{"id":"W6958551399","doi":"10.6084/m9.figshare.c.5444063","title":"SMILE: systems metabolomics using interpretable learning and evolution","year":2021,"lang":"en","type":"other","venue":"Figshare","topic":"Legal and Regulatory Analysis","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; Queen's University","funders":"","keywords":"Interpretability; Metabolomics; Visualization; Process (computing); Interface (matter); Mechanism (biology); Interpretation (philosophy); Supervised learning; Data visualization","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":[0.002720795,0.0006439031,0.0005771602,0.001165058,0.0005947919,0.001297917,0.001321906,0.0009831823,0.00769272],"category_scores_gemma":[0.007715656,0.0002957704,0.001587131,0.000732768,0.001305464,0.001433559,0.001798719,0.001469076,0.0009230755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008943877,"about_ca_system_score_gemma":0.0009108672,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00131312,"about_ca_topic_score_gemma":0.00104518,"domain_scores_codex":[0.9990295,0.0005586323,0.0000367665,0.0001356205,0.0001920041,0.00004745147],"domain_scores_gemma":[0.9970623,0.001962507,0.0002609973,0.0003813282,0.0002552924,0.0000776204],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000143263,0.0001336071,0.005180582,0.0003138846,0.0001717363,0.0004289295,0.0002454855,0.6608171,0.004689023,0.2218278,0.005903935,0.1001447],"study_design_scores_gemma":[0.000009349001,0.00001778179,0.000215129,0.00001115916,0.000007876965,0.00002834122,0.000009424707,0.9404943,0.0008138014,0.05643491,0.001949857,0.000008043778],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01324818,0.00008720483,0.9811224,0.0006304584,0.00003832341,0.00005565105,0.0003447602,0.002279568,0.0021935],"genre_scores_gemma":[0.3959936,0.0002194026,0.5984656,0.0002886718,0.0000815554,0.0004370628,0.001292909,0.0006973586,0.002523766],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00769272,"threshold_uncertainty_score":0.02573472,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0308106434693076,"score_gpt":0.2951166207068741,"score_spread":0.2643059772375664,"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."}}