.000734912,0.0003388404,0.05404836,0.0009784721,0.03441975],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.007423216,"threshold_uncertainty_score":0.02483314,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04274175354606776,"score_gpt":0.3269137378428305,"score_spread":0.2841719842967628,"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."}}