{"id":"W3157817475","doi":"10.1364/oe.425191","title":"Compact and fast depth sensor based on a liquid lens using chromatic aberration to improve accuracy","year":2021,"lang":"en","type":"article","venue":"Optics Express","topic":"Image Processing Techniques and Applications","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Chromatic aberration; Optics; Depth of field; Lens (geology); Zemax; Depth of focus (tectonics); Focus (optics); Focal length; Measured depth; Achromatic lens; Computer science; Chromatic scale; Software; Physics","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":[0.00004252283,0.0001157982,0.0001159789,0.00004357632,0.00008456696,0.0001238717,0.00006207451,0.00004743009,0.000007872765],"category_scores_gemma":[0.00004560203,0.0001232512,0.00002184639,0.000117194,0.00001403582,0.0001084688,0.00001740561,0.00009334468,0.000005185504],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004093142,"about_ca_system_score_gemma":0.00002367294,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005613737,"about_ca_topic_score_gemma":0.000001460416,"domain_scores_codex":[0.9994564,0.00001004868,0.0001361545,0.0001559586,0.00009007656,0.0001513812],"domain_scores_gemma":[0.9995486,0.00005340984,0.00002610842,0.0002496363,0.0000635446,0.00005867654],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000006597601,0.00003485453,0.000005700098,0.0001318269,0.00000712707,0.000004666921,0.000197983,0.05588155,0.9418575,0.0001413459,0.0002039441,0.001526932],"study_design_scores_gemma":[0.00009957959,0.00003066739,0.00003584284,0.0001028302,0.0000127926,0.000004821641,0.00003831221,0.6247385,0.3742958,0.00002351218,0.0004939999,0.0001233782],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.39574,0.00005449933,0.5992877,0.0002708405,0.00006595735,0.0002630738,0.00002621045,0.0003380023,0.00395374],"genre_scores_gemma":[0.8813653,0.000009410581,0.1183197,0.0001575723,0.00004816855,0.00001956374,0.00001284351,0.00002976961,0.0000376444],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.568857,"threshold_uncertainty_score":0.5026038,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02349353301401243,"score_gpt":0.2794106680222883,"score_spread":0.2559171350082758,"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."}}