{"id":"W4239206408","doi":"10.31227/osf.io/hwkxe","title":"Identifikasi Potensi Airtanah pada Area dengan Beragam Bentuklahan Menggunakan Beberapa Parameter Lapangan dan Pendekatan SIG di Kawasan Parangtritis, DIY","year":2017,"lang":"id","type":"preprint","venue":"","topic":"Geological and Geophysical Studies","field":"Earth and Planetary Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Encana (Canada); WiLAN (Canada)","funders":"","keywords":"Forestry; Hydrology (agriculture); Physics; Geomorphology; Environmental science; Geology; Geography; Geotechnical engineering","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":[0.001445704,0.0008324459,0.0008314077,0.002635701,0.001344157,0.004134445,0.0006688269,0.001060035,0.0103341],"category_scores_gemma":[0.002731442,0.0005172249,0.0007239556,0.003299468,0.0007093773,0.002284135,0.001713613,0.0008045964,0.003089129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001070684,"about_ca_system_score_gemma":0.00155296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01927907,"about_ca_topic_score_gemma":0.04889042,"domain_scores_codex":[0.9985318,0.0002042305,0.00009578401,0.0004441155,0.0005721262,0.0001519633],"domain_scores_gemma":[0.9978167,0.0006097933,0.0003139321,0.0002501012,0.0009075,0.0001020165],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005551479,0.0001546491,0.6466888,0.002213915,0.0002845099,0.001673448,0.007026095,0.003136282,0.07194163,0.002565884,0.00740272,0.2563569],"study_design_scores_gemma":[0.00002453725,0.0002881936,0.842766,0.0005562748,0.0005487285,0.001776946,0.02348215,0.006908508,0.03692357,0.003264752,0.08331063,0.0001496838],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8982004,0.004305401,0.03690759,0.001157469,0.0002207932,0.0004008361,0.01018372,0.001122706,0.04750104],"genre_scores_gemma":[0.9398167,0.002261258,0.03073979,0.0002576867,0.00005033618,0.0002255804,0.005214761,0.0003279684,0.02110605],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01927907,"threshold_uncertainty_score":0.03833371,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03611595760827917,"score_gpt":0.2353885564178982,"score_spread":0.199272598809619,"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."}}