{"id":"W2969493263","doi":"10.1016/j.scitotenv.2019.134000","title":"Environmental sciences benefit from robust evidence irrespective of speed","year":2019,"lang":"en","type":"article","venue":"The Science of The Total Environment","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"Environment and Climate Change Canada; Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada; Environment and Climate Change Canada","keywords":"Focus (optics); Environmental research; Data science; Computer science; Environmental science; Environmental resource management","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":["metaresearch"],"category_scores_codex":[0.3836213,0.004424665,0.01779348,0.01317621,0.00159467,0.0124844,0.005424787,0.01146971,0.01349276],"category_scores_gemma":[0.8009149,0.00499258,0.0108457,0.009135149,0.009144564,0.03467503,0.0103557,0.0138469,0.005188812],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005011344,"about_ca_system_score_gemma":0.007092042,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002074482,"about_ca_topic_score_gemma":0.002258129,"domain_scores_codex":[0.668322,0.2371592,0.0374412,0.02242314,0.03254688,0.002107696],"domain_scores_gemma":[0.1718463,0.7312068,0.02522614,0.04752328,0.02224944,0.001948116],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.008804618,0.000383308,0.01163268,0.1509709,0.07578854,0.0009838715,0.001802455,0.01458398,0.001410514,0.2255896,0.06240829,0.4456412],"study_design_scores_gemma":[0.00356747,0.000785963,0.00410419,0.02255437,0.01878375,0.0007443144,0.0004421664,0.008704495,0.0009002418,0.8816614,0.05739498,0.0003565724],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"review","genre_gemma":"commentary","genre_scores_codex":[0.007223372,0.4246629,0.3691307,0.1447447,0.02496549,0.002985646,0.004237425,0.002159645,0.0198901],"genre_scores_gemma":[0.3198331,0.1849664,0.3887212,0.05821734,0.03095565,0.006727583,0.002598491,0.002519696,0.005460613],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.6163787,"threshold_uncertainty_score":0.7601047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4222424456400266,"score_gpt":0.3974609373401112,"score_spread":0.02478150829991543,"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."}}