{"id":"W2106152599","doi":"10.1109/crv.2008.30","title":"Eye-In-Hand Visual Servoing for Accurate Shooting in Pool Robotics","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Artificial intelligence; Computer vision; Visual servoing; Computer science; Robot; Robotics; Image plane; Image (mathematics)","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":[0.0001748408,0.00009726603,0.0001371889,0.0001342075,0.000117807,0.00007604737,0.0002904499,0.00002540317,0.000004555323],"category_scores_gemma":[0.00008560132,0.00008952134,0.00003214519,0.0003580765,0.0000199612,0.0007583712,0.0001576982,0.0001027317,0.00001157439],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003772597,"about_ca_system_score_gemma":0.00004293528,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001515765,"about_ca_topic_score_gemma":0.00003566782,"domain_scores_codex":[0.9990335,0.0000192723,0.0002419961,0.0002752428,0.0001124295,0.0003175384],"domain_scores_gemma":[0.9995951,0.0001140585,0.00004570401,0.0001552263,0.00003874425,0.0000511691],"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":[0.00006812895,0.0006236319,0.1129311,0.0001461517,0.00001802597,0.0004574756,0.009011761,0.4204619,0.03086952,0.03413175,0.0008019163,0.3904786],"study_design_scores_gemma":[0.000576271,0.00002770066,0.006140689,0.000038682,4.190999e-7,0.0000101639,0.00008564277,0.98847,0.003713886,0.0005627578,0.0002367585,0.0001370413],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0478045,0.00003148038,0.9506134,0.0006785135,0.0001338649,0.0001411164,1.554144e-7,0.00006095941,0.0005360201],"genre_scores_gemma":[0.7110304,0.000008197999,0.2881279,0.0004824801,0.0000240351,0.000004906771,5.179342e-7,0.000006408424,0.0003150933],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6632259,"threshold_uncertainty_score":0.3650574,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03432233444326985,"score_gpt":0.3396501048730274,"score_spread":0.3053277704297576,"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."}}