{"id":"W4299815006","doi":"10.22541/au.166023903.39620339/v1","title":"HOW DEEP DO YOU GO? CLINICAL PREDICTION OF NASOPHARYNGEAL DEPTH BASED ON FACIAL MEASUREMENTS","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Sinusitis and nasal conditions","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Medicine; Otorhinolaryngology; Nuclear medicine; Orthodontics; Surgery","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0007579911,0.0002793643,0.0002541872,0.0006114079,0.0001683912,0.0006141376,0.0002551499,0.0004896172,0.001535201],"category_scores_gemma":[0.00594085,0.0001308071,0.0002574219,0.0002944205,0.0003097184,0.0007238442,0.0003227105,0.0003986617,0.0005888366],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002208065,"about_ca_system_score_gemma":0.0001331028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001783987,"about_ca_topic_score_gemma":0.002636709,"domain_scores_codex":[0.9996038,0.0001138365,0.00005790721,0.0000816586,0.00009657771,0.00004631923],"domain_scores_gemma":[0.9982637,0.0005861343,0.0006555885,0.00005859172,0.0002965815,0.0001395044],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000707707,0.00001724121,0.9916221,0.00001608066,0.00002363134,0.00008761538,0.00008191846,0.000102671,0.0003864677,0.00002922654,0.0002982287,0.00726411],"study_design_scores_gemma":[0.000006550934,0.0001588056,0.9957754,0.00003557711,0.00002932276,0.001185223,0.0005199689,0.001300591,0.0003322934,0.0001128504,0.0005326393,0.00001082104],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949397,0.0008544304,0.0009203284,0.000265461,0.00003017881,0.0000275247,0.0003668476,0.00001366856,0.00258191],"genre_scores_gemma":[0.9987092,0.0002740431,0.0005470786,0.00005549701,0.00001314345,0.00001042138,0.0001475958,0.000002838306,0.0002402386],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001783987,"threshold_uncertainty_score":0.005135775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1269352984070835,"score_gpt":0.3573307670944303,"score_spread":0.2303954686873468,"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."}}