{"id":"W2355601080","doi":"","title":"The Hardware Design of Automatic Collimation System Based on Image Processing","year":2006,"lang":"en","type":"article","venue":"Laser & Infrared","topic":"Image Processing Techniques and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"L'Alliance Boviteq","funders":"","keywords":"Computer vision; Computer science; Image processing; Missile; Artificial intelligence; Collimated light; Image quality; Image (mathematics); Software; Depth of field; Aperture (computer memory); Computer graphics (images); Field (mathematics); Optics; Mathematics; Laser; Physics; Engineering; Acoustics","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":[0.0001572733,0.0001055566,0.0001072354,0.0000479535,0.0001723437,0.0001037465,0.0001520201,0.0000453301,0.00000576047],"category_scores_gemma":[0.00001546645,0.00008244511,0.00003070398,0.0002355276,0.00003514678,0.0001093131,0.000008359236,0.00006965428,0.00001240314],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007129158,"about_ca_system_score_gemma":0.00003302741,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004797696,"about_ca_topic_score_gemma":6.134484e-7,"domain_scores_codex":[0.9993489,0.0000218791,0.0002518465,0.000091305,0.0001439123,0.0001421148],"domain_scores_gemma":[0.9995051,0.00007613104,0.00007791052,0.00023518,0.00008850019,0.00001716383],"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":[0.00006768994,0.0002823995,0.0001630165,0.007318167,0.00004571521,0.00001544008,0.0004360104,0.7479549,0.09355003,0.003953805,0.07866333,0.0675495],"study_design_scores_gemma":[0.0001311615,0.00001336117,0.0001658142,0.0002714691,0.00001269642,0.000001084376,0.00003307786,0.9274282,0.07060473,0.000508924,0.0007391379,0.00009030563],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002927637,0.0001126182,0.983581,0.00007167541,0.00003552794,0.0004735548,0.00001705807,0.00128789,0.01149305],"genre_scores_gemma":[0.9062513,0.000001985859,0.09323261,0.0000183569,0.00002983107,0.0002522056,0.00002005811,0.00003093648,0.0001627566],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9033237,"threshold_uncertainty_score":0.3362014,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008056626976411841,"score_gpt":0.2153747284754406,"score_spread":0.2073181014990287,"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."}}