{"id":"W6907150797","doi":"10.20383/103.01188","title":"Panoramic image set and deep learning model for monitoring Double-crested Cormorant nesting on the Ironworkers Memorial Second Narrows Bridge in Vancouver, British Columbia, Canada.","year":2025,"lang":"en","type":"dataset","venue":"Open MIND","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Nesting (process); Bridge (graph theory); Cormorant; Deep learning; Workflow; Set (abstract data type); Object detection","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001798257,0.0006873512,0.001229131,0.0001738534,0.001043976,0.003720794,0.001874007,0.0004825201,0.000409044],"category_scores_gemma":[0.001023046,0.0009493401,0.0001097043,0.0006299639,0.0001841736,0.0005231266,0.001056785,0.001937102,0.0000162795],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001375942,"about_ca_system_score_gemma":0.003247409,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9447749,"about_ca_topic_score_gemma":0.9993877,"domain_scores_codex":[0.9950276,0.0003655725,0.001080501,0.001591116,0.0007416157,0.001193576],"domain_scores_gemma":[0.9962468,0.001443549,0.00087412,0.0009554993,0.0002285519,0.0002515313],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007780213,0.00005890574,0.0005725484,0.0002024042,0.0001285214,0.0003536915,0.0001664131,0.007257495,0.00006243258,4.809299e-8,0.9845665,0.005852989],"study_design_scores_gemma":[0.01308473,0.000166984,0.001077315,0.003969428,0.0005179402,0.00005655529,0.001837409,0.06936292,0.00006331104,0.00001521485,0.9076763,0.002171829],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.1928539,0.0001923373,0.000007616598,0.00001657933,0.001974732,0.003888776,0.8008897,0.000008432672,0.0001679392],"genre_scores_gemma":[0.01680488,0.00005092117,0.001120033,0.00005845387,0.0006597869,0.0007120617,0.9731605,0.0002215765,0.00721181],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.176049,"threshold_uncertainty_score":0.9992957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03561036411439009,"score_gpt":0.2884530627395924,"score_spread":0.2528426986252023,"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."}}