{"id":"W4300061831","doi":"10.1002/essoar.10512102.1","title":"Building bridges over troubled waters","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Transboundary Water Resource Management","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Water security; Influencer marketing; Intervention (counseling); Natural (archaeology); Climate change; Key (lock); Adaptation (eye); Environmental planning; Political science; Environmental resource management; Environmental science; Business; Computer science; Geography; Ecology; Computer security; Psychology; Water resources","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009830301,0.000238179,0.0002814659,0.000192221,0.0008191626,0.0006199318,0.001100538,0.000130713,0.007757888],"category_scores_gemma":[0.00001604065,0.0002350791,0.0002316314,0.0001409329,0.0001983078,0.00009117602,0.001415181,0.0005413499,0.00004581712],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006366771,"about_ca_system_score_gemma":0.0001540762,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03036221,"about_ca_topic_score_gemma":0.001245052,"domain_scores_codex":[0.9972808,0.000341178,0.0002731923,0.0006132934,0.0009333454,0.0005581608],"domain_scores_gemma":[0.9992454,0.0000432293,0.00009501492,0.0004609549,0.00002285586,0.0001325159],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001523722,0.0004897568,0.04802496,0.0007542105,0.00118488,0.0003121001,0.1528661,0.0443987,0.0001867468,0.658674,0.06823432,0.02472185],"study_design_scores_gemma":[0.0002238148,0.00001245495,0.003352202,0.00001975716,0.00004868103,1.824628e-7,0.002517916,0.00007333376,0.00003730345,0.00418108,0.9891784,0.0003549198],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6281272,0.00009676499,0.005459651,0.01281043,0.002947866,0.001483461,0.00003416018,0.001028799,0.3480116],"genre_scores_gemma":[0.9576328,0.00007887476,0.002691592,0.0007414371,0.0004055963,0.0001699793,0.00003435764,0.00004766424,0.03819772],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.920944,"threshold_uncertainty_score":0.9931492,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03149626684115505,"score_gpt":0.3253650886616725,"score_spread":0.2938688218205174,"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."}}