{"id":"W2258463870","doi":"10.1145/2807442.2807496","title":"SHOCam","year":2015,"lang":"en","type":"article","venue":"","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; Simon Fraser University","funders":"","keywords":"Computer vision; Computer science; Artificial intelligence; Computer graphics (images); Object (grammar); Simple (philosophy); Camera auto-calibration; Scale (ratio); Path (computing); Camera resectioning; Geography","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":[0.0003970994,0.0008194224,0.0005636055,0.001072816,0.0004583666,0.001839204,0.001841426,0.00117218,0.0846539],"category_scores_gemma":[0.001601367,0.0005747719,0.0005370593,0.0007197459,0.000339837,0.00159874,0.002121818,0.0009151708,0.02612035],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003475573,"about_ca_system_score_gemma":0.0005621033,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001337274,"about_ca_topic_score_gemma":0.002378627,"domain_scores_codex":[0.9994212,0.00004375685,0.00002936844,0.0001244952,0.0003284719,0.00005266533],"domain_scores_gemma":[0.9993032,0.0001343586,0.00002835969,0.0001993121,0.000262726,0.00007210392],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005601842,0.0001166974,0.001452326,0.0007455825,0.00008143053,0.0003643752,0.0003214198,0.002301524,0.04591122,0.01496581,0.1517705,0.781409],"study_design_scores_gemma":[0.0001342513,0.000206638,0.002657378,0.0001404426,0.00006352894,0.001289944,0.0001661398,0.0508034,0.04191267,0.003941952,0.8985475,0.0001360647],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.01263646,0.001285376,0.8067259,0.0005092822,0.001118635,0.0006200841,0.004120507,0.05577378,0.11721],"genre_scores_gemma":[0.1191679,0.001496761,0.7261868,0.001826219,0.0003118211,0.0006433516,0.01368353,0.00859351,0.1280902],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.0846539,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04146210106619578,"score_gpt":0.2722389642002592,"score_spread":0.2307768631340634,"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."}}