{"id":"W2569899632","doi":"10.1039/c6me00079g","title":"Non-conventional charge transport in organic semiconductors: magnetoresistance and thermoelectricity","year":2017,"lang":"en","type":"article","venue":"Molecular Systems Design & Engineering","topic":"Advanced Thermoelectric Materials and Devices","field":"Materials Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"Engineering and Physical Sciences Research Council","keywords":"Magnetoresistance; Thermoelectric effect; Thermoelectric materials; Seebeck coefficient; Condensed matter physics; Materials science; Resistive touchscreen; Semiconductor; Thermal conductivity; Charge (physics); Electrical resistivity and conductivity; Magnetic field; Charge carrier; Optoelectronics; Physics; Electrical engineering; Composite material; Thermodynamics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005089905,0.0002247398,0.0003390335,0.00008841858,0.0001273014,0.0001672576,0.0003344029,0.00009405835,0.0001405098],"category_scores_gemma":[0.00004157212,0.000218637,0.00003658419,0.00008224555,0.00003036852,0.0002759096,0.00003069801,0.00009659984,0.00001984483],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006512256,"about_ca_system_score_gemma":0.00003711547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001414826,"about_ca_topic_score_gemma":0.00000538647,"domain_scores_codex":[0.9986667,0.00004137549,0.0003274638,0.0003760079,0.0002052238,0.0003832228],"domain_scores_gemma":[0.9993031,0.00002817738,0.000165565,0.000384386,0.00003732549,0.00008143015],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002017157,0.00001331078,0.0002552772,0.0001143036,0.000007877356,0.00008483425,0.00005151561,0.001428865,0.9968562,0.001142878,0.000005410043,0.00001939208],"study_design_scores_gemma":[0.0006044855,0.00005918012,0.006422772,0.0001903932,0.00001557202,0.00004126851,0.000006833837,0.01172548,0.9802358,0.0000774982,0.0002310461,0.0003896329],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8753213,0.001452978,0.1222641,0.00001072052,0.0003773173,0.000360722,0.000006359622,0.00006620085,0.0001403648],"genre_scores_gemma":[0.9987614,0.00003664335,0.0008650323,0.00001062148,0.00007838683,0.00006651186,0.000002657751,0.00004095457,0.0001378047],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1234401,"threshold_uncertainty_score":0.8915759,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009339949279912175,"score_gpt":0.2073745908713196,"score_spread":0.1980346415914075,"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."}}