{"id":"W4390046132","doi":"10.5311/josis.2023.27.307","title":"Reimagining GIScience education for enhanced employability","year":2023,"lang":"en","type":"article","venue":"Journal of Spatial Information Science","topic":"Geography Education and Pedagogy","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Employability; Geography; Data science; Computer science; Sociology; Pedagogy","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005547875,0.00005712361,0.0001017742,0.0007896951,0.0008596871,0.0003258016,0.0005372598,0.00003342791,0.0000732059],"category_scores_gemma":[0.003283188,0.00004601835,0.00007501942,0.001754631,0.0006677863,0.005011149,0.00002703756,0.0001057782,0.00005195241],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001206846,"about_ca_system_score_gemma":0.005037588,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001176718,"about_ca_topic_score_gemma":0.0001570071,"domain_scores_codex":[0.9982205,0.00004249728,0.0005030544,0.00008527392,0.0008735607,0.0002750842],"domain_scores_gemma":[0.9967603,0.0001610183,0.00056414,0.0001194906,0.002198893,0.0001961427],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004899275,0.00008917125,0.02562855,0.00003412615,0.000005560103,1.004058e-7,0.09857659,0.0004943133,0.003397986,0.02598706,0.003496606,0.8422409],"study_design_scores_gemma":[0.0006045577,0.0002793241,0.3042547,0.00008734308,0.00001819225,0.000006608074,0.05953557,0.001357414,0.006062471,0.01587862,0.6115749,0.0003402743],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7976028,0.00002296723,0.1256059,0.02193444,0.01259785,0.0007662727,0.000009485449,0.0001236411,0.04133666],"genre_scores_gemma":[0.9967855,0.00004744745,0.0022616,0.0004045552,0.0003102585,0.0000120125,0.000002276011,0.000001691521,0.0001746228],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8419006,"threshold_uncertainty_score":0.8936465,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04356390112471439,"score_gpt":0.4237467840321306,"score_spread":0.3801828829074162,"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."}}