{"id":"W2496859834","doi":"10.1385/1-59259-765-3:011","title":"Reverse Sample Genome Probing to Monitor Microbial Communities","year":2009,"lang":"en","type":"book-chapter","venue":"Environmental Microbiology","topic":"Microbial Community Ecology and Physiology","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Microbial population biology; Fish <Actinopterygii>; Microbial ecology; Sample (material); Fluorescence in situ hybridization; Biology; Variety (cybernetics); Diversity (politics); Computational biology; Ecology; Computer science; Bacteria; Artificial intelligence; Fishery; Chemistry; Gene; Genetics; 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":[],"consensus_categories":[],"category_scores_codex":[0.000638633,0.0009540656,0.0005739672,0.0007600377,0.0002961296,0.0008866979,0.001093946,0.001162555,0.01074622],"category_scores_gemma":[0.0004311335,0.0006095931,0.0005546826,0.0007237335,0.0004266705,0.0009299634,0.000874299,0.002510922,0.01655153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003325716,"about_ca_system_score_gemma":0.0002400514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003108445,"about_ca_topic_score_gemma":0.0009549483,"domain_scores_codex":[0.9994665,0.0000741175,0.00001512625,0.0001795714,0.000233334,0.00003146118],"domain_scores_gemma":[0.9997584,0.0000991335,0.00001994196,0.00005128133,0.0000529977,0.00001828456],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003624112,0.00004532391,0.0001634541,0.0004335953,0.00001738884,0.0001006461,0.00008118286,0.0001932444,0.8846176,0.004687724,0.008954318,0.1006693],"study_design_scores_gemma":[0.00001907398,0.0001531665,0.0008703553,0.00007490756,0.00003689371,0.001722969,0.00005977199,0.002470921,0.6084961,0.004665432,0.3813977,0.00003273792],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01835228,0.03401677,0.8446143,0.001442204,0.00213483,0.0004932988,0.00234444,0.005761889,0.09083992],"genre_scores_gemma":[0.06319686,0.02497828,0.6999774,0.004051983,0.0003683752,0.001141697,0.006139813,0.001607553,0.1985381],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01074622,"threshold_uncertainty_score":0.03594965,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01169720841305033,"score_gpt":0.1951197739994043,"score_spread":0.183422565586354,"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."}}