{"id":"W4394304157","doi":"10.6084/m9.figshare.23811522","title":"Ecosystem Education with Augmented Reality: A Flexible Tool for In-Field Learning","year":2023,"lang":"en","type":"dataset","venue":"Figshare","topic":"Educational Games and Gamification","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Augmented reality; Field (mathematics); Ecosystem; Computer science; Human–computer interaction; Ecology; Environmental science; Environmental resource management; Biology; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008290253,0.00162478,0.0008342238,0.003198995,0.0007508562,0.001408502,0.002397837,0.001679979,0.01907151],"category_scores_gemma":[0.003755146,0.0004141611,0.001257415,0.00397603,0.0003497285,0.0009774603,0.002444936,0.001309535,0.03256928],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001192722,"about_ca_system_score_gemma":0.001364474,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05976515,"about_ca_topic_score_gemma":0.1615799,"domain_scores_codex":[0.999301,0.0001496472,0.00007732034,0.0001845025,0.0001670252,0.0001204953],"domain_scores_gemma":[0.9988029,0.00033533,0.0001153767,0.0002857866,0.0003231951,0.0001374144],"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":[0.0002214782,0.0001089846,0.006471604,0.001589511,0.00007927685,0.00009795015,0.0001360447,0.0009331991,0.000333351,0.0007536067,0.9688281,0.020447],"study_design_scores_gemma":[0.0002615788,0.00005405804,0.02323732,0.0007545229,0.00006819164,0.0001371092,0.0003889005,0.001943265,0.001018678,0.001911168,0.9701495,0.00007560071],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001012698,0.0002055085,0.0004034836,0.0001287061,0.00004391381,0.00005461562,0.995499,0.001028021,0.001624033],"genre_scores_gemma":[0.001884218,0.000115939,0.001343203,0.00005498932,0.000008196241,0.0002219945,0.9953579,0.0000634739,0.0009501285],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05976515,"threshold_uncertainty_score":0.1188346,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07063689132858285,"score_gpt":0.3793535128865896,"score_spread":0.3087166215580068,"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."}}