{"id":"W4388862557","doi":"10.1002/mrc.5409","title":"<sup>13</sup>C‐depleted algae as food: Permitting background free <i>in‐vivo</i> nuclear magnetic resonance of <scp><i>Daphnia magna</i></scp> at natural abundance","year":2023,"lang":"en","type":"article","venue":"Magnetic Resonance in Chemistry","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"Ontario Ministry of Research and Innovation; Natural Sciences and Engineering Research Council of Canada; Krembil Foundation; Canada Foundation for Innovation; Government of Ontario","keywords":"Chemistry; Daphnia magna; Daphnia; Algae; Abundance (ecology); Branchiopoda; Environmental chemistry; Zoology; Botany; Ecology; Cladocera; Toxicity; Biology; Crustacean","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":[0.0002795657,0.0002551954,0.0002021354,0.0001330447,0.0004074964,0.0006463244,0.0005067767,0.0005059439,0.001492395],"category_scores_gemma":[0.0002792187,0.0002335784,0.0001166123,0.00018845,0.0006361979,0.0003535225,0.000434765,0.0007189419,0.000449655],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007940381,"about_ca_system_score_gemma":0.0006351159,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006488608,"about_ca_topic_score_gemma":0.01898185,"domain_scores_codex":[0.9998546,0.00001872932,0.000009404051,0.00005153734,0.00003281929,0.00003295736],"domain_scores_gemma":[0.9996448,0.00008254043,0.00007611933,0.00006360845,0.00008162721,0.00005127086],"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":[0.0005210488,0.00001166311,0.0006081999,0.00002906539,0.000008935764,0.0000272471,0.00003462031,0.00006783564,0.997367,0.0001374501,0.0001736018,0.001013392],"study_design_scores_gemma":[0.00002325178,0.0001658573,0.01319247,0.00001113741,0.00003379309,0.00009524496,0.000105701,0.0006733097,0.9821947,0.0001345641,0.003353127,0.00001679624],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9898084,0.0003459112,0.003230663,0.0003324861,0.00004536004,0.00002174442,0.001382521,0.00009879672,0.004734198],"genre_scores_gemma":[0.9865699,0.0003864478,0.003772057,0.0003542935,0.00001285924,0.0000391569,0.001399163,0.0001744142,0.007291745],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006488608,"threshold_uncertainty_score":0.01290172,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00880524539949436,"score_gpt":0.2231159800454492,"score_spread":0.2143107346459548,"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."}}