{"id":"W4394294787","doi":"10.6084/m9.figshare.12097170","title":"Additional file 2 of E. coli diversity: low in colorectal cancer","year":2020,"lang":"en","type":"dataset","venue":"Figshare","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Colorectal cancer; Diversity (politics); Biology; Computer science; Genetics; Cancer; Political science","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001013728,0.001226841,0.001421739,0.002027565,0.0006672805,0.002049959,0.001889758,0.001785871,0.5345775],"category_scores_gemma":[0.01187838,0.0005916624,0.001182133,0.003683953,0.0003106851,0.001452518,0.001285051,0.001239676,0.1091172],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009934031,"about_ca_system_score_gemma":0.001552013,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009313967,"about_ca_topic_score_gemma":0.0167935,"domain_scores_codex":[0.9994122,0.00008877907,0.00008871534,0.0002202031,0.0000871204,0.0001029835],"domain_scores_gemma":[0.9947658,0.003349609,0.0004274329,0.000493346,0.0006534552,0.0003105056],"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":[0.0003119385,0.00005134623,0.004219437,0.003930534,0.0001012963,0.00005523565,0.00003727286,0.0004880511,0.0001591099,0.0005639971,0.9856047,0.004477122],"study_design_scores_gemma":[0.00370388,0.0001644624,0.03347955,0.003052438,0.0003236279,0.0004711309,0.0002332512,0.001265929,0.0006845905,0.00610823,0.9504061,0.0001067114],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005777714,0.00001734,0.00002754069,0.00002606398,0.00000460015,0.000007772186,0.9996715,0.00005253138,0.000134937],"genre_scores_gemma":[0.001688476,0.00007407028,0.0004294427,0.0001638054,0.00001904341,0.0002171655,0.9962307,0.000132559,0.001044734],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.5345775,"threshold_uncertainty_score":0.6638687,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01761427471631574,"score_gpt":0.2476953509260087,"score_spread":0.230081076209693,"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."}}