{"id":"W4313363291","doi":"10.22148/001c.55507","title":"Conceptual Forays: A Corpus-based Study of “Theory” in Digital Humanities Journals","year":2022,"lang":"en","type":"article","venue":"Journal of Cultural Analytics","topic":"Digital Humanities and Scholarship","field":"Arts and Humanities","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Narrative; Narratology; Subject (documents); Perspective (graphical); Digital humanities; Semantics (computer science); Literary theory; Interpretation (philosophy); Epistemology; Field (mathematics); Heuristic; Sociology; Computer science; Linguistics; Humanities; Artificial intelligence; Literary criticism; Mathematics; Philosophy; World Wide Web","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":[0.01566899,0.0003696072,0.0006274634,0.02117312,0.009285017,0.01290492,0.00211572,0.001834538,0.004232962],"category_scores_gemma":[0.0745191,0.0005356577,0.0003547414,0.03084583,0.02249863,0.02003182,0.008572211,0.003304369,0.0004171628],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008269928,"about_ca_system_score_gemma":0.004475874,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007189532,"about_ca_topic_score_gemma":0.01378863,"domain_scores_codex":[0.9877649,0.007439412,0.0009625561,0.001291061,0.002087035,0.0004550263],"domain_scores_gemma":[0.8735979,0.1047298,0.008052205,0.006253332,0.00570429,0.001662472],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.00006345407,0.00005627169,0.008284908,0.0007671968,0.00002697174,0.0007201938,0.8054963,0.0001773058,0.0009930319,0.1502783,0.005271167,0.02786492],"study_design_scores_gemma":[0.00002479169,0.00005259705,0.01791771,0.001350526,0.00003682745,0.0007621396,0.7127453,0.001185215,0.001083988,0.04598681,0.2187957,0.00005845162],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8857383,0.007992866,0.014951,0.01345715,0.0006238178,0.0004704806,0.003287803,0.0001257333,0.07335298],"genre_scores_gemma":[0.983923,0.002201363,0.008014813,0.000613109,0.0002025775,0.0003276695,0.001591391,0.000212926,0.002913185],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9788269,"threshold_uncertainty_score":0.08286655,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1228525614456737,"score_gpt":0.2842866195238496,"score_spread":0.161434058078176,"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."}}