{"id":"W2735883825","doi":"","title":"Infrasense: Stories from the Horses Mouth. A project by KIT and Robert Saucier / Kit and Robert Saucier, Infrasense, Fonderie Darling, Montréal","year":2005,"lang":"en","type":"article","venue":"Érudit (Université de Montréal)","topic":"Cultural Insights and Digital Impacts","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00168555,0.001074223,0.00039749,0.0009137091,0.01509893,0.007177388,0.001299363,0.002148102,0.02095025],"category_scores_gemma":[0.003886608,0.0005616749,0.0002770846,0.001154203,0.008629913,0.005884253,0.005241702,0.004001251,0.002836767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005784874,"about_ca_system_score_gemma":0.004770572,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2188201,"about_ca_topic_score_gemma":0.5306693,"domain_scores_codex":[0.9988099,0.0005367928,0.00001462532,0.00007540103,0.000305175,0.0002581211],"domain_scores_gemma":[0.9979544,0.0007067356,0.00009655564,0.0001167103,0.0003445637,0.0007810226],"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":[0.00006825048,0.0000369221,0.0005484946,0.0001442038,0.000007546297,0.0006595583,0.1738013,0.00006241419,0.0005676518,0.01693757,0.7690753,0.03809083],"study_design_scores_gemma":[0.000005905918,0.00001521254,0.000938328,0.0001519089,0.000005768624,0.0001977177,0.09120346,0.00002661926,0.0002457243,0.0008190248,0.9063735,0.00001693944],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.08797214,0.05490768,0.005702539,0.239554,0.007864747,0.0002182004,0.002012565,0.001025971,0.6007422],"genre_scores_gemma":[0.3730661,0.01940061,0.002833176,0.0166973,0.001140504,0.0002019551,0.0005415494,0.001600547,0.5845182],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.7811799,"threshold_uncertainty_score":0.4350929,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01837054945103649,"score_gpt":0.1945864923499262,"score_spread":0.1762159428988897,"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."}}