{"id":"W2611270003","doi":"10.1002/lom3.10186","title":"Methodological biases in estimates of macroalgal macromolecular composition","year":2017,"lang":"en","type":"article","venue":"Limnology and Oceanography Methods","topic":"Seaweed-derived Bioactive Compounds","field":"Agricultural and Biological Sciences","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mount Allison University","funders":"Canada Research Chairs; New Brunswick Innovation Foundation; Gordon and Betty Moore Foundation","keywords":"Macromolecule; Carbohydrate; Extraction (chemistry); Chemistry; Nitrogen; Sample preparation; Composition (language); Food science; Chromatography; Biochemistry","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":[],"consensus_categories":[],"category_scores_codex":[0.001178875,0.0001723198,0.0004169519,0.00006243176,0.0003188235,0.00004864854,0.0003716129,0.0002392056,0.00006032888],"category_scores_gemma":[0.0006449453,0.000075542,0.0001371835,0.0001857273,0.0008608063,0.0001208086,0.0002066729,0.0002000721,8.953585e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005740478,"about_ca_system_score_gemma":0.00000370036,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001156945,"about_ca_topic_score_gemma":0.00004835429,"domain_scores_codex":[0.9980787,0.0009140698,0.0002555671,0.0003633745,0.00008120565,0.0003070933],"domain_scores_gemma":[0.9975175,0.002003983,0.0002183728,0.0001348954,0.00005371943,0.00007157528],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001209985,0.00008726973,0.2688106,0.000007608627,0.00003353788,0.00001556755,0.00003560028,8.172866e-7,0.6335912,0.0006623129,0.000006092834,0.0966284],"study_design_scores_gemma":[0.0002049554,0.0003257041,0.7988678,0.00002725437,0.00002246856,0.00003059474,0.00009002427,0.000136912,0.1914545,0.008545542,0.0001559503,0.0001382986],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9963168,0.0009871732,0.001155507,0.000679476,0.0001322162,0.0001340531,0.0000186336,0.00003900423,0.000537175],"genre_scores_gemma":[0.8761303,0.0001712013,0.1235277,0.0001054066,0.00003468672,0.000007480619,0.00001911125,0.000001010315,0.000003131415],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5300572,"threshold_uncertainty_score":0.3171677,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.17788664341699,"score_gpt":0.404915511999285,"score_spread":0.2270288685822951,"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."}}