{"id":"W7092181148","doi":"10.6084/m9.figshare.30370708.v2","title":"Supplementary Material 2. Qualitative Coding Hierarchy","year":2025,"lang":"","type":"article","venue":"Figshare","topic":"Advanced Statistical Modeling Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Coding (social sciences); Hierarchy; Qualitative analysis; Encoding (memory); Hierarchical control system","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.008877273,0.0008441753,0.0005824907,0.006635896,0.002441558,0.003059608,0.001444646,0.0008625388,0.5054891],"category_scores_gemma":[0.07310216,0.0005497951,0.0005162974,0.009822479,0.001109987,0.002316772,0.001959036,0.001707612,0.0679816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004551056,"about_ca_system_score_gemma":0.007923651,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009437992,"about_ca_topic_score_gemma":0.01704764,"domain_scores_codex":[0.9949347,0.002334516,0.0005957608,0.0005249698,0.001385633,0.0002243824],"domain_scores_gemma":[0.9004575,0.0695743,0.002170363,0.003924757,0.02299579,0.0008773803],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002088894,0.0001207544,0.0015855,0.003905345,0.00001438611,0.0001478801,0.01352586,0.0007417359,0.0007640687,0.04040245,0.8332364,0.1053467],"study_design_scores_gemma":[0.0001944266,0.0001107732,0.0077738,0.004375209,0.00002962062,0.00026963,0.01968447,0.002457504,0.001617593,0.05465702,0.908689,0.0001410686],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.007639395,0.0002624002,0.069212,0.002152741,0.0008483142,0.008977262,0.8352732,0.002482329,0.0731523],"genre_scores_gemma":[0.0700274,0.0007877813,0.3109075,0.001716079,0.0002644052,0.08415092,0.4349698,0.003414566,0.09376158],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.5054891,"threshold_uncertainty_score":0.7053598,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07469264808834315,"score_gpt":0.4004996982177391,"score_spread":0.3258070501293959,"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."}}