{"id":"W2031849362","doi":"10.1002/ece3.508","title":"High‐Throughput Sequencing: A Roadmap Toward Community Ecology","year":2013,"lang":"en","type":"article","venue":"Ecology and Evolution","topic":"Microbial Community Ecology and Physiology","field":"Environmental Science","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Université du Québec à Rimouski","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Toolbox; Ecology; Throughput; Data science; Computer science; Diversity (politics); Biology; Sociology","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004593339,0.0001597351,0.0002592335,0.00004345548,0.0009019764,0.00001065518,0.0002892379,0.0004017523,0.01147546],"category_scores_gemma":[0.0001128497,0.0001575098,0.00004017806,0.0001223318,0.0008591669,0.0002679669,0.0005427875,0.000729237,0.003181683],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003747417,"about_ca_system_score_gemma":0.00003109989,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008785875,"about_ca_topic_score_gemma":0.01561667,"domain_scores_codex":[0.9979647,0.001126213,0.0002246164,0.000222116,0.0000414583,0.0004208817],"domain_scores_gemma":[0.999153,0.0003125695,0.00009811039,0.0003261056,0.00001721975,0.00009297401],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009099848,0.0004936956,0.8226913,0.00003412654,0.00008319752,0.000007486607,0.00330299,0.0009712817,0.07895813,0.01085611,0.08179892,0.000711725],"study_design_scores_gemma":[0.0003558788,0.0004465259,0.9357113,0.000001934314,0.0000152659,0.00004892038,0.0003617618,0.000223524,0.0001326053,0.06156363,0.0009799828,0.0001586795],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935301,0.00002282974,0.0001153098,0.001456124,0.0004397584,0.0002792249,0.000003625974,0.00006557727,0.004087426],"genre_scores_gemma":[0.9972315,0.00002068946,0.0006316392,0.001524359,0.00004517378,0.00006039054,0.00003803697,0.000008553799,0.0004396171],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.11302,"threshold_uncertainty_score":0.9978147,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01883584238949153,"score_gpt":0.2199512995199413,"score_spread":0.2011154571304498,"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."}}