{"id":"W7095794035","doi":"","title":"Spatial-genetic structuring in a red-breasted merganser (Mergus serrator) colony in the Canadian Maritimes","year":2011,"lang":"en","type":"article","venue":"","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Structuring; Context (archaeology); Scope (computer science); Key (lock)","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":[],"consensus_categories":[],"category_scores_codex":[0.000138792,0.0001058962,0.0001066412,0.000176269,0.00005460023,0.0001680539,0.0009164012,0.00006184176,0.0001752104],"category_scores_gemma":[0.00001176539,0.00008274858,0.0000194076,0.0003403553,0.00003081766,0.000465117,0.0001134043,0.0001114226,0.00004320895],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007221774,"about_ca_system_score_gemma":0.0002637616,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6082136,"about_ca_topic_score_gemma":0.954956,"domain_scores_codex":[0.999066,0.00005002159,0.000200674,0.0002674069,0.00009010917,0.0003257881],"domain_scores_gemma":[0.9993572,0.00002043594,0.00002817359,0.0004604194,0.00001711954,0.0001166324],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000358932,0.0002279316,0.6287894,0.00005078764,0.00004676013,0.001349494,0.01642009,0.00007396871,0.0000775185,0.1317728,0.007291654,0.2138637],"study_design_scores_gemma":[0.0003014103,0.0000389814,0.9857947,0.00001344727,0.000001680092,0.00004805569,0.0001289341,0.003592709,0.000314752,0.006886115,0.002671806,0.0002074081],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6283431,0.0001096056,0.002380535,0.002634252,0.0004377716,0.0005786011,0.00002600283,0.00009077164,0.3653994],"genre_scores_gemma":[0.9956908,0.000001904795,0.003189794,0.0009662537,0.00001355192,0.00001618162,0.000004243467,0.00000503185,0.0001122929],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3673477,"threshold_uncertainty_score":0.3943954,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02868711988129745,"score_gpt":0.196137664884466,"score_spread":0.1674505450031686,"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."}}