{"id":"W4387362556","doi":"10.1117/12.2676818","title":"Gemini planet imager 2.0: implementing a Zernike wavefront sensor for non-common path aberrations measurement","year":2023,"lang":"en","type":"article","venue":"","topic":"Adaptive optics and wavefront sensing","field":"Physics and Astronomy","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Herzberg Institute of Astrophysics","funders":"","keywords":"Wavefront sensor; Adaptive optics; Coronagraph; Testbed; Computer science; Telescope; Wavefront; Zernike polynomials; Upgrade; Offset (computer science); Optics; Real-time computing; Remote sensing; Physics; Computer vision; Exoplanet; Geology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001019945,0.0004443213,0.0003054037,0.0007722813,0.0003882372,0.0007353405,0.001053292,0.0006202792,0.002799018],"category_scores_gemma":[0.00120041,0.000359438,0.0002868026,0.0006584552,0.0002884092,0.001055725,0.0008893115,0.0007821233,0.001569611],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004977429,"about_ca_system_score_gemma":0.0005778546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002493939,"about_ca_topic_score_gemma":0.003526227,"domain_scores_codex":[0.9994247,0.00004021867,0.00001815329,0.00009881615,0.0003530146,0.00006520974],"domain_scores_gemma":[0.9995579,0.00004162789,0.00004598406,0.0001395653,0.0001638133,0.0000509842],"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":[0.0009153893,0.0003035911,0.02951811,0.0002586632,0.0001388485,0.0003660037,0.0008635324,0.009925387,0.5832031,0.008732599,0.0513415,0.3144332],"study_design_scores_gemma":[0.0002030411,0.0009330151,0.04570661,0.00004102977,0.00007153501,0.0007442349,0.0002351559,0.195307,0.5659323,0.002871548,0.187741,0.0002134462],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1932502,0.0002843896,0.6839432,0.0006136656,0.0002924524,0.0005807631,0.005228065,0.0959462,0.01986101],"genre_scores_gemma":[0.3149343,0.0001044889,0.672087,0.000207464,0.00004760195,0.0001747954,0.005799636,0.002234652,0.004410048],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002799018,"threshold_uncertainty_score":0.009363592,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03427013391215093,"score_gpt":0.2746121681446636,"score_spread":0.2403420342325127,"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."}}