{"id":"W1963590456","doi":"10.1145/2659021.2659050","title":"A Negotiation Protocol with Conditional Offers for Camera Handoffs","year":2014,"lang":"en","type":"article","venue":"","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Computer science; Handover; Negotiation; Task (project management); Protocol (science); State (computer science); Scheme (mathematics); Camera auto-calibration; Computer vision; Artificial intelligence; Real-time computing; Computer network; Camera resectioning; Engineering; Algorithm","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":[0.003346161,0.0006327261,0.0007978144,0.0005456895,0.001298194,0.002337089,0.002398184,0.001566582,0.006163448],"category_scores_gemma":[0.00921825,0.0004765693,0.0009354571,0.000777542,0.001534752,0.005715156,0.002834075,0.002445752,0.0007580015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001197726,"about_ca_system_score_gemma":0.001806294,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001662122,"about_ca_topic_score_gemma":0.0009576803,"domain_scores_codex":[0.9975303,0.0009783414,0.000198445,0.000387848,0.0006445039,0.0002605462],"domain_scores_gemma":[0.9963964,0.002108119,0.0003879146,0.0004434769,0.0003177015,0.0003464118],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007405405,0.0002707805,0.000909791,0.0002712055,0.0001112843,0.0008218641,0.001401125,0.1834342,0.008916989,0.7115991,0.004886498,0.08663667],"study_design_scores_gemma":[0.0001044208,0.0001457665,0.0001437614,0.00003634698,0.00004472504,0.0002772827,0.000188964,0.8894587,0.002507203,0.09498062,0.01205056,0.00006166824],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02013027,0.0003147066,0.9688552,0.0005053115,0.0001661682,0.000228301,0.0000657014,0.0002931283,0.009441159],"genre_scores_gemma":[0.7606875,0.0005338333,0.2265691,0.000218597,0.000154096,0.0006325845,0.0001681387,0.0001202848,0.0109159],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006163448,"threshold_uncertainty_score":0.0206188,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01683642924869188,"score_gpt":0.2986550536748215,"score_spread":0.2818186244261296,"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."}}