{"id":"W4405075194","doi":"10.33965/celda2024_202408l012","title":"ASSESSMENT OF BARRIERS TO EDUCATIONAL TECHNOLOGY ACCEPTANCE","year":2024,"lang":"en","type":"article","venue":"","topic":"Gender and Technology in Education","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Computer science; 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":[0.01244011,0.0005268425,0.0007999753,0.003187046,0.0006674048,0.001996569,0.0007014972,0.0007395162,0.003939755],"category_scores_gemma":[0.07166968,0.000275171,0.001108555,0.001127832,0.0007454821,0.001540448,0.002200667,0.001107387,0.0004392004],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009931845,"about_ca_system_score_gemma":0.00219704,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001125418,"about_ca_topic_score_gemma":0.001474991,"domain_scores_codex":[0.9832391,0.007153301,0.001429605,0.0003803682,0.006829882,0.0009677676],"domain_scores_gemma":[0.9049609,0.06296451,0.01156554,0.002130137,0.01571929,0.002659517],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006429314,0.00235879,0.7806613,0.001509911,0.0002405349,0.0003987218,0.02651952,0.001244046,0.005118784,0.003443596,0.0008316577,0.1770302],"study_design_scores_gemma":[0.00008178225,0.005647455,0.8975046,0.001510686,0.0003811421,0.00141707,0.04798662,0.008314385,0.01632909,0.004414015,0.01619265,0.0002205383],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9869522,0.0004156028,0.003721613,0.0002448836,0.00002596796,0.0003775509,0.0001036875,0.00002973241,0.008128727],"genre_scores_gemma":[0.9950386,0.0003121307,0.002766058,0.00004746426,0.00001016913,0.0003680654,0.0001048851,0.00001230521,0.001340378],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01244011,"threshold_uncertainty_score":0.0657903,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01544493554509778,"score_gpt":0.3983152908629267,"score_spread":0.3828703553178289,"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."}}