{"id":"W2793573443","doi":"10.11575/prism/30643","title":"Artifacts as Instant Messenger Buddies","year":2008,"lang":"en","type":"article","venue":"","topic":"Personal Information Management and User Behavior","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Instant; Second messenger system; Computer science; Biology; Food science; Cell biology; Signal transduction","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.00218476,0.0006204667,0.0002925779,0.00221388,0.002166437,0.007897657,0.001344429,0.001506905,0.01365172],"category_scores_gemma":[0.006573192,0.0004954247,0.0004069261,0.001737517,0.002163401,0.004768182,0.004508277,0.0009944955,0.004330891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009239172,"about_ca_system_score_gemma":0.001006191,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001166203,"about_ca_topic_score_gemma":0.001434563,"domain_scores_codex":[0.9969151,0.001293948,0.0001982719,0.0003560786,0.0009652755,0.0002713832],"domain_scores_gemma":[0.9933558,0.001921844,0.00104851,0.002291327,0.0005151883,0.0008674184],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0006340502,0.0002031172,0.01538847,0.0006584671,0.00009767202,0.00390903,0.04930061,0.003642751,0.008797271,0.5271394,0.05342889,0.3368003],"study_design_scores_gemma":[0.000038545,0.0001658125,0.008958719,0.0003181744,0.00007306435,0.001802964,0.00806772,0.004343002,0.004004192,0.06560097,0.9065524,0.00007439635],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1990725,0.004138236,0.1974628,0.005561022,0.001338635,0.0006523911,0.001978501,0.005412302,0.5843835],"genre_scores_gemma":[0.8150265,0.001240179,0.06240994,0.000576036,0.0004826636,0.0003160221,0.001588493,0.0004192574,0.1179409],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01365172,"threshold_uncertainty_score":0.04566956,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4898447169992889,"score_gpt":0.4661963351478713,"score_spread":0.0236483818514176,"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."}}