{"id":"W2922503731","doi":"10.2113/jeeg23.4.469","title":"The Warr Machine: System Design, Implementation and Data","year":2018,"lang":"en","type":"article","venue":"Journal of Environmental and Engineering Geophysics","topic":"Geophysical Methods and Applications","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Research Canada","funders":"","keywords":"Ground-penetrating radar; Offset (computer science); Geology; Software deployment; Computer science; Data processing; Transmitter; Remote sensing; Radar; Telecommunications; Database","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":[0.001792947,0.0008799449,0.0006963541,0.001197175,0.0003799012,0.001627152,0.001935863,0.0008672457,0.01533268],"category_scores_gemma":[0.003104966,0.0005704304,0.000257041,0.0006724643,0.0005096545,0.002280263,0.001254066,0.0007580536,0.008004975],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005648967,"about_ca_system_score_gemma":0.001100905,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001209811,"about_ca_topic_score_gemma":0.0006702368,"domain_scores_codex":[0.9984869,0.0003374443,0.0001126505,0.0002816179,0.0006588536,0.0001226593],"domain_scores_gemma":[0.9985836,0.0002381005,0.00008131465,0.000318341,0.0006766119,0.0001020809],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00143744,0.0005851866,0.01303099,0.0007521753,0.0001036517,0.0009908434,0.0007640291,0.02444108,0.1294107,0.01193129,0.04781992,0.7687328],"study_design_scores_gemma":[0.0004463788,0.00368578,0.007837121,0.0002361616,0.0001078068,0.001746208,0.0004714346,0.5070267,0.2602602,0.005544794,0.2124093,0.0002280159],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05255789,0.0003213266,0.8814542,0.0008860904,0.0002224784,0.002702606,0.001010286,0.04687881,0.01396622],"genre_scores_gemma":[0.3628609,0.0003554321,0.6067767,0.0007788398,0.0002140147,0.002217633,0.002759255,0.00192106,0.02211633],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01533268,"threshold_uncertainty_score":0.0512929,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01230095151393533,"score_gpt":0.2361956636891027,"score_spread":0.2238947121751674,"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."}}