{"id":"W7057998016","doi":"","title":"Making Sense of Mitigation Used to Address Industrial Effects on&#13;\\nWildlife in Canadian Environmental Assessments","year":2015,"lang":"en","type":"other","venue":"YorkSpace (York University)","topic":"Magnetic Field Sensors Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Work (physics); Process (computing); Context (archaeology); Sustainability; Government (linguistics); Limiting","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009035795,0.0004754387,0.0003188642,0.002747284,0.02306083,0.007620479,0.001749414,0.001264923,0.002201989],"category_scores_gemma":[0.0132921,0.0003454509,0.0003647178,0.003309271,0.01133632,0.002914816,0.005866365,0.002494159,0.0001060394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.09118886,"about_ca_system_score_gemma":0.1032108,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9779388,"about_ca_topic_score_gemma":0.9920213,"domain_scores_codex":[0.9924293,0.002539139,0.0002965614,0.0006859666,0.002631625,0.001417372],"domain_scores_gemma":[0.9908071,0.003301082,0.0009639809,0.0002795647,0.003285219,0.00136308],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00005056686,0.00005706962,0.0452074,0.0003460033,0.00002394967,0.0006360147,0.8405181,0.0006622216,0.001560105,0.01814939,0.01095355,0.08183564],"study_design_scores_gemma":[0.000004311691,0.00002421438,0.06084353,0.0004041031,0.00002772943,0.0001200475,0.8233836,0.0005467064,0.0006383847,0.001748495,0.1121522,0.0001067236],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8707262,0.003039531,0.004001562,0.02386722,0.0001755356,0.0001987071,0.0002640399,0.00007950697,0.09764769],"genre_scores_gemma":[0.9893791,0.00163469,0.002221798,0.0009525091,0.00001195222,0.00003861096,0.00006151213,0.00002152276,0.005678421],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09118886,"threshold_uncertainty_score":0.6616246,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02549312485281165,"score_gpt":0.2325374124088538,"score_spread":0.2070442875560422,"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."}}