{"id":"W7132982591","doi":"","title":"Towards Multiplexed Nuclear Magnetic Resonance for Environmental Analysis","year":2025,"lang":"","type":"dissertation","venue":"TSpace","topic":"Environmental Toxicology and Ecotoxicology","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ontario Ministry of Research and Innovation; Natural Sciences and Engineering Research Council of Canada; Fundação de Amparo à Pesquisa do Estado de São Paulo; Krembil Foundation; University of Toronto; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Health Canada; Government of Ontario","keywords":"Daphnia magna; Environmental analysis; Modularity (biology); Key (lock); Pulse sequence; Characterization (materials science); Tracking (education)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00349676,0.001524874,0.001074167,0.001592136,0.0004439168,0.00174428,0.001751233,0.002219282,0.002974693],"category_scores_gemma":[0.002753288,0.0009597866,0.000551222,0.001339617,0.001116931,0.00237707,0.002335799,0.002764649,0.001766964],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000926297,"about_ca_system_score_gemma":0.0008232731,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006840198,"about_ca_topic_score_gemma":0.001605909,"domain_scores_codex":[0.9970982,0.0006438814,0.0001075994,0.001189591,0.0007671656,0.0001935971],"domain_scores_gemma":[0.9983882,0.0004697766,0.0002267747,0.0002564719,0.0005127343,0.0001460965],"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":[0.0002443814,0.000132811,0.001155313,0.0004537034,0.0001172344,0.0002552775,0.0001565133,0.002012059,0.8899741,0.01153221,0.002484504,0.09148195],"study_design_scores_gemma":[0.00006098251,0.0006085125,0.001719299,0.0001900265,0.0001285828,0.0008899195,0.0001776525,0.04346386,0.8518004,0.01538563,0.08534787,0.0002272533],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02412735,0.005765511,0.957239,0.001181994,0.0005684565,0.0003128314,0.0009735272,0.003494008,0.006337356],"genre_scores_gemma":[0.1039072,0.003495093,0.8856484,0.001034914,0.0002769384,0.0005239901,0.0008748248,0.0002349252,0.004003775],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00349676,"threshold_uncertainty_score":0.01849288,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01212357795685972,"score_gpt":0.2945005332636316,"score_spread":0.2823769553067719,"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."}}