{"id":"W3046132349","doi":"10.1007/978-3-030-47992-3_4","title":"Compilations: Designing and Using Archaeological Databases","year":2020,"lang":"en","type":"book-chapter","venue":"Interdisciplinary Contributions to Archaeology/Interdisciplinary contributions to archaeology","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Database; Computer science; Metadata; Relational database; Database design; Redundancy (engineering); Database model; Data redundancy; View; Information retrieval; World Wide Web","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":[0.004250232,0.001057156,0.001018855,0.004954371,0.001398652,0.009235237,0.003133328,0.0008611714,0.01036442],"category_scores_gemma":[0.01615509,0.002214606,0.001147825,0.005668812,0.002369019,0.01069311,0.00526346,0.001524899,0.004080593],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008296861,"about_ca_system_score_gemma":0.002243214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003797842,"about_ca_topic_score_gemma":0.006192547,"domain_scores_codex":[0.9966568,0.0008949957,0.0004521168,0.0006376151,0.001229602,0.0001289537],"domain_scores_gemma":[0.9921163,0.004590479,0.0003674064,0.001883596,0.0008014416,0.0002407532],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000119581,0.00009953768,0.00350921,0.001688826,0.0001358993,0.0006416088,0.01154164,0.005496478,0.007179107,0.1446663,0.07645102,0.7484708],"study_design_scores_gemma":[0.00006234259,0.0000589399,0.002229694,0.0006572334,0.0002151262,0.0009065151,0.005492603,0.03563512,0.02438174,0.1565631,0.7736888,0.0001087338],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008258088,0.001292212,0.9439803,0.0006508268,0.0002257485,0.0003635957,0.002479047,0.02509826,0.01765186],"genre_scores_gemma":[0.05533607,0.001946104,0.9029425,0.0003552341,0.0001433427,0.00041831,0.007337107,0.00982494,0.02169633],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01036442,"threshold_uncertainty_score":0.03467244,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03578809629777251,"score_gpt":0.3499177429721882,"score_spread":0.3141296466744157,"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."}}