{"id":"W3067142208","doi":"10.1139/facets-2020-0021","title":"Ten simple rules to facilitate evidence implementation in the environmental sciences","year":2020,"lang":"en","type":"article","venue":"FACETS","topic":"Environmental Education and Sustainability","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Leverage (statistics); Simple (philosophy); Checklist; Reuse; Management science; Computer science; Data science; Knowledge management; Engineering ethics; Engineering; Psychology; Epistemology; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0005414718,0.0001223407,0.000090958,0.00002021499,0.0002062044,0.00005156801,0.0004526257,0.00002353844,0.005371578],"category_scores_gemma":[0.0000921543,0.00009177617,0.00003594723,0.0002475174,0.0002618924,0.0003559658,0.0002185667,0.00009689951,0.001961156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002530111,"about_ca_system_score_gemma":0.00001326102,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005798563,"about_ca_topic_score_gemma":0.0001655398,"domain_scores_codex":[0.9984567,0.0001628344,0.0002169478,0.0004142535,0.000449753,0.0002995662],"domain_scores_gemma":[0.9995586,0.00008934143,0.00003851799,0.0001833012,8.548951e-7,0.0001293615],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001538398,0.00009396479,0.9339108,0.000007658019,0.000001962972,0.000003171045,0.03001559,0.001901439,0.008573501,0.00004756265,0.009245123,0.01618379],"study_design_scores_gemma":[0.0001302646,0.0001604683,0.9511336,0.000002347058,0.000002948918,0.000001399347,0.02316733,0.0001850704,0.0007288028,0.0003239357,0.02402908,0.0001347791],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9806284,0.00003991844,0.000114109,0.01734343,0.00002422343,0.0005927688,0.00002469439,0.00001644472,0.001215963],"genre_scores_gemma":[0.9931536,0.00001447587,0.0004666841,0.006186924,0.00001506437,0.00007231463,0.00001206309,0.000005024275,0.00007383614],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01722273,"threshold_uncertainty_score":0.998816,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05949737849770188,"score_gpt":0.3239499092991114,"score_spread":0.2644525308014095,"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."}}