{"id":"W4221007319","doi":"10.1002/rra.3939","title":"Voicing Rivers","year":2022,"lang":"en","type":"article","venue":"River Research and Applications","topic":"Water Governance and Infrastructure","field":"Social Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Voice; Environmental science; Geology; Hydrology (agriculture); Computer science; Geotechnical engineering; Speech recognition","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":[0.004962354,0.001179571,0.001125618,0.002269673,0.004508401,0.01589343,0.0019139,0.006649344,0.1393365],"category_scores_gemma":[0.02009431,0.0005661997,0.001208379,0.001345354,0.001969795,0.01035846,0.006052325,0.007567723,0.0460162],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001536852,"about_ca_system_score_gemma":0.00301799,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007922552,"about_ca_topic_score_gemma":0.002508809,"domain_scores_codex":[0.9954575,0.001209759,0.0003587618,0.000885495,0.001607972,0.0004805372],"domain_scores_gemma":[0.9857836,0.004551383,0.001065305,0.0009966304,0.003395649,0.004207501],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002027764,0.00001011829,0.00009424283,0.0001364052,0.000004159684,0.0000777747,0.0003038798,0.00001541771,0.0001508023,0.003140528,0.9755396,0.02050693],"study_design_scores_gemma":[0.000002496008,0.000008050255,0.0000724103,0.00007190465,0.00000201285,0.00005201263,0.0001928799,0.000009647692,0.00003312022,0.0006107264,0.9989403,0.000004480321],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"empirical","genre_scores_codex":[0.0009686607,0.02507431,0.002063737,0.1498553,0.7415413,0.0001040916,0.0003949181,0.001169249,0.07882853],"genre_scores_gemma":[0.01141426,0.01885274,0.002977125,0.0897695,0.403816,0.0001919842,0.0008103799,0.002215527,0.4699524],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1393365,"threshold_uncertainty_score":0.4661272,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05612118980162521,"score_gpt":0.3878338802696603,"score_spread":0.3317126904680351,"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."}}