{"id":"W2038310925","doi":"10.1371/journal.pcbi.1003972","title":"A Quick Guide for Building a Successful Bioinformatics Community","year":2015,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Ontario Institute for Cancer Research","funders":"Common Fund; Biotechnology and Biological Sciences Research Council; Engineering and Physical Sciences Research Council; Government of Ontario; National Human Genome Research Institute; Klaus Tschira Stiftung; Bundesministerium für Bildung und Forschung; European Molecular Biology Laboratory; National Institutes of Health; Ontario Institute for Cancer Research","keywords":"Context (archaeology); Field (mathematics); Public relations; Knowledge management; Engineering ethics; Computer science; Political science; Biology; Engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.0008022509,0.0001735168,0.0002162515,0.0001117431,0.0001918019,0.00004148699,0.0004774237,0.0002287165,0.000008504948],"category_scores_gemma":[0.001438684,0.000151298,0.0000959876,0.0001167191,0.0003092339,0.000008313365,0.0003283266,0.0001807358,0.00003645883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000401752,"about_ca_system_score_gemma":0.0003821955,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004219247,"about_ca_topic_score_gemma":0.00002834322,"domain_scores_codex":[0.9985487,0.0001439274,0.0004974651,0.0001746216,0.0002314358,0.0004038061],"domain_scores_gemma":[0.9984656,0.0002106899,0.0001410124,0.0002728815,0.000638945,0.0002708609],"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":[0.003308766,0.004554264,0.04390422,0.002755918,0.003131707,0.00001011848,0.006890198,0.02308407,0.3045726,0.03741273,0.3902323,0.180143],"study_design_scores_gemma":[0.009606007,0.008775813,0.002768756,0.0001136344,0.00011924,0.0001073386,0.003552021,0.3506939,0.04704489,0.05941929,0.5160885,0.001710643],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.615238,0.0002787338,0.3789183,0.001069842,0.0003636,0.0007336168,0.0003093242,0.00005310193,0.003035569],"genre_scores_gemma":[0.8317637,0.0000461174,0.1636691,0.001405187,0.0003742558,0.00007364543,0.002405132,0.00002290218,0.0002399691],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3276098,"threshold_uncertainty_score":0.6169752,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05772293337235274,"score_gpt":0.3446849327599997,"score_spread":0.2869619993876469,"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."}}