{"id":"W7115040675","doi":"","title":"Calibration and validation strategies for 21 cm cosmology","year":2025,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Radio Astronomy Observations and Technology","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Science and Technology Facilities Council; Natural Sciences and Engineering Research Council of Canada; European Commission; Canadian Institute for Advanced Research; McGill University; Gordon and Betty Moore Foundation; National Research Foundation; Space Telescope Science Institute; Massachusetts Institute of Technology; National Aeronautics and Space Administration; National Science Foundation","keywords":"Calibration; Cosmology; Extrapolation; Term (time); Stability (learning theory)","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":[0.01984885,0.001817828,0.000936974,0.004237392,0.001584278,0.004095049,0.003570657,0.002106184,0.007459905],"category_scores_gemma":[0.05582063,0.0008155082,0.001474448,0.003297513,0.001528219,0.002843568,0.005677736,0.001844691,0.004250918],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001780065,"about_ca_system_score_gemma":0.003255304,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006770139,"about_ca_topic_score_gemma":0.00329824,"domain_scores_codex":[0.987691,0.005717341,0.0005109806,0.002100212,0.003230344,0.0007500671],"domain_scores_gemma":[0.976397,0.008892437,0.001991479,0.006041528,0.006067711,0.0006098594],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006461228,0.0002244044,0.07898801,0.0006316491,0.0006547623,0.0004227318,0.001165391,0.178236,0.01611038,0.1771085,0.01138471,0.5344273],"study_design_scores_gemma":[0.0001536158,0.0003330633,0.04397294,0.0007318205,0.0001977113,0.000598843,0.0008569061,0.6751097,0.02396446,0.1660436,0.08783419,0.0002031346],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04378766,0.001354152,0.9250173,0.0006593959,0.0002594534,0.0003535647,0.0009878646,0.00423095,0.02334967],"genre_scores_gemma":[0.4168331,0.0007693844,0.5716531,0.0005801468,0.0002571032,0.000756474,0.003530346,0.001192597,0.004427793],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01984885,"threshold_uncertainty_score":0.1049719,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01599564891405805,"score_gpt":0.2484524476965429,"score_spread":0.2324567987824848,"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."}}