{"id":"W3181114435","doi":"10.48550/arxiv.2107.04902","title":"Industry and Academic Research in Computer Vision","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Citation; Field (mathematics); Preference; Computer science; Work (physics); Distribution (mathematics); Data science; Join (topology); Set (abstract data type); Operations research; Library science; Engineering; Economics","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":["research_integrity"],"consensus_categories":["research_integrity"],"category_scores_codex":[0.0006872014,0.0001834283,0.0002798807,0.0005466222,0.00007252977,0.00007860415,0.0001972249,0.002435552,0.00002711661],"category_scores_gemma":[0.00001448948,0.000221113,0.00006066958,0.0006887873,0.00005663815,0.0001526288,0.0005825097,0.006276979,0.000021317],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002761996,"about_ca_system_score_gemma":0.00006010414,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002343757,"about_ca_topic_score_gemma":0.0000448096,"domain_scores_codex":[0.9986331,0.0002348891,0.0002066104,0.0005302156,0.0001029608,0.0002921981],"domain_scores_gemma":[0.9993029,0.0001117635,0.00003863191,0.0003470774,0.0000842027,0.0001153988],"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":[0.00005022236,0.00002607271,0.006545097,0.0003177553,0.00005262874,0.0007829486,0.0003015864,0.9809839,0.0005869725,0.0006278761,0.001016723,0.008708249],"study_design_scores_gemma":[0.001118797,0.0001048247,0.009511753,0.001673311,0.00002401998,0.00002935259,0.0006365682,0.9824944,0.0006473879,0.001715758,0.00142316,0.0006206256],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9897859,0.0002116073,0.007784844,0.00001637322,0.0009437954,0.0002418808,0.000004663806,0.0001219428,0.0008890341],"genre_scores_gemma":[0.9991511,0.0003198473,0.00003741577,0.000008440325,0.0002954458,9.319323e-7,0.000007799787,0.00002510522,0.0001538898],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009365266,"threshold_uncertainty_score":0.9988595,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1933225886815539,"score_gpt":0.2626880729983533,"score_spread":0.06936548431679943,"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."}}