{"id":"W4406093517","doi":"10.48550/arxiv.2501.01912","title":"Exoplanet Detection via Differentiable Rendering","year":2025,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Astronomy and Astrophysical 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; National Aeronautics and Space Administration; Space Telescope Science Institute; National Science Foundation","keywords":"Rendering (computer graphics); Differentiable function; Exoplanet; Computer science; Computer graphics (images); Computer vision; Mathematics; Pure mathematics","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":[0.0004360942,0.0008649057,0.0006299537,0.0006664206,0.0002639626,0.002159964,0.0009180895,0.0007447227,0.003816325],"category_scores_gemma":[0.002065733,0.0003383828,0.0008546737,0.0003657647,0.0006750444,0.0007898973,0.001448249,0.001553663,0.0007554643],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006568666,"about_ca_system_score_gemma":0.000629703,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00349044,"about_ca_topic_score_gemma":0.004763064,"domain_scores_codex":[0.9997366,0.00004550629,0.000009730888,0.0000457525,0.0001353268,0.00002692569],"domain_scores_gemma":[0.999467,0.0002589138,0.00005001336,0.00009148254,0.00008629872,0.00004639175],"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":[0.0001947853,0.0001175978,0.001982218,0.0001608595,0.0000594634,0.0003417806,0.0003385308,0.7726935,0.04474398,0.02690961,0.005812472,0.1466452],"study_design_scores_gemma":[0.000007769643,0.000009568917,0.00007467551,0.000003363654,0.000002434875,0.00002692215,0.000009632964,0.9933438,0.002010249,0.003289659,0.00121607,0.000005729221],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01702069,0.00008172412,0.9768755,0.0001563375,0.00003914269,0.0000332811,0.0000944052,0.002468207,0.003230603],"genre_scores_gemma":[0.4439463,0.0002814283,0.5485156,0.0001652101,0.000063088,0.00007199834,0.0004124889,0.001541048,0.005002873],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003816325,"threshold_uncertainty_score":0.0127669,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04257232601458494,"score_gpt":0.1884717489655125,"score_spread":0.1458994229509276,"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."}}