{"id":"W3135456059","doi":"10.17504/protocols.io.u83ezyn","title":"Ultrasound for Small Animal Imaging v1","year":2018,"lang":"en","type":"preprint","venue":"","topic":"Body Composition Measurement Techniques","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Ultrasound; Biomedical engineering; Ultrasound imaging; Medicine; Radiology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000456889,0.000266806,0.0003752633,0.000153916,0.00006649223,0.00007223256,0.000193003,0.0001887752,0.0004321794],"category_scores_gemma":[0.0001361917,0.0002429297,0.0002318454,0.0000457067,0.00009195352,0.00003053926,0.0001856708,0.0003494832,0.00004370065],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001756881,"about_ca_system_score_gemma":0.0001757279,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004014199,"about_ca_topic_score_gemma":0.000008704964,"domain_scores_codex":[0.998611,0.0000252031,0.0003265159,0.0005102703,0.0002549287,0.00027205],"domain_scores_gemma":[0.9985471,0.00007503355,0.000127293,0.0005913813,0.0005413098,0.0001178359],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006695635,0.0004177416,0.02904679,0.001595963,0.0003397388,0.00002319373,0.0001534299,6.418098e-7,0.554834,0.002311148,0.4082013,0.00240647],"study_design_scores_gemma":[0.00367304,0.001442186,0.05295893,0.003232248,0.001536276,0.0004609432,0.0001049317,0.0019559,0.831446,0.02327787,0.07808141,0.001830261],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2178194,0.0006264166,0.5959032,0.007791939,0.001436626,0.007434595,0.0001211406,0.004143016,0.1647237],"genre_scores_gemma":[0.7191165,0.00002439148,0.2757438,0.001818477,0.001290198,0.0002840321,0.0002900083,0.00007587088,0.001356669],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5012972,"threshold_uncertainty_score":0.9906387,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05831842742761784,"score_gpt":0.3258114194210819,"score_spread":0.267492991993464,"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."}}