{"id":"W6997621323","doi":"","title":"Why choose this one? Factors in scientists' selection of bioinformatics tools","year":2011,"lang":"en","type":"article","venue":"eScholarship@McGill (McGill)","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Dalhousie University","keywords":"Selection (genetic algorithm); Identification (biology); Variation (astronomy); Usability; Feature selection; Sequence (biology)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0667678,0.0004918186,0.0006279608,0.00466946,0.005354487,0.008554213,0.00170287,0.002854534,0.002393097],"category_scores_gemma":[0.2526307,0.0006532864,0.0008950961,0.003995304,0.005537501,0.006286335,0.002912412,0.003064326,0.0008790524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003624131,"about_ca_system_score_gemma":0.006141362,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005018802,"about_ca_topic_score_gemma":0.005750628,"domain_scores_codex":[0.9097527,0.05468563,0.00798279,0.004339328,0.01899954,0.004239996],"domain_scores_gemma":[0.6683867,0.2507547,0.03060284,0.00573818,0.03243802,0.01207953],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009833042,0.0006089884,0.4801117,0.00253718,0.0006020998,0.002270683,0.3169484,0.001133496,0.006064803,0.008399105,0.01998901,0.1603511],"study_design_scores_gemma":[0.0003763822,0.001082785,0.3183534,0.00222505,0.0005825228,0.003955691,0.5354991,0.006109692,0.005303034,0.0279672,0.09772214,0.0008229917],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9311526,0.002247899,0.02087138,0.02407425,0.000330246,0.0004726361,0.0002644337,0.000301155,0.02028546],"genre_scores_gemma":[0.9851072,0.0007312241,0.01053546,0.002230029,0.0001074254,0.0001690749,0.0001105386,0.00009133002,0.0009176618],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9332322,"threshold_uncertainty_score":0.3531061,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04235973405650275,"score_gpt":0.2471661202084192,"score_spread":0.2048063861519165,"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."}}