{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001083227,0.003053954,0.002094663,0.003625359,0.001657242,0.002667227,0.003038563,0.002771893,0.02470288],"category_scores_gemma":[0.003281853,0.0007593861,0.001969069,0.00502221,0.0006618955,0.001073146,0.003285109,0.001744669,0.03756955],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00100941,"about_ca_system_score_gemma":0.002004178,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02520237,"about_ca_topic_score_gemma":0.06075056,"domain_scores_codex":[0.999115,0.0001125963,0.00006815665,0.0003412921,0.0001896949,0.0001732368],"domain_scores_gemma":[0.9990506,0.0002457803,0.00009533551,0.0002468176,0.0001765964,0.000184912],"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":[0.0004836233,0.00007315852,0.005717707,0.001874787,0.0002508268,0.0001598758,0.0001748236,0.0007948174,0.003078079,0.0006254624,0.9809676,0.005799319],"study_design_scores_gemma":[0.001050197,0.0001094725,0.03975362,0.0007855027,0.0003507107,0.0003751115,0.000437362,0.001917057,0.00338138,0.002991352,0.9487174,0.0001308133],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00181714,0.0004006071,0.0001466959,0.00007938268,0.00005959884,0.00001547749,0.9955776,0.00101466,0.0008889298],"genre_scores_gemma":[0.001258162,0.00008707502,0.0003721484,0.00004140564,0.000008269723,0.00004042141,0.997769,0.00008965206,0.0003338865],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02520237,"threshold_uncertainty_score":0.08263934,"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."}}