{"id":"W2489529667","doi":"10.1016/j.tree.2016.07.002","title":"Transparency in Ecology and Evolution: Real Problems, Real Solutions","year":2016,"lang":"en","type":"article","venue":"Trends in Ecology & Evolution","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":208,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal","funders":"Australian Research Council; Laura and John Arnold Foundation; National Science Foundation","keywords":"Transparency (behavior); Incentive; Ecology; Interpretation (philosophy); Data science; Computer science; Management science; Economics; Biology; Computer security; Microeconomics","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":["metaresearch","open_science"],"consensus_categories":[],"category_scores_codex":[0.01792648,0.0005361433,0.001194293,0.001431592,0.003201392,0.01155716,0.001509029,0.007653388,0.009069361],"category_scores_gemma":[0.03835796,0.0005508268,0.0006826402,0.001521905,0.0302466,0.02620261,0.005472154,0.008207236,0.0005519442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004323481,"about_ca_system_score_gemma":0.004065559,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002613007,"about_ca_topic_score_gemma":0.002300313,"domain_scores_codex":[0.9908327,0.005387616,0.000301122,0.0008357488,0.001817544,0.0008252408],"domain_scores_gemma":[0.9437165,0.04290684,0.003699617,0.003265858,0.003642249,0.002768817],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006902734,0.00006902425,0.003081504,0.0004640479,0.0000593152,0.0002135721,0.002210363,0.001614081,0.000428743,0.9226131,0.01429879,0.05487831],"study_design_scores_gemma":[0.00002970425,0.00002127549,0.001229062,0.0002428666,0.0000155075,0.0001684318,0.001635738,0.001779192,0.0001643125,0.9773297,0.01734984,0.00003425727],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.06991114,0.06184126,0.05672784,0.7590258,0.003135553,0.00005741443,0.0002481227,0.0002149424,0.04883791],"genre_scores_gemma":[0.9506642,0.01659106,0.01365619,0.01146437,0.00269489,0.00008202843,0.00006795327,0.00008052131,0.004698666],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.998491,"threshold_uncertainty_score":0.09480542,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03116036390670309,"score_gpt":0.2609137116440053,"score_spread":0.2297533477373022,"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."}}