{"id":"W4362600795","doi":"10.24908/iqurcp16459","title":"Journals","year":2023,"lang":"en","type":"article","venue":"Inquiry Queen s Undergraduate Research Conference Proceedings","topic":"Artificial Intelligence Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Publishing; Session (web analytics); Queen (butterfly); Moderation; Scope (computer science); Library science; Sociology; Political science; Psychology; Computer science; World Wide Web; Law; Social psychology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003936175,0.0002298278,0.00025768,0.001198017,0.0008837046,0.001803474,0.003079216,0.0001487109,0.00004293853],"category_scores_gemma":[0.0008828508,0.0002200089,0.00009419837,0.00599201,0.0006164953,0.001896866,0.001290078,0.0008890843,0.005218928],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001719112,"about_ca_system_score_gemma":0.0005110234,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000133213,"about_ca_topic_score_gemma":0.000008615692,"domain_scores_codex":[0.9952853,0.00009700347,0.0005361724,0.000899456,0.001834402,0.001347648],"domain_scores_gemma":[0.9956456,0.0004103764,0.0001390243,0.0005886489,0.002761495,0.0004548308],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000005263347,0.00004704397,0.000797054,0.00002312848,0.00002060142,0.00001616417,0.002996822,0.000008847429,0.009365933,0.8990192,0.06003596,0.02766402],"study_design_scores_gemma":[0.00009715922,0.0001165757,0.001325634,0.0001036669,0.000003242959,0.00001986369,0.001817679,0.0313217,0.01813217,0.9250644,0.02165753,0.000340343],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0677868,0.0001074076,0.5329379,0.366718,0.0006735986,0.001652492,0.000006130418,0.003288191,0.0268295],"genre_scores_gemma":[0.9924995,0.000809826,0.00342284,0.0001614912,0.0002755572,0.0002978915,0.000003585552,0.00002908128,0.002500204],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9247127,"threshold_uncertainty_score":0.9992328,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2916563475549718,"score_gpt":0.4565487603401903,"score_spread":0.1648924127852184,"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."}}