{"id":"W4409727390","doi":"10.54985/peeref.2504a8958069","title":"Determination of Formaldehyde from Multiple Types of Test Specimens by HPLC/DAD","year":2025,"lang":"en","type":"article","venue":"","topic":"Advanced Chemical Sensor Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"George Brown College","funders":"","keywords":"Formaldehyde; Chromatography; High-performance liquid chromatography; Test (biology); Chemistry; Biology; Botany; Organic chemistry","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":[0.0008241499,0.00136539,0.0006637656,0.001324318,0.0006135634,0.0005815989,0.0009025632,0.0006283308,0.001925735],"category_scores_gemma":[0.0007420881,0.000478196,0.0004844213,0.000474733,0.0004553628,0.0005672119,0.0003188505,0.0009563399,0.0007388393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005104083,"about_ca_system_score_gemma":0.0006806692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002429083,"about_ca_topic_score_gemma":0.006931364,"domain_scores_codex":[0.9992025,0.00007107922,0.00005468403,0.0002826734,0.0003019042,0.00008709448],"domain_scores_gemma":[0.9995592,0.0001119645,0.00004508856,0.0000639292,0.0001778464,0.00004193179],"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":[0.00009190545,0.00006267222,0.0009365026,0.00009404904,0.00003868882,0.0000485279,0.00003373608,0.00008074947,0.9905719,0.00006331544,0.0001453927,0.007832503],"study_design_scores_gemma":[0.000006414047,0.000199744,0.002971502,0.00001171774,0.00004782765,0.0001928763,0.00003248465,0.0006399992,0.9943396,0.00004318569,0.001501691,0.0000129871],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6872452,0.01037861,0.283543,0.0005654477,0.0009945595,0.00125402,0.002995753,0.002731619,0.01029189],"genre_scores_gemma":[0.7017908,0.005963141,0.2739111,0.0009597525,0.0001885105,0.0009067082,0.00273689,0.0003135851,0.01322946],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002429083,"threshold_uncertainty_score":0.006442249,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003919805759903475,"score_gpt":0.2017166624365865,"score_spread":0.197796856676683,"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."}}