{"id":"W4214622630","doi":"10.1002/oa.3096","title":"Practice makes perfect? Inter‐analyst variation in the identification of fish remains from archaeological sites","year":2022,"lang":"en","type":"article","venue":"International Journal of Osteoarchaeology","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Zoo; Occupational Cancer Research Centre; SGS (Canada); University of Toronto","funders":"","keywords":"Optimal distinctiveness theory; Identification (biology); Fish <Actinopterygii>; Archaeology; Species identification; Set (abstract data type); Species richness; Geography; Biology; Evolutionary biology; Computer science; Ecology; Psychology; Fishery","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.05242963,0.0002496911,0.0003095345,0.001786443,0.001573743,0.002571043,0.001365393,0.000711289,0.0007425619],"category_scores_gemma":[0.1480851,0.0005401604,0.0002363676,0.000895919,0.003284459,0.001876238,0.002959823,0.0006108088,0.0002639249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001159767,"about_ca_system_score_gemma":0.001197129,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006872599,"about_ca_topic_score_gemma":0.01847254,"domain_scores_codex":[0.9211828,0.04487999,0.006747355,0.007716447,0.0172319,0.002241518],"domain_scores_gemma":[0.8231129,0.1264894,0.0195713,0.01222976,0.01646134,0.002135327],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007971842,0.0002073367,0.6981654,0.0003213172,0.0003345654,0.0007031141,0.1947387,0.0005607656,0.01341067,0.0009932278,0.001986563,0.08778122],"study_design_scores_gemma":[0.00002828129,0.0007959525,0.8321958,0.0002185075,0.0001011965,0.00145381,0.1445387,0.002177889,0.006223924,0.001918736,0.01019572,0.0001514586],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946654,0.000170713,0.00288303,0.0002693614,0.00003243684,0.0000465261,0.00003431267,0.0000299825,0.001868179],"genre_scores_gemma":[0.9977723,0.00006406126,0.001754992,0.00008855752,0.000009408033,0.00002891237,0.00003264082,0.00001338956,0.0002357146],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9475704,"threshold_uncertainty_score":0.2772777,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01419781563144644,"score_gpt":0.2678068895934687,"score_spread":0.2536090739620222,"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."}}