{"id":"W4412412865","doi":"10.1061/jwrmd5.wreng-6719","title":"Water’s for Fightin’: Lessons on Water Management Learned through Serious Gaming","year":2025,"lang":"en","type":"article","venue":"Journal of Water Resources Planning and Management","topic":"Environmental Education and Sustainability","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Environmental science; Water resource management; Business; Environmental resource management; Environmental planning; Natural resource economics; Environmental economics; Computer science; Economics","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":[],"consensus_categories":[],"category_scores_codex":[0.0006052171,0.0001794357,0.0002053268,0.0001099137,0.0003163183,0.0001009671,0.000235717,0.00004517655,0.0002417495],"category_scores_gemma":[0.000003496613,0.00009717821,0.00009216769,0.00004100199,0.00008248332,0.0001524662,0.0003549305,0.0001338342,0.00003956505],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001999524,"about_ca_system_score_gemma":9.467279e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000147917,"about_ca_topic_score_gemma":0.000001319937,"domain_scores_codex":[0.9986038,0.00005820921,0.0003751949,0.0002891043,0.0002646665,0.0004090799],"domain_scores_gemma":[0.9996375,0.00001800669,0.00006368862,0.000202378,0.000006508462,0.00007193182],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.006087919,0.004535969,0.04850448,0.006315041,0.003498542,0.001580415,0.295021,0.1775618,0.02111996,0.003467459,0.2054121,0.2268953],"study_design_scores_gemma":[0.001118283,0.000218423,0.008333424,0.000140879,0.0001160434,0.00001089285,0.0092311,0.00009207397,0.01576058,0.003036484,0.9617456,0.0001961763],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9590219,0.00006933047,0.00154744,0.01114861,0.000244899,0.0004740848,0.000001369352,0.0000206079,0.02747174],"genre_scores_gemma":[0.9619911,0.0000891591,0.001532579,0.00140429,0.00004025002,0.00005189537,0.000009706059,0.00001518899,0.03486587],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7563335,"threshold_uncertainty_score":0.3962812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01695795172356824,"score_gpt":0.2875925670080273,"score_spread":0.2706346152844591,"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."}}