{"id":"W1993229211","doi":"10.1145/2422956.2422963","title":"Spider","year":2013,"lang":"en","type":"article","venue":"ACM Transactions on Multimedia Computing Communications and Applications","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; British Columbia Innovation Council","keywords":"Computer science; Precision and recall; Matching (statistics); Computer vision; Artificial intelligence; Realization (probability); Video tracking; Information retrieval; Video processing; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001387549,0.0001686816,0.0001540194,0.0001658084,0.0008448959,0.0002244775,0.002113908,0.00007045757,0.00002731705],"category_scores_gemma":[0.0000325373,0.0001650385,0.00006476506,0.0006035052,0.0001971313,0.000565882,0.0001761765,0.0003439748,0.0002149488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000337628,"about_ca_system_score_gemma":0.000029548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006065935,"about_ca_topic_score_gemma":0.000005047262,"domain_scores_codex":[0.9988823,0.00006876465,0.0003098697,0.0003683885,0.0001378025,0.0002328871],"domain_scores_gemma":[0.995489,0.0008166134,0.0001003216,0.003269341,0.00018082,0.0001438846],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[3.805816e-7,0.0002005255,0.00002496856,0.000004424718,0.0000118313,8.807076e-8,0.0001885016,0.00002383672,0.0005863578,0.00642045,0.0001158201,0.9924228],"study_design_scores_gemma":[0.001282008,0.0004108009,0.004781911,0.0001443061,0.00006819262,0.00007769573,0.0007236809,0.5663677,0.01661212,0.136477,0.2715299,0.001524694],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0002419623,0.0003273589,0.9904013,0.006566299,0.00003363692,0.0007562205,0.000004730126,0.0006373433,0.001031113],"genre_scores_gemma":[0.3738518,0.0006469439,0.6244444,0.0004917979,0.00002229917,0.0004101993,0.000006762998,0.00001199305,0.0001137966],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9908981,"threshold_uncertainty_score":0.6730073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02706555765660691,"score_gpt":0.3095773581382047,"score_spread":0.2825118004815978,"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."}}