{"id":"W4398381531","doi":"10.7910/dvn/29787","title":"Gender-specific assessment of natural resources using the pebble game.","year":2015,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Water resources management and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pebble; Natural (archaeology); Natural resource; Computer science; Geography; Biology; Ecology; Archaeology","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003198162,0.0003001424,0.0003098068,0.0001993653,0.00006762353,0.0001513286,0.0007841639,0.0001346845,0.001765501],"category_scores_gemma":[0.00001237685,0.0002317417,0.00008846355,0.0002128174,0.00007623635,0.0002239705,0.0003750144,0.0003836741,0.001020455],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001392339,"about_ca_system_score_gemma":0.00002424458,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007031347,"about_ca_topic_score_gemma":0.00002063635,"domain_scores_codex":[0.9985215,0.00007034034,0.0003519969,0.0002594592,0.0005198289,0.0002768766],"domain_scores_gemma":[0.9986226,0.00002859006,0.0001556785,0.001065633,0.00006679923,0.00006071009],"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":[0.000007071255,0.00001466151,0.000006697063,0.0001911939,0.0001083667,0.00001120393,0.00009835277,0.08993753,0.00002116316,0.000008348456,0.9095498,0.00004559553],"study_design_scores_gemma":[0.0002575528,0.00001059043,0.00003105917,0.00005325854,0.0001354292,0.000003454654,0.0001670521,0.05681778,0.0000121036,0.0000075602,0.9422619,0.0002422031],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004009987,0.00004337252,0.001586479,0.000001712585,0.001043369,0.0003810592,0.9956238,0.000102759,0.0008164955],"genre_scores_gemma":[0.001114883,0.0004672568,0.001346492,0.00002202189,0.0003157011,0.000009146936,0.9965604,0.00004361158,0.0001205008],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03311976,"threshold_uncertainty_score":0.9997573,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03483671507806895,"score_gpt":0.2512108873812,"score_spread":0.2163741723031311,"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."}}