{"id":"W4210287589","doi":"10.1016/j.cmpb.2022.106673","title":"Hierarchical autoclassification of cryo-EM samples and macromolecular energy landscape determination","year":2022,"lang":"en","type":"article","venue":"Computer Methods and Programs in Biomedicine","topic":"Advanced Electron Microscopy Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Ministerio de Ciencia e Innovación","keywords":"Computer science; Inference; Cluster analysis; Data mining; Bayesian probability; Homogeneous; Hierarchical clustering; Bayesian inference; Artificial intelligence; Machine learning; Pattern recognition (psychology); Mathematics","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":[0.004259723,0.001313275,0.001332441,0.003356907,0.001191944,0.002136819,0.002754692,0.001639368,0.00304397],"category_scores_gemma":[0.01168806,0.0005363574,0.001803171,0.001579523,0.001070568,0.001513298,0.001853083,0.00247777,0.001705992],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001414027,"about_ca_system_score_gemma":0.001449857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004581552,"about_ca_topic_score_gemma":0.007644221,"domain_scores_codex":[0.9972475,0.0005086072,0.0001911056,0.001018679,0.0007859615,0.0002481002],"domain_scores_gemma":[0.9938172,0.002196377,0.0008860075,0.00166617,0.001203842,0.0002304154],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009136404,0.0006058404,0.04089433,0.001142291,0.00048889,0.0002723862,0.001254219,0.1435872,0.09921862,0.01027263,0.01559656,0.6857535],"study_design_scores_gemma":[0.00003543812,0.00008180973,0.01459823,0.0000819839,0.00007208179,0.0002349939,0.000222937,0.921675,0.04529213,0.0108459,0.006788228,0.00007123434],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1362221,0.0005426041,0.8498067,0.000327394,0.00009281471,0.0003652389,0.001439452,0.009312747,0.001890923],"genre_scores_gemma":[0.2936244,0.0002285971,0.6972472,0.0001962177,0.00004832288,0.0004555615,0.005211274,0.001814571,0.001173943],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004581552,"threshold_uncertainty_score":0.02252781,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02516973112527951,"score_gpt":0.3660861459133418,"score_spread":0.3409164147880623,"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."}}