{"id":"W2294147879","doi":"","title":"Blending Science Knowledge and AI Gaming Techniques for Experiential Learning","year":2007,"lang":"en","type":"article","venue":"Summit (Simon Fraser University)","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Beluga Whale; Beluga; Experiential learning; Whale; Rendering (computer graphics); Situated; Citizen science; Computer science; Marine mammal; Human–computer interaction; Fishery; Psychology; Artificial intelligence; Oceanography; Geology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005636839,0.0001119335,0.0001037035,0.0006033825,0.0008574965,0.0001162236,0.0007658512,0.00006300263,0.000003811444],"category_scores_gemma":[0.00004235876,0.0001334477,0.00004146426,0.001350086,0.0002860548,0.0009558115,0.0004820204,0.0001601355,0.000004978865],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001805274,"about_ca_system_score_gemma":0.0001028168,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002329649,"about_ca_topic_score_gemma":0.0007293344,"domain_scores_codex":[0.9988554,0.0000231871,0.0001172475,0.0004741026,0.0001612992,0.0003687986],"domain_scores_gemma":[0.9992163,0.000115739,0.00007373758,0.0002857026,0.0001571964,0.0001513502],"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":[0.00005656577,0.0002618652,0.06722883,0.00008349344,0.00004275857,0.00004973704,0.001397033,0.0001004491,0.006309741,0.6247,0.003280646,0.2964889],"study_design_scores_gemma":[0.0006663016,0.0001522073,0.0005851939,0.00006700553,0.00002745063,8.123371e-8,0.01242158,0.0291308,0.1810345,0.0008531687,0.7745613,0.0005004759],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02833122,0.00005141748,0.9625865,0.0001748687,0.00009493096,0.0002570537,0.000001773959,0.0003112965,0.008190949],"genre_scores_gemma":[0.9799981,0.00001758751,0.01894999,0.0000453994,0.00004456674,0.000002509116,0.00000292172,0.000007912839,0.0009310858],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9516668,"threshold_uncertainty_score":0.6595256,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01386043443282221,"score_gpt":0.2655097645877405,"score_spread":0.2516493301549183,"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."}}