{"id":"W3133585374","doi":"","title":"Building a Comprehensive Repository for Montreal Gamelan Archives","year":2020,"lang":"en","type":"article","venue":"World Academy of Science, Engineering and Technology, International Journal of Humanities and Social Sciences","topic":"Digital Games and Media","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Library science; Computer science","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":[0.008983387,0.001200167,0.001405912,0.03135684,0.006135297,0.01039455,0.005740699,0.001382577,0.06211962],"category_scores_gemma":[0.03086699,0.001173876,0.000904504,0.03092144,0.001528857,0.01109085,0.009734895,0.002014471,0.02866198],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01031491,"about_ca_system_score_gemma":0.03873247,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3849841,"about_ca_topic_score_gemma":0.4725155,"domain_scores_codex":[0.9949378,0.0007428476,0.0005965118,0.0007529449,0.002532033,0.0004379373],"domain_scores_gemma":[0.965911,0.003361114,0.001504984,0.007525815,0.01797202,0.003725044],"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":[0.0002816836,0.0002644031,0.01297127,0.001624089,0.0001322189,0.0006882664,0.005563114,0.002499708,0.00411967,0.01747325,0.6706556,0.2837267],"study_design_scores_gemma":[0.00004078505,0.00003665965,0.007642247,0.000596286,0.0001088758,0.0001782975,0.002734253,0.003031382,0.002845894,0.003028383,0.979587,0.0001698259],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.03403344,0.004080356,0.118217,0.006469775,0.001243946,0.006276186,0.5902554,0.0819108,0.1575131],"genre_scores_gemma":[0.07454471,0.003407796,0.2629408,0.0009413387,0.0003207224,0.00275837,0.5531505,0.01923839,0.08269743],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6150159,"threshold_uncertainty_score":0.7654864,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03213558190212908,"score_gpt":0.2973940865850881,"score_spread":0.265258504682959,"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."}}