{"id":"W2243208470","doi":"","title":"Getting Into Position: Serious Gaming in Geomatics","year":2009,"lang":"en","type":"article","venue":"E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education","topic":"Educational Games and Gamification","field":"Psychology","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University; Université Laval","funders":"","keywords":"Geomatics; Position (finance); Geography; Computer science; Data science; Remote sensing; Business","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.0006108327,0.0005914019,0.0001655146,0.0004161974,0.001198034,0.002898617,0.0008724345,0.001282111,0.02200345],"category_scores_gemma":[0.002512006,0.0001321092,0.0002836158,0.0002673852,0.001077323,0.002413574,0.002386904,0.001295619,0.003167119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004307892,"about_ca_system_score_gemma":0.0006179803,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002424639,"about_ca_topic_score_gemma":0.008654133,"domain_scores_codex":[0.999605,0.0001766792,0.000009864032,0.00005128359,0.00006707088,0.0000900345],"domain_scores_gemma":[0.9991764,0.0002449263,0.00003403854,0.00004905833,0.00006345695,0.0004319462],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008125906,0.002540838,0.02506541,0.0006468323,0.00008207175,0.001618952,0.04461095,0.001341133,0.01544133,0.07506292,0.1474953,0.6852816],"study_design_scores_gemma":[0.0003241727,0.001826004,0.06772949,0.0008515955,0.0001934404,0.003509961,0.07391781,0.01191232,0.01058048,0.1218478,0.7071065,0.0002004962],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5891637,0.002239902,0.03806241,0.01882441,0.001646504,0.0003635234,0.0003925071,0.00206807,0.3472389],"genre_scores_gemma":[0.8934811,0.001183286,0.02502516,0.003021404,0.0001841872,0.0001366255,0.000405389,0.0002543793,0.07630848],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02200345,"threshold_uncertainty_score":0.07360888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05250919683380946,"score_gpt":0.3329640169633847,"score_spread":0.2804548201295753,"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."}}