{"id":"W3162763322","doi":"10.1145/3411764.3445749","title":"EvalMe: Exploring the Value of New Technologies for In Situ Evaluation of Learning Experiences","year":2021,"lang":"en","type":"article","venue":"","topic":"Mobile Learning in Education","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Autodesk (Canada)","funders":"Engineering and Physical Sciences Research Council; Arts and Humanities Research Council","keywords":"In situ; Value (mathematics); Computer science; Machine learning; Physics","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":[0.008262055,0.0007022601,0.0003778574,0.001338432,0.0009249203,0.005572102,0.001593795,0.001272314,0.003568655],"category_scores_gemma":[0.01624779,0.0003270354,0.0004123417,0.0006421859,0.003424841,0.006144864,0.005159263,0.000979711,0.0003891438],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009549654,"about_ca_system_score_gemma":0.0004811764,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004470379,"about_ca_topic_score_gemma":0.0009883665,"domain_scores_codex":[0.9942945,0.0038225,0.0001626727,0.0004091562,0.0009714838,0.0003397992],"domain_scores_gemma":[0.9879826,0.00963278,0.0005057885,0.0009912839,0.0005869598,0.0003005148],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001365604,0.0006452426,0.01543464,0.003301543,0.0001235304,0.002429502,0.127597,0.007796986,0.1341097,0.1199884,0.003344588,0.5838632],"study_design_scores_gemma":[0.0004224509,0.006459503,0.03752504,0.004854818,0.0003258669,0.007445335,0.1389778,0.07084438,0.2485583,0.1049275,0.3789099,0.0007492422],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4698773,0.002287703,0.476001,0.001832891,0.0002995341,0.0007260255,0.0002218736,0.0009241062,0.04782955],"genre_scores_gemma":[0.8584833,0.0005999568,0.1334817,0.0001831857,0.00005394907,0.000475298,0.00007551201,0.0001438053,0.006503334],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008262055,"threshold_uncertainty_score":0.04369444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09616421279728761,"score_gpt":0.3479731745082584,"score_spread":0.2518089617109708,"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."}}