{"id":"W2949425747","doi":"10.48550/arxiv.1602.07383","title":"Automatic Moth Detection from Trap Images for Pest Management","year":2016,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Insect Pheromone Research and Control","field":"Agricultural and Biological Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Pipeline (software); PEST analysis; Software deployment; Trap (plumbing); Computer science; Integrated pest management; Field (mathematics); Artificial intelligence; Codling moth; Real-time computing; Software engineering; Engineering; Ecology; Biology; Lepidoptera genitalia; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004018335,0.0009837679,0.0005783086,0.001602003,0.0002315965,0.0005238735,0.000920457,0.0006410699,0.002474233],"category_scores_gemma":[0.0008622816,0.0002823642,0.0005817139,0.0006137131,0.0001613172,0.0006534393,0.0006891566,0.0006878813,0.001897132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004536021,"about_ca_system_score_gemma":0.0006204838,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003485107,"about_ca_topic_score_gemma":0.01025828,"domain_scores_codex":[0.9997359,0.00002716054,0.00001103236,0.0000920543,0.00008851686,0.00004528054],"domain_scores_gemma":[0.9996508,0.00008715741,0.00006380983,0.00006132787,0.0001025,0.00003438653],"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":[0.0004216715,0.0004923773,0.02168086,0.000579444,0.0001614553,0.0001492474,0.00007850377,0.01330805,0.1946197,0.0007357813,0.02054544,0.7472275],"study_design_scores_gemma":[0.00008065806,0.0004658643,0.05323633,0.0001305346,0.0001200586,0.0006689123,0.0001765773,0.7727308,0.1449941,0.004125064,0.02319582,0.0000751383],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3493815,0.007548441,0.591685,0.0008908812,0.0003719784,0.0006283008,0.01324455,0.02388114,0.01236821],"genre_scores_gemma":[0.544594,0.001872079,0.4296124,0.0003885842,0.0001304126,0.0002276499,0.01501847,0.0002905318,0.007865698],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003485107,"threshold_uncertainty_score":0.008277059,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0473172379568958,"score_gpt":0.1765363599304683,"score_spread":0.1292191219735725,"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."}}