{"id":"W2761232955","doi":"10.16995/dscn.284","title":"What’s Under the Big Tent?: A Study of ADHO Conference Abstracts","year":2017,"lang":"en","type":"article","venue":"Digital Studies / Le champ numérique","topic":"Wikis in Education and Collaboration","field":"Social Sciences","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Humanities; Political science; Rhetoric; Digital humanities; Library science; Art; Computer science; Philosophy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.01260498,0.000495433,0.0006816818,0.007994712,0.01370646,0.02066276,0.002052536,0.001863012,0.02234008],"category_scores_gemma":[0.07576314,0.0004447961,0.0004010217,0.01485467,0.004333762,0.01343734,0.007321143,0.003343777,0.002892235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00823863,"about_ca_system_score_gemma":0.006704949,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01322631,"about_ca_topic_score_gemma":0.01554765,"domain_scores_codex":[0.9875205,0.006201517,0.0007783395,0.0008761658,0.003230938,0.00139254],"domain_scores_gemma":[0.9410255,0.03750301,0.007732392,0.001460069,0.006571067,0.005707893],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0001836946,0.0002127118,0.02192659,0.0008475892,0.00003782346,0.0006848738,0.8862332,0.00007592666,0.000575069,0.0150767,0.01944837,0.05469748],"study_design_scores_gemma":[0.0000110391,0.00007491006,0.02575142,0.000386344,0.00001323955,0.0001468689,0.8427251,0.00007265782,0.0001344726,0.001069382,0.1295798,0.00003486998],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7765255,0.006320089,0.001285555,0.01749223,0.0007572785,0.0003640268,0.0009561122,0.0001129833,0.1961862],"genre_scores_gemma":[0.9652387,0.003880619,0.0004619999,0.001977379,0.0006754095,0.0003797063,0.0003995127,0.0001716328,0.02681499],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9920053,"threshold_uncertainty_score":0.07473505,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1101691852981274,"score_gpt":0.379981611134697,"score_spread":0.2698124258365696,"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."}}