{"id":"W6964268295","doi":"10.25345/c57659s53","title":"MassIVE MSV000095054 - Leave no stone unturned: Exploring the metaproteome of beerstone for the identification of archaeological beer production","year":2024,"lang":"en","type":"dataset","venue":"UC San Diego","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Identification (biology); Production (economics); Production system (computer science); Work (physics)","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003186566,0.0006670129,0.0009882005,0.0005460132,0.0002896966,0.00006898795,0.001600381,0.0003295153,0.0003799304],"category_scores_gemma":[0.002896412,0.0003871946,0.0005958806,0.0009808501,0.001739782,0.0003027161,0.0006613688,0.001110197,0.002531609],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002691392,"about_ca_system_score_gemma":0.0001524551,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002498609,"about_ca_topic_score_gemma":0.0003875788,"domain_scores_codex":[0.9949776,0.0004146417,0.001582375,0.001166119,0.001270186,0.0005890946],"domain_scores_gemma":[0.9941222,0.0008577058,0.001721822,0.002399962,0.0008172871,0.00008100862],"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":[0.0005195367,0.0001992434,0.000005456803,0.001001474,0.001075239,0.000006265175,0.0008398105,0.0004360471,0.02555072,0.0003256488,0.9695584,0.000482206],"study_design_scores_gemma":[0.0005327829,0.0004715141,0.0009221294,0.0004887207,0.00370476,0.00002941697,0.001942322,0.0002012684,0.08597094,0.002478583,0.9025499,0.0007076624],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.008773546,0.002346464,0.0001703555,0.0008611285,0.003086014,0.004946187,0.9796916,0.0001100358,0.00001465863],"genre_scores_gemma":[0.03939561,0.0006755472,0.0003774418,0.00003872658,0.00237762,0.006004838,0.949657,0.0002699097,0.001203283],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06700844,"threshold_uncertainty_score":0.999858,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07018165596531922,"score_gpt":0.3061503246578547,"score_spread":0.2359686686925355,"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."}}