{"id":"W2920215701","doi":"10.1093/database/baz033","title":"Update on cpnDB: a reference database of chaperonin sequences","year":2019,"lang":"en","type":"article","venue":"Database","topic":"Heat shock proteins research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Chaperonin; GroEL; Biology; Phylogenetic tree; Computational biology; Identification (biology); Sequence analysis; Sequence (biology); Database; Computer science; Genetics; Ecology; Gene","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001958091,0.001378439,0.001428089,0.009665181,0.0008018455,0.00205224,0.001886302,0.0009143528,0.01438127],"category_scores_gemma":[0.007518647,0.0007136022,0.0007369794,0.01026749,0.000327944,0.002280723,0.002121347,0.001992546,0.01498475],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001066086,"about_ca_system_score_gemma":0.0032865,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008586314,"about_ca_topic_score_gemma":0.008752844,"domain_scores_codex":[0.9989102,0.0001031396,0.0002126535,0.0001971478,0.0004685176,0.0001083434],"domain_scores_gemma":[0.9957183,0.0004937125,0.0004349979,0.0005939417,0.002240098,0.0005189653],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001230236,0.0001676418,0.004735138,0.005458907,0.0001647182,0.0004890327,0.0003400775,0.0007138667,0.03229562,0.003018788,0.6395702,0.3118159],"study_design_scores_gemma":[0.00004147187,0.00004156337,0.006183854,0.0004812636,0.00007823874,0.0004702569,0.00005145531,0.0004409968,0.004048959,0.0007736717,0.9873313,0.00005695258],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.02870242,0.03228949,0.03347457,0.003165719,0.003215843,0.0003251673,0.8514359,0.02420158,0.02318921],"genre_scores_gemma":[0.009995289,0.006735811,0.0364784,0.0006107329,0.0002912884,0.0001829878,0.9362626,0.001999442,0.007443412],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01438127,"threshold_uncertainty_score":0.04811013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03033648656265123,"score_gpt":0.3165121856923562,"score_spread":0.2861756991297049,"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."}}