{"id":"W2063633070","doi":"10.1016/j.bbrc.2006.02.037","title":"On the correlation between genomic G+C content and optimal growth temperature in prokaryotes: Data quality and confounding factors","year":2006,"lang":"en","type":"review","venue":"Biochemical and Biophysical Research Communications","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":92,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Institute for Advanced Research; Dalhousie University","funders":"","keywords":"GC-content; Biology; Content (measure theory); Correlation; Genome; Confounding; Positive correlation; Genetics; Gene; Mathematics; Statistics","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":[0.008310067,0.001190977,0.00360262,0.001861126,0.0003306615,0.002484428,0.003249761,0.002315101,0.001604628],"category_scores_gemma":[0.01890302,0.0007269927,0.0004729274,0.005579111,0.002545266,0.003607408,0.001115263,0.002492048,0.001480002],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001540949,"about_ca_system_score_gemma":0.002262542,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002305472,"about_ca_topic_score_gemma":0.002109028,"domain_scores_codex":[0.9977924,0.0005351634,0.0003033195,0.0005060089,0.0007739688,0.00008911601],"domain_scores_gemma":[0.9648442,0.02905822,0.001636832,0.0007488823,0.003423595,0.0002882624],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002701339,0.00003970751,0.001654089,0.01247301,0.0002000611,0.0002548689,0.0001483026,0.00150741,0.007586414,0.01071633,0.01566501,0.9494847],"study_design_scores_gemma":[0.0001505113,0.0006086114,0.01778233,0.0198092,0.001626351,0.00438326,0.0005800696,0.003194096,0.03539385,0.07806372,0.8379617,0.0004462818],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001038866,0.9917004,0.004124049,0.001756482,0.0004222875,0.00001123895,0.000127194,0.00004419535,0.0007752366],"genre_scores_gemma":[0.006027726,0.9881677,0.003687809,0.0008119891,0.0007674956,0.00002152224,0.0002152059,0.00002618194,0.0002743201],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.008310067,"threshold_uncertainty_score":0.04394835,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3662164024863104,"score_gpt":0.4496752219322083,"score_spread":0.08345881944589789,"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."}}