{"id":"W4319983352","doi":"10.1098/rsfs.2022.0073","title":"Cultivating a more effective culture to advance the engineering of microbial communities","year":2023,"lang":"en","type":"article","venue":"Interface Focus","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Data science; World Wide Web","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001914851,0.0001023943,0.0001596947,0.0001820002,0.0001533911,0.0001993131,0.001241534,0.00002159831,0.00003516835],"category_scores_gemma":[0.001981267,0.00006106663,0.00006498517,0.001336253,0.00006796658,0.0001179374,0.0008274574,0.0001386671,0.000281447],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002070703,"about_ca_system_score_gemma":0.000007072818,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001475524,"about_ca_topic_score_gemma":0.00005680612,"domain_scores_codex":[0.9986699,0.0000982167,0.0003049962,0.000243733,0.0004813625,0.0002017577],"domain_scores_gemma":[0.9977046,0.001196721,0.0001011341,0.0007890936,0.0001714289,0.0000370011],"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":[0.00006880779,0.00005435776,0.001171806,0.00003310128,0.00007512684,0.000006357519,0.1027197,0.2279947,0.1256987,0.0006717987,0.3156539,0.2258516],"study_design_scores_gemma":[0.000542079,0.0002480717,0.008242248,0.0005887774,0.00001918966,0.000009769195,0.1009381,0.05363088,0.1846983,0.001202899,0.6494312,0.0004485006],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9544942,0.0001859116,0.04125786,0.001453176,0.001030044,0.0003727446,0.00005185176,0.0001285822,0.001025671],"genre_scores_gemma":[0.9967806,0.000001271307,0.001067565,0.00002968977,0.00003864251,0.00001672202,0.000001253951,0.000006956664,0.002057276],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3337772,"threshold_uncertainty_score":0.3617526,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04563013337672363,"score_gpt":0.370281376522302,"score_spread":0.3246512431455784,"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."}}