{"id":"W4413364820","doi":"10.20944/preprints202508.1333.v1","title":"Comparative Analysis of Foundational and Traditional Deep Learning Models for Hyperpolarized Gas MRI Lung Segmentation: Robust Performance in Data-Constrained Scenarios","year":2025,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Atomic and Subatomic Physics Research","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Segmentation; Deep learning; Artificial intelligence; Computer science; Machine learning","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002583353,0.00168498,0.0009839601,0.000759313,0.0003602389,0.001034756,0.001405706,0.001538564,0.0009122716],"category_scores_gemma":[0.006708533,0.0003749516,0.000752575,0.0005248527,0.0006265389,0.001705882,0.001286588,0.001352821,0.0004270994],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001077703,"about_ca_system_score_gemma":0.001469342,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01244837,"about_ca_topic_score_gemma":0.01196021,"domain_scores_codex":[0.9991255,0.0002094983,0.00006578584,0.0002761021,0.0001701863,0.0001528791],"domain_scores_gemma":[0.9981768,0.0009007052,0.0001488681,0.0002551611,0.0004047657,0.0001136955],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00145313,0.0003095506,0.009339713,0.0004602133,0.0003503443,0.0002119776,0.0001196338,0.7991561,0.007045004,0.001594889,0.004009677,0.1759498],"study_design_scores_gemma":[0.00002475917,0.0002674462,0.001867349,0.00003965705,0.00004812725,0.00005038822,0.00004643721,0.9921299,0.003777805,0.001142857,0.0005837874,0.0000214316],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8386824,0.008298066,0.1372609,0.001594196,0.000322241,0.0001875359,0.001792517,0.004752426,0.007109687],"genre_scores_gemma":[0.9658618,0.00101013,0.02815651,0.000298258,0.00004066055,0.00007698486,0.002816744,0.0001256414,0.001613392],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01244837,"threshold_uncertainty_score":0.02475184,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2368569899139507,"score_gpt":0.384253364128141,"score_spread":0.1473963742141903,"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."}}