{"id":"W2971052335","doi":"10.1130/abs/2019am-338739","title":"STUDENTS MAPPING DRUMLINS: INCORPORATING DIGITAL DRUMLIN IDENTIFICATION INTO UNDERGRADUATE TEACHING","year":2019,"lang":"en","type":"article","venue":"Abstracts with programs - Geological Society of America","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Drumlin; Identification (biology); Computer science; Geology","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":[0.001414734,0.0004509413,0.0002204171,0.0009348356,0.000636793,0.002181896,0.001067191,0.0007135396,0.009657538],"category_scores_gemma":[0.00961371,0.0002977838,0.000226265,0.000676155,0.0001917839,0.002385593,0.002301401,0.0006105292,0.003099355],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000562221,"about_ca_system_score_gemma":0.001409381,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004445821,"about_ca_topic_score_gemma":0.01495271,"domain_scores_codex":[0.9992906,0.0002790682,0.00003278727,0.0002072739,0.0001241862,0.00006617749],"domain_scores_gemma":[0.9965189,0.001547761,0.0002457003,0.0004272593,0.0007144324,0.0005460766],"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":[0.0005506862,0.00221465,0.08234943,0.0001662796,0.00004674453,0.0002116403,0.004943864,0.005410799,0.01274175,0.001632552,0.01898906,0.8707425],"study_design_scores_gemma":[0.0004302164,0.002898404,0.1949564,0.0005090076,0.0003366217,0.0006859925,0.03948985,0.473246,0.08526611,0.02948476,0.1723331,0.0003636664],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7457467,0.0001185504,0.1961199,0.00151314,0.0002493828,0.0006968934,0.001442384,0.01143228,0.04268076],"genre_scores_gemma":[0.7554064,0.000110444,0.2303559,0.0002477061,0.00004035594,0.0002230196,0.001055303,0.0003579843,0.01220297],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009657538,"threshold_uncertainty_score":0.03230768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01406581563303445,"score_gpt":0.2719366034879666,"score_spread":0.2578707878549322,"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."}}